PRE2019 3 Group1: Difference between revisions

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To finalize the project, interviews with a general practitioner were scheduled to derive some different perspectives for human factors that will influence the design of the band. This interview should enlight the project about user perspectives and some concerns that come with the usage of the band. This interview is a great way of getting a user perspective, since it was not possible to get the user perspective directly from a tremor patient. Besides, the interviews would give more insight into user perspective and into the functionality and specific needs for the design. Also, the general practitioner has more practical information in the medical practice regarding determining a diagnosis for tremor diseases and the exercises that are useful for this. This will give more information for possible revisions in for example the manual, the design and app used with the band or to change existing exercises and finetune the product before realizing it. Finally, for obtaining one of the most important human factor answers, the general practitioner is asked if the product is useful and relevant. This is a very important note for realizing the band into a successful project.
To finalize the project, interviews with a general practitioner were scheduled to derive some different perspectives for human factors that will influence the design of the band. This interview should enlight the project about user perspectives and some concerns that come with the usage of the band. This interview is a great way of getting a user perspective, since it was not possible to get the user perspective directly from a tremor patient. Besides, the interviews would give more insight into user perspective and into the functionality and specific needs for the design. Also, the general practitioner has more practical information in the medical practice regarding determining a diagnosis for tremor diseases and the exercises that are useful for this. This will give more information for possible revisions in for example the manual, the design and app used with the band or to change existing exercises and finetune the product before realizing it. Finally, for obtaining one of the most important human factor answers, the general practitioner is asked if the product is useful and relevant. This is a very important note for realizing the band into a successful project.
==Deliverables==
*Wiki page
*Model
*A prototype band
*Presentation


=State of art=
=State of art=
Line 448: Line 439:
==='''Model'''===
==='''Model'''===


For our product we used an Arduino Uno and the MPU6050 which contains a gyroscope and accelerometer. To make it function as intended we need to write a code for the Arduino. For our product we need to have as output the relative X,Y and Z positions. After some research online, code was written that fulfilled the requirements of the product. It now correctly puts out the relative X, Y and Z components. It appears however that the device needs about 10 seconds to calibrate its position. So this needs to be taken into account, we can only start measuring after those 10 seconds. The Arduino measures about 120 per second, meaning about 0.0083 seconds between measurements. Therefore the data we acquire is really accurate. The data is presented to us in the serial monitor, to do further research on this data we copied it into excel and after that into Matlab. The following code is used to analyze. We put a fast Fourier transform over the data and it puts out a graph where the amount of acceleration is plotted against the frequency. We can then see which frequency is the dominant one. This code is an example for the Y direction. We need to also look at the X and Z direction. We then look at these different axis to determine which has the highest frequency and amplitude and we select this axis to determine what the dominant frequency and amplitude is.       
For our product we used an Arduino Uno and the MPU6050 which contains a gyroscope and accelerometer. To make it function as intended we need to write a code for the Arduino. For our product we need to have as output the relative X,Y and Z positions. After some research online, code was written that fulfilled the requirements of the product. It now correctly puts out the relative X, Y and Z components. It appears however that the device needs about 10 seconds to calibrate its position. So this needs to be taken into account, we can only start measuring after those 10 seconds. The Arduino measures about 70 per second, meaning about 0.015 seconds between measurements. Therefore the data we acquire is really accurate. The data is presented to us in the serial monitor, to do further research on this data we copied it into excel and after that into Matlab. The following code is used to analyze. We put a fast Fourier transform over the data and it puts out a graph where the amount of acceleration is plotted against the frequency. We can then see which frequency is the dominant one. This code is an example for the Y direction. We need to also look at the X and Z direction. We then look at these different axis to determine which has the highest frequency and amplitude and we select this axis to determine what the dominant frequency and amplitude is.       




     data1 = Y_vect4(1:2000);
     data1 = Y_vect(1:2000);
     data = detrend(data1);
     data = detrend(data1);
     fs = 1/(1/100);
     fs = 1/(1/100);
Line 464: Line 455:
     plot(t,data);
     plot(t,data);


Unfortunately, the product was not able to be tested with actual tremors patients to see what the data would show in that case. This is why tremors were simulated to illustrate how the model works. After doing the plotting and testing with different tremors (the device was vibrated manually) the following things are found. In the measurement we did the Y values were most useful to look at as these gave a distinct dominant frequency. It appears that most of the movements are in the very low frequency range therefore most of the normal movements (no tremor) gave dominant frequency peaks around the 0-1 Hz range. When we however did a measurement with a constant higher frequency and plotted this we are able to see a dominant frequency namely at around 5 Hz. When looking at the signal plotted over time this does appear to be possible. The peaks were counted by the amount of peaks that are present in this plot within 3 seconds, these are 14 peaks. Meaning there are 14 oscillations in 3 seconds. When calculating this means there are about 4.667 oscillations per second, meaning 4.667 Hz.
Unfortunately, the product was not able to be tested with actual tremors patients to see what the data would show in that case. This is why tremors were simulated to illustrate how the model works. After doing the plotting and testing with different tremors (the device was vibrated manually) the following things are found. In the measurement we did the Y values were most useful to look at as these gave a distinct dominant frequency. It appears that most of the movements are in the very low frequency range therefore most of the normal movements (no tremor) gave dominant frequency peaks around the 0-1 Hz range. When we however did a measurement with a constant higher frequency and plotted this we are able to see a dominant frequency namely at around 5 Hz. When looking at the signal plotted over time this does appear to be possible. The peaks were counted by the amount of peaks that are present in this plot within 3 seconds, these are 14 peaks. Meaning there are 14 oscillations in 3 seconds. When calculating this means there are about 4.667 oscillations per second, meaning 4.667 Hz. For figure 6c we did another measurement where we tried to get an even higher frequency and as can be seen in the figure this happened we found a dominant frequency around 7 Hz.


[[File:domfreq.jpg|center|thumb|700px|Figure 6a: Fourier transform over signal, figure shows dominant frequency at around 5 Hz (highest peak)]]
[[File:domfreq.jpg|center|thumb|700px|Figure 6a: Fourier transform over signal, figure shows dominant frequency at around 5 Hz (highest peak)]]


[[File:signaltime2.jpg|center|thumb|700px|Figure 6b: Signal plotted over time]]
[[File:signaltime2.jpg|center|thumb|700px|Figure 6b: Signal plotted over time]]
[[File:domfreq7.jpg|center|thumb|700px|Figure 6c: Another Fourier transform over signal, this figure shows a dominant frequency around 7 Hz.]]


We also did a zero-measurement to see what the gyroscope and accelerometer would put out if there was no movement. To do this measurement we laid the device on a table without touching it. It does appear that we see some movement in the data, most likely due to an uncertainty in the gyroscope and accelerometer. In the figure below it can be seen that these peaks in the frequency spectrum show way lower powers, in the order of 1000x smaller. Meaning that this will have no significant impact on the tremor measurements.  
We also did a zero-measurement to see what the gyroscope and accelerometer would put out if there was no movement. To do this measurement we laid the device on a table without touching it. It does appear that we see some movement in the data, most likely due to an uncertainty in the gyroscope and accelerometer. In the figure below it can be seen that these peaks in the frequency spectrum show way lower powers, in the order of 1000x smaller. Meaning that this will have no significant impact on the tremor measurements.  
Line 478: Line 472:
Data of the band can be sent to an app on the phone of the doctor using an HC06 module. (Electronoobs, 2020) This allows for the sending of data via a Bluetooth connection between the HC06 module and the phone. The app shows a graph of the data, analyzed using a Fourier transform, from which the doctor can clearly read out the amplitude and frequency of the tremors of the patients.  
Data of the band can be sent to an app on the phone of the doctor using an HC06 module. (Electronoobs, 2020) This allows for the sending of data via a Bluetooth connection between the HC06 module and the phone. The app shows a graph of the data, analyzed using a Fourier transform, from which the doctor can clearly read out the amplitude and frequency of the tremors of the patients.  


The interface of the app is very simple and easy to use. The data of the band will automatically be send the band to the app, which then analyses the data and computes it into a graph.  
The interface of the app is very simple and easy to use. The data of the band will automatically be sent from the band to the app, which then analyzes the data and computes it into a graph.  


Basically the interface has two buttons. One for the graph and one for the statistics. One can switch between the two.
Basically the interface has two buttons. One for the graph and one for the statistics. One can switch between the two easily using these buttons.


The graph page shows on the top, two buttons with which you are able to switch between two graphs. The first graph is the data with on the x-axis the frequency in Hertz and on the y-axis the power of the corresponding frequency.  
The graph page shows two buttons at the top of the page with which you are able to switch between two graphs. The first graph is the data with on the x-axis the frequency in Hertz and on the y-axis the Power of the corresponding frequency.  


[[File:SR App image x3.PNG]]
[[File:X3.png|center|thumb|700px|Figure 7a: Dominant frequency measurement]]


The second graph show on the x-axis the elapsed time in seconds and on the y-axis the displacement in millimeter.  
The second graph shows on the x-axis the elapsed time in seconds and on the y-axis the displacement in millimeters. This is a visualization of how the tremor behaves over time.  


The statistics show a list of the important aspects of the graph, such as: Elapsed time, dominant frequency and the average displacement of the graphs.
[[File:SR_App_image_y3.png|center|thumb|700px|Figure 7b: Displacement per second measurement]]


The statistics show a list of the important aspects of the graphs, such as: Elapsed time, the dominant frequency and the average displacement of the graphs.


By using this app, the doctor can examine the data on his own time and call the patient back later in the day with the results. This saves a lot of back and forth to the hospital for the patient to be examined by a neurologist or other specialists.
[[File:SR_App_image_y.png|center|thumb|700px|Figure 7c: Statistics of the measurement]]
 
It is of utmost importance that the doctor takes into account the graphs as well as the statistics. The graphs can still give interesting information, like other peaks with a high power or the tremor pattern, which can also aid in determining a diagnosis. This is why the graphs are still shown, despite the fact that a doctor might be intimidated by them. The statistics aid the doctor in understanding the graphs better, to further lessen the intimidation factor of the graphs.
 
By using this app, the doctor can examine the data on his own time and call the patient back later in the day with the results. This saves a lot of back and forth to the hospital for the patient, where they need to be examined by a neurologist or other specialists.


==='''Costs'''===
==='''Costs'''===
Line 603: Line 602:
''All of these ethical concerns need to be taken into account when producing and testing this product. We are confident that a solution can be found that is at least satisfactory for everyone involved, if discussion is not avoided and proper testing is being conducted.''
''All of these ethical concerns need to be taken into account when producing and testing this product. We are confident that a solution can be found that is at least satisfactory for everyone involved, if discussion is not avoided and proper testing is being conducted.''


=Planning=
 
=References=
 
Belda-Lois, J. M., Vivas, M. J., Castillo, A., Peydro, F., Garrido, J. D., Sanchez-Lacuesta, J., … Prat, J. (2004). Functional assessment of tremor in the upper limb. INTERNATIONAL JOURNAL OF REHABILITATION RESEARCH, 27, 62–63. LIPPINCOTT WILLIAMS & WILKINS 530 WALNUT ST, PHILADELPHIA, PA 19106-3621 USA.
 
Bulboacă, A. E., Bolboacă, S. D., & Bulboacă, A. C. (2017). Ethical considerations in providing an upper limb exoskeleton device for stroke patients. Medical Hypotheses, 101, 61–64. https://doi.org/https://doi.org/10.1016/j.mehy.2017.02.016
 
Chu, C.-Y., & Patterson, R. M. (2018). Soft robotic devices for hand rehabilitation and assistance: a narrative review. Journal of NeuroEngineering and Rehabilitation, 15(1). https://doi.org/10.1186/s12984-018-0350-6
Darweesh, S. K. L., Raphael, K. G., Brundin, P., Matthews, H., Wyse, R. K., Chen, H., & Bloem, B. R. (2018). Parkinson matters. Journal of Parkinson’s Disease, 8(4), 495–498.
 
Dai, H., Lin, H., & Lueth, T. C. (2015). Quantitative assessment of parkinsonian bradykinesia based on an inertial measurement unit. BioMedical Engineering OnLine, 14(1). https://doi.org/10.1186/s12938-015-0067-8
 
Electronoobs. (2020, 03 07). http://www.electronoobs.com/. Opgehaald van electronoobs.com: http://www.electronoobs.com/eng_arduino_tut20_1.php
 
Foye, S. J., Kirschner, K. L., Brady Wagner, L. C., Stocking, C., & Siegler, M. (2002). Ethical Issues in Rehabilitation: A Qualitative Analysis of Dilemmas Identified by Occupational Therapists. Topics in Stroke Rehabilitation, 9(3), 89–101. https://doi.org/10.1310/7824-1ae0-gff0-kt55
 
Gallego, A. J., Rocon, E., Roa, J. O., Moreno, C. J., & Pons, J. L. (2010). Real-Time Estimation of Pathological Tremor Parameters from Gyroscope Data. Sensors , Vol. 10. https://doi.org/10.3390/s100302129
 
Grimaldi, G., & Manto, M. (2008). Tremor: from pathogenesis to treatment. Synthesis Lectures on Biomedical Engineering, 3(1), 1–212.
 
Irene Gort-Vos, personal communication, March 14, 2020
 
Koh, T. H., Cheng, N., Yap, H. K., & Yeow, C.-H. (2017). Design of a Soft Robotic Elbow Sleeve with Passive and Intent-Controlled Actuation. Frontiers in Neuroscience, 11. https://doi.org/10.3389/fnins.2017.00597
 
Marshall, K., & Hale, D. (2020). Parkinson Disease. Home Healthcare Now TA  - TT  -, 38(1), 48–49. https://doi.org/10.1097/NHH.0000000000000844 LK  - https://tue.on.worldcat.org/oclc/8492212894
 
National Tremor Foundation. (2020, 03 01). https://tremor.org.uk/orthostatic-tremor.html. Opgehaald van https://tremor.org.uk: https://tremor.org.uk/orthostatic-tremor.html
 
Nederlandse Huisartsen Genootschap. (2020, 03 02). https://www.nhg.org/standaarden/volledig/nhg-standaard-ziekte-van-parkinson? Opgehaald van https://www.nhg.org/: https://www.nhg.org/standaarden/volledig/nhg-standaard-ziekte-van-parkinson?tmp-no-mobile=1
 
Ozair, F. F., Jamshed, N., Sharma, A., & Aggarwal, P. (2015). Ethical issues in electronic health records: A general overview. Perspectives in Clinical Research, 6(2), 73–76. https://doi.org/10.4103/2229-3485.153997
 
Parkinson's News today. (2020, 03 06). https://parkinsonsnewstoday.com/. Opgehaald van Parkinson's News today: https://parkinsonsnewstoday.com/2018/01/18/18-tips-getting-dressed-easier-parkinsons-disease/
 
Robakis, D., & Louis, E. D. (2014). Another case of “shopping bag” tremor: a difficult to classify action tremor. Tremor and Other Hyperkinetic Movements (New York, N.Y.), 4, 269. https://doi.org/10.7916/D8PV6HVJ
 
Thenganatt, M. A., & Louis, E. D. (2012). Distinguishing essential tremor from Parkinson’s disease: bedside tests and laboratory evaluations. Expert Review of Neurotherapeutics, 12(6), 687–696. https://doi.org/10.1586/ern.12.49
 
Velandia, C. C., Tibaduiza, A. D., & Vejar, A. M. (2017). Proposal of Novel Model for a 2 DOF Exoskeleton for Lower-Limb Rehabilitation. Robotics , Vol. 6. https://doi.org/10.3390/robotics6030020
 
Yap, H. K., Lim, J. H., Nasrallah, F., & Yeow, C.-H. (2017). Design and Preliminary Feasibility Study of a Soft Robotic Glove for Hand Function Assistance in Stroke Survivors. Frontiers in Neuroscience, 11. https://doi.org/10.3389/fnins.2017.00547
 
Yap, H. Kai., Sebastian, Frederick., Wiedeman, Christopher., & Yeow, C.-H. (2017). Design and characterization of low-cost fabric-based flat pneumatic actuators for soft assistive glove application. 2017 International Conference on Rehabilitation Robotics (ICORR). https://doi.org/10.1109/icorr.2017.8009454\
 
=Appendix=
 
==Literature study week 1 & 2==
 
[https://docs.google.com/document/d/10J-_bgQLFVivruupC6p4-PWCnrY1nneBPrjuYC39hxc/edit?usp=sharing Literature study week 1 & 2]
 
==Deliverables==
*Wiki page
 
*Model
 
*A prototype band
 
*Presentation
 
==Presentation==
 
[https://youtu.be/GkGFtzbAKhU Presentation]
 
==Peer review==
{| border=1 style="border-collapse: collapse;" cellpadding = 5
! Name !! Grade
|-style="text-align: center;"
| Pim Gort || 0
|-style="text-align: center;"
| Chantal Vreezen || 0
|-style="text-align: center;"
| Jan van Leeuwen || 0
|-style="text-align: center;"
| Jorn Voet || -0.5
|-style="text-align: center;"
| Femke Ligtenberg || +0.5
|-style="text-align: center;"
|}
 
==Planning==
{| class="wikitable" | border="1" style="border-collapse:collapse"
{| class="wikitable" | border="1" style="border-collapse:collapse"
! style="font-weight:bold"; |  
! style="font-weight:bold"; |  
Line 679: Line 757:
* All  
* All  
|}
|}
==Time management==
Week 1 log:
{| border=1 style="border-collapse: collapse;" cellpadding = 5
! Name !! Student number !! Time spent !! Break-down
|-style="text-align: center;"
| Jan van Leeuwen || 1261401 ||  hours || 
|-style="text-align: center;"
| Jorn Voet || 1386794 || 9 hours|| Meeting (2 hrs), Literature research (6 hrs), Update wiki (1 hr)
|-style="text-align: center;"
| Pim Gort || 1253042 || 8 hours ||Meeting (2 hrs), Literature research (6 hrs)
|-style="text-align: center;"
| Femke Ligtenberg || 1237054  || 9 hours || Meeting (2 hrs), Literature research (7 hrs)
|-style="text-align: center;"
| C.C. Vreezen || 1011476 || 8 hours || Meeting (2hrs), Literature research (6 hrs),
|-style="text-align: center;"
|}
Week 2 log:
{| border=1 style="border-collapse: collapse;" cellpadding = 5
! Name !! Student number !! Time spent !! Break-down
|-style="text-align: center;"
| Jan van Leeuwen || 1261401 || 16 hours ||  Meeting (3 hrs), Literature research (7 hrs), Working on model ( 6 hrs)
|-style="text-align: center;"
| Jorn Voet || 1386794 || 14 hours|| Meeting (3 hrs), Literature research (6 hrs), Research diseases (4 hrs)
|-style="text-align: center;"
| Pim Gort || 1253042 ||17 hours || Meeting (3 hrs), Literature research (6 hrs), researching forces and tremors parkinson (6 hrs), Contact for an interview (2 hrs)
|-style="text-align: center;"
| Femke Ligtenberg || 1237054  || 19 hours || Writing introduction (3 hrs), literature research (8 hrs), researching subject of project and relevance (5 hrs), meeting (3 hrs)
|-style="text-align: center;"
| C.C. Vreezen || 1011476 || 13 hours || Meeting (2hrs), Writing introduction (4hrs), Contact medics( 1hrs). Literature research (6 hrs),
|-style="text-align: center;"
|}
Week 3 log:
{| border=1 style="border-collapse: collapse;" cellpadding = 5
! Name !! Student number !! Time spent !! Break-down
|-style="text-align: center;"
| Jan van Leeuwen || 1261401 || 14 hours || Literature research ( 9 hrs), working on planning ( 2 hrs), meeting x2 ( 3 hrs)
|-style="text-align: center;"
| Jorn Voet || 1386794 || 16 hours|| Literature research (9 hrs)
Meeting x2 (3 hrs)
Work on types of PD (4 hrs)
|-style="text-align: center;"
| Pim Gort || 1253042 || 18 hours || Literature research (8 hrs)
collected data parkinson (2 hrs)
mailing + calling (2 hrs)
meeting 2x (3 hrs)
|-style="text-align: center;"
| Femke Ligtenberg || 1237054  || 18 hours|| Literature research (8 hrs), worked on introduction (4 hrs), meeting x2 (4 hrs), working on records of meetings (2 hrs)
|-style="text-align: center;"
| C.C. Vreezen || 1011476 || 23 hours || Literature research (9 hrs),
Working on the introduction (3 hrs), Meeting x2 (3hrs), Mailing
State of the art (6 hrs), Adjusting introduction (2hrs)
|-style="text-align: center;"
|}
Week 4 log:
{| border=1 style="border-collapse: collapse;" cellpadding = 5
! Name !! Student number !! Time spent !! Break-down
|-style="text-align: center;"
| Jan van Leeuwen || 1261401 || 14 hours || Thinking about model, finding literature (6 hrs), meeting (2 hrs)
|-style="text-align: center;"
| Jorn Voet || 1386794 || 19 hours|| Literature research (8 hrs)
User analysis (6 hrs)
Meeting x2 (4 hrs), Updating wiki (1 hr)
|-style="text-align: center;"
| Pim Gort || 1253042 || 20 hours || interview ( 2 hrs), model orientation (8 hrs), meeting 2x(4 hrs), Literature research on exercises Parkinson patients (6 hrs)   
|-style="text-align: center;"
| Femke Ligtenberg || 1237054  || 22 hours|| Literature research (8 hrs), working on the marketing of our product (3 hrs), meeting x2 (4 hrs), working on pitch (2 hrs), working on wiki page (5 hrs)
|-style="text-align: center;"
| C.C. Vreezen || 1011476 || 17 hours || Litarature research (8 hrs), Writing state of the art (4 hrs), Contacting for interviews(1 hr), meeting (2 hrs), Intervieuw questionaire (2hrs)
|-style="text-align: center;"
|}
Week 5 log:
{| border=1 style="border-collapse: collapse;" cellpadding = 5
! Name !! Student number !! Time spent !! Break-down
|-style="text-align: center;"
| Jan van Leeuwen || 1261401 || 17 hours ||  Meeting ( 3 hrs), compile parts of Arduino ( 8 hrs), Work on Arduino code ( 6 hrs)
|-style="text-align: center;"
| Jorn Voet || 1386794 || 19 hours|| Rewriting state of the art ( 4 hrs), working out tremor-related diseases (8 hrs),  Meeting (3 hrs), Updating users ( 4 hrs)
|-style="text-align: center;"
| Pim Gort || 1253042 || 17  hours || Meeting (3 hrs), compile parts of Arduino (8 hrs), Work on Arduino code (6 hrs)
|-style="text-align: center;"
| Femke Ligtenberg || 1237054  || 17 hours || Writing instruction manual based on literary research (6 hrs), writing progress of project (2 hrs), reading and checking wiki page (5 hrs), meeting (3 hrs), working on records of meeting (1 hrs)
|-style="text-align: center;"
| C.C. Vreezen || 1011476 || 20 hours || Rewrting state of the art (6hrs), Benefits of product (2hrs), Adjustment to introduction & contact with doctor (6hrs), Update wiki page (3hrs), meeting(1hrs),writing beyond state of art (2hrs)
|-style="text-align: center;"
|}
Week 6 log:
{| border=1 style="border-collapse: collapse;" cellpadding = 5
! Name !! Student number !! Time spent !! Break-down
|-style="text-align: center;"
| Jan van Leeuwen || 1261401 || 18 hours ||  Meeting ( 3 hrs), Working on fourier transform ( 8 hrs), Measurements with Arduino (7 hrs)
|-style="text-align: center;"
| Jorn Voet || 1386794 || 12 hours|| Meeting (3 hrs), Updating users (2 hrs), Searching additional items for prototype ( 1 hr), Working out concessions ( 6 hrs)
|-style="text-align: center;"
| Pim Gort || 1253042 || 18  hours || Meeting (3 hrs), costs estimation product (3 hrs), worked on requirements and users (4 hrs), Testing with Arduino (8 hrs)
|-style="text-align: center;"
| Femke Ligtenberg || 1237054  || 16 hours || Meeting (3 hrs), working on problem statement (5 hrs), literature research (6 hrs), working on validation of the product (2 hrs)
|-style="text-align: center;"
| C.C. Vreezen || 1011476 || 16 hours || Meeting 2x (3 hrs), Working on the approach (4 hrs), Formatting the wikipage on literature study (1hrs), Interview writing in english (4hrs), Convert interview into wiki page (4hrs)
|-style="text-align: center;"
|}
Week 7 log:
{| border=1 style="border-collapse: collapse;" cellpadding = 5
! Name !! Student number !! Time spent !! Break-down
|-style="text-align: center;"
| Jan van Leeuwen || 1261401 || 15 hours ||  Meeting ( 4 hrs), working on Fourier ( 7 hrs), working wiki (4 hrs)
|-style="text-align: center;"
| Jorn Voet || 1386794 ||  hours|| Meeting (4 hrs), Writing app interface ( 5 hrs)
|-style="text-align: center;"
| Pim Gort || 1253042 || 16 hours || Meeting 2x (4 hrs), mock-up design (8 hrs), Perform measurements with Arduino (4 hrs)
|-style="text-align: center;"
| Femke Ligtenberg || 1237054  || 19 hours || Meeting x2 (4 hrs), writing text for presentation (4 hrs), organizing wiki page (3 hrs), working on risk analysis (1 hrs), writing mock-up text (1 hrs), critically reading and rewriting parts of wiki page (6 hrs)
|-style="text-align: center;"
| C.C. Vreezen || 1011476 || 15 hours || Meeting 2x (4 hrs), Writing on the expected impacts (1hrs), Writing down for ideas of risks analysis and updating wiki on treatments (1hrs), Rewrtining State of the Art (3hrs), Rewriting Diagnosis (1hrs) , Writing Appendix (2hrs), Critically reading wiki page (3hrs).
|-style="text-align: center;"
|}
Week 8 log:
{| border=1 style="border-collapse: collapse;" cellpadding = 5
! Name !! Student number !! Time spent !! Break-down
|-style="text-align: center;"
| Jan van Leeuwen || 1261401 ||  hours || 
|-style="text-align: center;"
| Jorn Voet || 1386794 ||  hours||
|-style="text-align: center;"
| Pim Gort || 1253042 ||  hours ||
|-style="text-align: center;"
| Femke Ligtenberg || 1237054  || hours||
|-style="text-align: center;"
| C.C. Vreezen || 1011476 || 7 hours || Meeting 2x (4hours), Writing presentation (3hours), Reading wikipage (2hours)
|-style="text-align: center;"
|}
=References=
Belda-Lois, J. M., Vivas, M. J., Castillo, A., Peydro, F., Garrido, J. D., Sanchez-Lacuesta, J., … Prat, J. (2004). Functional assessment of tremor in the upper limb. INTERNATIONAL JOURNAL OF REHABILITATION RESEARCH, 27, 62–63. LIPPINCOTT WILLIAMS & WILKINS 530 WALNUT ST, PHILADELPHIA, PA 19106-3621 USA.
Bulboacă, A. E., Bolboacă, S. D., & Bulboacă, A. C. (2017). Ethical considerations in providing an upper limb exoskeleton device for stroke patients. Medical Hypotheses, 101, 61–64. https://doi.org/https://doi.org/10.1016/j.mehy.2017.02.016
Chu, C.-Y., & Patterson, R. M. (2018). Soft robotic devices for hand rehabilitation and assistance: a narrative review. Journal of NeuroEngineering and Rehabilitation, 15(1). https://doi.org/10.1186/s12984-018-0350-6
Darweesh, S. K. L., Raphael, K. G., Brundin, P., Matthews, H., Wyse, R. K., Chen, H., & Bloem, B. R. (2018). Parkinson matters. Journal of Parkinson’s Disease, 8(4), 495–498.
Dai, H., Lin, H., & Lueth, T. C. (2015). Quantitative assessment of parkinsonian bradykinesia based on an inertial measurement unit. BioMedical Engineering OnLine, 14(1). https://doi.org/10.1186/s12938-015-0067-8
Electronoobs. (2020, 03 07). http://www.electronoobs.com/. Opgehaald van electronoobs.com: http://www.electronoobs.com/eng_arduino_tut20_1.php
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=Appendix=
==Literature study week 1 & 2==
[https://docs.google.com/document/d/10J-_bgQLFVivruupC6p4-PWCnrY1nneBPrjuYC39hxc/edit?usp=sharing Literature study week 1 & 2]

Latest revision as of 18:58, 16 May 2020


Band that aids general practitioner in distinguishing between different tremor related diseases

Group 1

Group members Student number Study Email
C.C. Vreezen 1011476 Medical sciences and technology c.c.vreezen@student.tue.nl
J. Voet 1386794 Psychology and Technology j.voet@student.tue.nl
F.W.H.M. Ligtenberg 1237054 Biomedical engineering f.w.h.m.ligtenberg@student.tue.nl
J.A. van Leeuwen 1261401 Applied Physics j.a.v.leeuwen@student.tue.nl
P. Gort 1253042 Applied Physics p.gort@student.tue.nl

Introduction

There are many neurodegenerative disorders that have one main occurring symptom in common, tremors. A tremor is an involuntary, rhythmic, muscle contraction and relaxation involving oscillations or twitching movements of one or more body parts. It is the most common of all involuntary movements and can affect the hands, arms, eyes, face, head, vocal folds, trunk, and legs. These tremors most of the time have an unknown cause, like in for example Parkinson’s disease, paraneoplastic syndrome, extrapyramidal syndrome and Idiopathic parkinson. It is very difficult to determine which disorder is related to which type of tremor. A recent report of the Public Health England shows trends in death numbers of neurological diseases in England between 2001-2014. Mortality associated with Parkinson’s disease and other similar neurodegenerative disorders has increased substantially between 2001-2014. (Darweesh et al., 2018) Since neurodegenerative diseases significantly decrease the quality of life and the incidence is high and still rising, helping these patients becomes of increasing importance for our society.

These neurodegenerative disorders cause tremors with different stages and different rates that affects a patient in their everyday life. Tremors can be caused by different malfunction in the neurons in the part of the brains. This causes difficulties in controlling movements. Tremors worsen because of stress or anxiety and can also cause Bradykinesia; slowed movements, which can cause feelings of tiredness and weakness. This causes a shuffling way of walking and falling since they cannot adjust their footing quickly enough. Moreover, this causes difficulty when buttoning clothes, brushing their teeth or typing something. They can suffer from decreased movement and range of motion due to muscle stiffness, which causes discomfort. Determining the disease is of high importance, since the health risks of each disorder differs. Also a lot of these disorders have serious tremors that contribute to difficulties in maintaining everyday life activities.

Problem statement

The user problem we want to solve is that it is very difficult for doctors to distinguish between tremor diseases, especially in their beginning stages. Since determining a correct diagnosis is a lengthy process, patients with an undiagnosed tremor diseases need to be in and out of the hospital often and undergo all kinds of testing. Some medical examinations like MRIs also can really add up in price. With a quicker and more accurate diagnosis, patients can spare their energy, fuel used for travelling to and from the hospital, their time and their money. On top of that, a wrong diagnosis could lead to the doctors prescribing wrong or temporary, only slightly effective medicine to the patients. This leads to frustration on the side of the patient and could even lead to undesired health consequences from either medicine side effects or from not treating the correct illness and thus decreasing the health of the patient.

When a correct diagnosis cannot be determined, patients will frequently come back to their family medicine doctor to get referred to other specialists in order to find the correct diagnosis. This leads to the doctor having less time to spend on other patients. Moreover, the doctor gets frustrated since he cannot give the patient the correct diagnosis, which might lead to official complaints against his practice.

Our solution

The product we developed to aid this problem is a band. The band gives a broader insight in determining a tremor disease. With our band, family medicine doctors can help these patients more efficiently, with the tests just taking a couple of minutes of the doctors' and patients' time. The doctor can then take a day to evaluate the data of the tremor frequency and amplitude to make sure the diagnosis agrees with the data. This also leads to less frustration on the side of the doctor and more free time to see other patients.

As can be read under the headers "Interview" and "Validation of the product", a basic physician was interviewed to make sure the product was needed and useful. The concerns she expressed were taken into account, and overall she was enthusiastic and thought our idea was useful for basic physicians and tremor patients alike.

Progress of Project

This project started with developing a soft skeleton to help the physically disabled. Feedback on this was that this subject was too broad for the scope of this class, and not focused on a relevant user problem. The focus then shifted from doing literature research on exoskeletons to finding an important and interesting user problem that we can try to find a solution for. Soft exoskeletons can be used for extra stabilization and support, which is how we thought about Parkinson’s disease.

The most well-known symptom of Parkinson’s disease is tremors, mostly of the arms, which proves to be the most bothersome when performing daily tasks. (National Tremor Foundation, 2020) However, for this only the arms need to be stabilized, so we realized an exoskeleton was not necessary for our demographic. Then we thought about creating a band which would counteract tremors, thus reducing them. However this seemed too difficult to do in this course. Through further literature study on Parkinson’s disease, it was discovered that diseases with tremors as a symptom are very difficult to distinguish from each other. (Thenganatt & Louis, 2012) To diagnose such a patient correctly takes multiple trips to the hospital, MRI scans and other tests. (Nederlandse Huisartsen Genootschap, 2020) Tremor diseases are found to be distinguishable from each other by the amplitude and frequency, and this can be used to diagnose these diseases correctly. This diagnosis can be made faster and more efficient by our band.

Approach

From the beginning of the project, a literature study was performed to investigate the current state of the art of diagnosing tremor diseases and devices to do so. From the literature study, a problem statement has been derived so a solution for this problem can be found and developed. For solving the problem statement, objectives have been determined to set guidelines for the realization of a band.

Further, literature study was done to learn about different user perspectives and different tremor-related diseases. Also, the literature study was needed to figure out the optimal design of the product and the ethical considerations it gives when this product is put on the market. Furthermore, when designing the product, different factors need to be taken into account. Firstly, the user problems need to be taken into account. Secondly, a working prototype has to be made. Lastly, the impact of our product needs to be determined.

To finalize the project, interviews with a general practitioner were scheduled to derive some different perspectives for human factors that will influence the design of the band. This interview should enlight the project about user perspectives and some concerns that come with the usage of the band. This interview is a great way of getting a user perspective, since it was not possible to get the user perspective directly from a tremor patient. Besides, the interviews would give more insight into user perspective and into the functionality and specific needs for the design. Also, the general practitioner has more practical information in the medical practice regarding determining a diagnosis for tremor diseases and the exercises that are useful for this. This will give more information for possible revisions in for example the manual, the design and app used with the band or to change existing exercises and finetune the product before realizing it. Finally, for obtaining one of the most important human factor answers, the general practitioner is asked if the product is useful and relevant. This is a very important note for realizing the band into a successful project.

State of art

Today, many types of tremors are known, but there is still a lot more that needs to be investigated about these tremors. There are a lot of causes of tremors: neurological disorders, neurodegenerative disorders and disorderly conditions that include damage to the brain (e.g. stroke). Other causes are drugs, alcohol, smoking, overactive thyroid or liver failure, lack of sleep, lack of vitamins, increased stress or a cold. Moreover, magnesium and thiamine deficiency can cause tremors. (Chen et al, 2017 & Marshall et al, 1956). Unless there is an underlying issue that causes the tremors, for example, cancer or drug-related tremors, there aren’t any specific medical tests to diagnose the disease that causes these tremors. The most prominent examples of this are Parkinson’s disease (PD) and Essential Tremor (ET). A neurologist diagnoses a patient with tremors by performing an anamnesis which is a patient's account of their medical history. Besides the neurologist diagnoses a patient by looking at clinical characteristics and neurological examination. (Federation of Medical specialists, 2020) In case of suspicion of a certain disease, there are tests that can help support this suspicion. For example, in the case of PD, a dopamine transporter scan can be made. This process to get to a diagnosis is done by ruling out other diseases. In order to try and distinguish between tremor diseases, specific frequencies for some disease tremors have been determined. These frequencies can then be related to certain tremor types and therefore also certain diseases. However, since this field is in development, further investigation is still needed for testing different frequencies.

A tremor frequency can vary over time in some diseases. (Hellwig et al, 2009) In Parkinson’s disease and Essential tremor the instantaneous tremor frequency can change by fractions of 1 Hz over a period of seconds, either spontaneously or during voluntary paced contraction of another limb. In psychogenic tremors, tremors in all involved limbs appear to have a common oscillator. By revealing frequency dissociation among physically contracting muscle groups, a feature difficult to detect in clinical examination, multi-limbed recording in both spontaneous and paced conditions help in distinguishing psychogenic tremor from non-psychogenic tremors. (O’Suilleabhain, 1998).

So far there are a few techniques on the market which can measure the kinematic movement of a tremulous activity, but these stay within boundaries. With a tremor stability index, for example, Parkinson’s disease tremor can be discriminated from essential tremor with high diagnostic accuracy. (Di Biase et al., 2017) The tremor stability index is derived from kinematic measurements of tremulous activity. This sensor consists of an accelerometer to measure the linear acceleration caused by the vibrations and a gyroscope which determines the angular position. The data of these two components is used to continuously measure the position of the limb and can be mapped out to create a frequency and amplitude spectrum of the tremors of a patient.

Furthermore, there are already studies that are testing for specific diseases using the same technique as the last mentioned study is proposing. For example, a wearable bradykinesia assessment system with an inertial measurement unit was used, based on hand gripping actions and calculations of hand grasping ranges of Parkinson at which bradykinesia was occurring. (Dai et al,. 2015) Results there already showed that the system had a greater correlation with the evaluation by neurologists than other Parkinson bradykinesia assessment systems. Moreover, a two-stage algorithm was made for real-time estimation of instantaneous tremor parameters from gyroscope recordings. (Galego et al., 2010) The proposed algorithm extracted tremor patterns from raw angular data and estimated the instantaneous amplitude and frequency. They proposed real-time tremor parameters to be employed for driving a “soft robot” for tremor suppression based on Functional Electrical Stimulation.

However, there is not yet a product on the market that can measure the differences between multiple tremors for diagnosticating of a tremor disease, instead of just distinguishing between two tremors. As said before, more research into frequencies and amplitudes of each of the tremor types is needed for fine-tuning an algorithm of such a product. This product should reduce health care costs, prevent wrong diagnoses, ensure faster diagnosis and limit the number of hospital visits. It would be a helpful tool for medical practitioners, as well as for the patients. Therefore, this band could be a very promising new product on the market.


Diagnosis

Protocol of diagnosing tremor disease

When a patient is indicating complaints about tremors, a medical practitioner will diagnose the kind of tremor disease mainly by anamnesis and observations, followed by measurements with sensors taking place in the hospital. To provide more insight into how such a diagnosis works, below the step by step process of diagnosing Parkinson's disease by a medical practitioner is described.

Diagnosing Parkinson's disease
Figure 2: Animated diagnosis of Parkinson's Disease. Source: You and Parkinson's. (2020, 03 27). You and Parkinson's, an Animated Patient's Guide to Parkinson's Disease. Opgehaald van http://youandparkinsons.com/: http://youandparkinsons.com/en-pk/view/m201-s02-diagnosis-of-parkinsons-disease-slide-show

Parkinson's disease is diagnosed by observations of the occurrences of four main symptoms, following the anamnesis protocol:

1. Is there a rest tremor occurring?

2. What is the rigidity?

3. Which kind of kinesia: Akinesia, hypokinesia, bradykinesia?

4. Are there interrupted posture and posture reflexes occurring?


For Parkinson's disease, a clinical diagnosis is needed for a typical presentation no additional research is further needed. Some more supportive characteristics of Parkinson’s disease, to help indicate the diagnosis by further observation of the disease, are:

• Is there asymmetry?

• Is there a typical ‘count tremor’?

• Is there a good response to dopamine medication?

• Is there a slowly progressive course?

In short, mainly by anamnesis and observations, a medical practitioner will identify which tremor disease is involved. Further explorations, (e.g. monitoring the tremor frequency) will cost more time, more hospital visits and more visits to the local general practitioners.

Users

Types of users

Primary users

The primary users are family medicine doctors. We want to make it easier for them with our device. Through our device they do not need medical tests to identify tremor-related diseases, these tests are mostly not available for family medicine doctors. It is not always clear what disease a patient may have when they are in the beginning stages. Now they have to work with symptom-based judgement, even though the main symptom that they are looking at is the same: Involuntary limb movements. Our device can distinguish between these different illnesses based on the tremors. The types of medication for tremor diseases differ from disease to disease. Our device will help to come to the right diagnosis right away. With the help of the band, the family medicine doctors have an additional measuring tool to help determine the right diagnosis.

The second primary users are the patients that suffer from an early stage tremor-related disease. As said previously, the band is useful in getting to the right diagnosis. This prevents cases of misdiagnosis which would result in taking the wrong medication. Taking the wrong medication can be very bad for someone’s general health and it can also cause tedious side effects. Furthermore, the band prevents having to go to a specialist. This can save a lot of money and time of the patient as well as the specialists, who can treat more patients when the band is in use.

Secondary users

Secondary users of the band are the companies that create the product. Eventually, if there is a high enough demand for the product, companies will be producing the band. New technologies such as the band may create good business opportunities for both well-established companies and for newer companies.

Another type of secondary users are insurance companies. The purchase of the product will most likely end up being for insurance companies. Hospitals get financed by health insurers. The main option to make it more attractive for the health insurers to finance the product for the hospitals is to be as cheap as possible. So for them, it needs to be of low cost.

Tertiary users

The tertiary users are the neurologists. In case of suspicion with a disease caused by a neurological issue, the patient is normally sent to a neurologist. The goal of the band is that family doctors would already be able to accurately diagnose patients with tremors that result from neurological causes without the help of neurologists. This has positive and negative impacts on neurologists as in this case they would lose a portion of their patients, but they would also have more time to treat other patients that need it. This makes for shorter waiting lists or more time that can be spent on one patient.

Research on Tremor Related Diseases

General practitioners that seek a diagnosis for their patient with a tremor related disease, have to take into account the following tremor diseases:

Tremor related diseases

Essential tremor (ET)

ET is a progressive neurological disorder that usually starts between the 10th and 20th or 60th and 70th year of life. ET causes an involuntary rhythmic pure action tremor, and as such no tremors are experienced while in rest. ET can affect the whole body but it occurs most often in the hands. Due to the lack of medical tests for this disease, the diagnosis is at first based on the symptoms. When one has the symptoms of ET, the medical history and family history of the patient is reviewed. ET is autosomal dominant, which means that a child of a patient with ET has a 50% chance to inherit it.

Essential tremor signs and symptoms:

• Begin gradually, usually more prominently on one side of the body

• Worsen with movement

• Usually occur in the hands first, affecting both hands

• Can include a "yes-yes" or "no-no" motion of the head

• May be aggravated by emotional stress, fatigue, caffeine or temperature extremes

A patient with ET can be prescribed multiple types of medication. Firstly, one of these medications are beta blockers, these are normally used for treating high blood pressure but also tend to reduce the tremors of patients. Secondly, anti-seizure medication is often a replacement for people who do not respond to beta blockers. Lastly, tranquilizers can be used which are anti-anxiety medications for patients whose ET is affected by their emotional state. These are addictive.

Parkinson’s disease (PD)

PD is a neurodegenerative disorder that is the second most prevalent in America today, only surpassed by Alzheimer disease. (Marshall & Hale, 2020) 500.000 people have been diagnosed with PD in the United States, but it is believed that this number would be nearing a million if we allowed for misdiagnosed or undiagnosed cases. It is considered a disease that comes with old age. Costs for treatment are high, around $14 billion, and there is no cure as of now.

PD is caused by a malfunction in the neurons in the part of the brain that produces dopamine. Because of this, it becomes harder to control movement. The cause for this degeneration is still unknown. The greatest risks for PD are old age, genetics or prolonged exposure to toxins such as pesticides. PD can come with both motor and nonmotor symptoms, however motor symptoms are most common. These symptoms can affect one side of the body and then later also affect the other side. Tremors most often occur at rest and subside when the patient performs purposeful movements. They worsen because of stress or anxiety. It can also cause Bradykinesia; slowed movements, which can cause feelings of tiredness and weakness. This causes a shuffling way of walking and falling since they cannot adjust their footing quickly enough. Other motor symptoms include: freezing, sudden stopping, slurred speech and stammering. An issue is that the symptoms do not always show up in the same order. Some patient may only perceive a slight tremor at first while others start with other symptoms such as hypokinesia without any form of a tremor.

The most commonly prescribed medication for PD is Levodopa. Levodopa is processed in the brain, which turns it into dopamine. As PD affects the dopamine production, this is the best medication to help control the symptoms slow movements and stiff body parts. Levodopa is often taken along with Carbidopa, as Carbidopa increases the effectiveness of Levodopa. This results in smaller doses of Levodopa, which reduces the negative side effects. Other types of medication are dopamine agonists. These mimic the effects of dopamine, while they are not as effective as dopamine. Furthermore, anticholinergics have often been used in the past. These block involuntary movements to some degree. However, it is not often used anymore due to its side effects. Amantadine is also used for PD. This increases the availability of dopamine. Lastly, both MAO B inhibitors and COMT inhibitors block the enzyme which is responsible for the breaking down of dopamine in the brain.

Different forms of Parkinsonism

PD is not the only form of Parkinsonism. These other diseases are all similar to PD and therefore difficult to diagnose. The issue here is that not all of these diseases react the same to the normal PD treatments.Generally, the other forms than PD have in common that: - The decline is faster - The life expectancy is shorter - Other neurological phenomena occur - React less to dopamine treatments

Progressive Supra-nuclear Palsy (PSP)

Mainly, people have problems with walking and will unexpectedly fall down. Later, vision issues will occur. Sight might get blurry and the movements of the eye become slower. This is most commonly the point where PSP is able to be diagnosed. Vertical Canine Pareses comes after this. If a patient is asked to move the eyes vertically, the patient will experience saccades, which are rapid eye movements to find a new fixation point. In a later stage, one may not be able to move the eyes vertically at all.

Multiple System Atrophy

This disease affects the body's autonomic involuntary actions. The first symptoms may be: males may get impotent, bladder issues and orthostatic hypotension, which is that the blood pressure lowers while standing up. Other symptoms may involve slurred speech and issues with swallowing.

Vasculair Parkinsonism

This is a form of Parkinsonism that is induced by cerebral infarction. The symptoms are mostly walking based. Patients have issues with their balance and generally walk very slowly in small steps. The symptoms are often barely noticeable in the upper body region and as such it is sometimes called lower-body Parkinsonism. The normal PD dopamine treatments are not very effective for this type of Parkinsonism

Essential tremor vs Parkinson’s disease

ET is occasionally confused with Parkinson’s disease but there are some key differences. ET only causes tremors and there are no other health issues, whereas PD may shorten a patients' lifespan as it causes issues within the brain. Moreover, the tremor affected parts of the body differ. ET involves the hand, head and the voice, while PD cannot be involved with the voice but can be involved with other body parts. Furthermore, ET is a pure action tremor whereas PD is more often a (pure) resting tremor. Lastly, there are differences with the timing of the tremors. ET tremors tend to be of a lower magnitude and with a higher frequency than PD tremors.

Dystonia

The cause of most cases of Dystonia are not currently known. However, in some cases it may be acquired due to brain damage or genetics. Dystonia can occur at any age but it typically starts at an early age. It is characterized by involuntary muscle contractions, causing slow repetitive movements and tremors. Dystonia may affect all parts of the body. There are currently no treatments that can prevent dystonia or slow its progress.

However, there are treatments that can lessen the symptoms. The most effective treatment is botulinum toxin. These injections are put in the affected muscles to prevent muscle contractions and also decreases muscle spasms. One injection can last for multiple months. Other drugs that are used as medication are anticholerinic agents. These block involuntary movements, however due to side effects aren’t used as often. Another type of drugs are GABAergic (gamma-Aminobutyric acid) agents. These drugs regulate the GABA neurotransmitter. Lastly, Dopaminergic agents can be used. These act on the dopamine system which helps the control of muscle movement.

Cerebellar tremor

This type of tremor is caused by damage to the cerebellum and its pathways, which may be the result of a stroke, a tumor, alcoholism, or a disease. It is characterized by slow tremors with a high amplitude.

The tremors always occur in the extremities such as the hands or legs. Cerebellar tremors are currently not effectively treated with the use of medications.

Psychogenic tremor

These tremors are caused by some sort of psychiatric disorder such as PTSD (post traumatic stress disorder). Its tremors can be all types of tremors but are characterized by a few things: Its onset is always very sudden and may affect any part of the body. It is also affected by stress levels.

(Enhanced) Physiologic tremor

Any human has a small tremor in their hands and fingers. This is a physiologic tremor. Physiologic tremor is not related to a disease but rather a human phenomenon. This tremor can be temporarily enhanced however due to drugs, drug withdrawal and some medical conditions.

Table 2: All tremor diseases with their respective causes, effects and frequency
Tremor types Cause Effect Frequency
Cerebellar tremor Damage to cerebellum, chronic alcoholism, overdose on medication. A slow, broad tremor of the extremities that occurs at the end of a purposeful movement <5 Hz
Dystonic tremor Dystonia Sustained involuntary muscle contractions cause twisting and repetitive motions or painful and abnormal postures or positions 7 Hz
Essential tremor/benign essential tremor Neurodegenerative disorder Although the tremor may be mild and nonprogressive in some people, in others, the tremor is slowly progressive, starting on one side of the body but affecting both sides within 3 years. 4-8 Hz (Severity differs on age, emotion stress, fever, physical exhaustion)
Orthostatic tremor Neurodegenerative disorder Rhythmic muscle contractions that occur in the legs and trunk immediately after standing. Cramps are felt in the thighs and legs and the patient may shake uncontrollably when asked to stand in one spot. >12 Hz
Parkinsonian tremor Damage to structures within the brain that control movement. resting tremor: hands, may also affect the chin, lips, legs, and trunk, can be markedly increased by stress or emotion. The movement starts in one limb or on one side of the body and usually progresses to include the other side. 4-6 Hz
Physiological tremor Strong emotion, physical exhaustion, hypoglycemia, hyperthyroidism, heavy metal poisoning, stimulants, alcohol withdrawal or fever. Rarely visible 0.1-10 Hz
Enhanced physiological tremor Reaction to certain drugs, alcohol withdrawal, or medical conditions including an overactive thyroid and hypoglycemia a strengthening of physiological tremor to more visible levels 10 Hz
Psychogenic tremor/hysterical tremor Conversion disorder or psychiatric disease. Characteristics of this tremor may vary but generally include sudden onset and remission, increased incidence with stress, change in tremor direction or body part affected, and greatly decreased or disappearing tremor activity when the patient is distracted. Unknown
Rubral tremor Conditions that affect the red nucleus in the midbrain, classically unusual strokes. coarse slow tremor which is present at rest, at posture and with intention. Unknown
Alcoholism Kill certain nerve cells Asterix Unknown
Peripheral neuropathy Nerves that supply the body's muscles are traumatized by injury, disease, abnormality in the central nervous system, or as the result of systemic illnesses. Affect the whole body or certain areas, such as the hands, and may be progressive. Resulting sensory loss may be seen as a tremor or ataxia (inability to coordinate voluntary muscle movement) of the affected limbs and problems with gait and balance. Unknown
Tobacco withdrawal Smoking - Unknown
Panic Stress - Unknown

Current treatments

The medical practitioner finds a suitable way to treat patients with Parkinson's disease mainly by diagnosing the symptoms from which the patients experience the most hindrance, the side effects and the stadium of the disease.

Drug treatment of Parkinson's disease

The cause of Parkinson's disease is the loss of neurons in the substantia nigra (where dopamine is produced), resulting in a decrease in dopaminergic compounds. All of Parkinson's disease treatments are symptomatic. Still, there has been no demonstration of the neuroprotective effect of the medication. With relatively mild symptoms, treatment is started with amantadine or an MAO-B inhibitor. If the tremor is prominent, an anticholinergic or propranolol is prescribed as medication. In case of clear functional nuisance (motor main symptoms), dopaminergic medication prescribed. That is almost always levodopa with a decarboxylase inhibitor. During the progression of the disease, the duration of action of the medication decreases and the response follows the pattern of the concentration in the blood. During peaks, that means just after ingestion, excess movements occur (dyskinesias) and at the end of the medication period when it has largely disappeared from the body, the hypokinesia complaints occur again. These response fluctuations are called “on-off periods”. As these periods are less imaginable and therefore less effective with the medication, brain surgery may be considered or a continuous form of administration of dopaminergic stimulation in the form of apomorphine subcutaneously (injections or infusion into the skin) or with levodopa via an intestinal pump infusion (in which it passes directly into the intestines continuously).

Table 3: Tremor symptoms in Parkinson's disease and their respective medications
Tremor symptoms Medication
Motoric main symptoms Activation of the Dopamine-2-receptor is most important. By Levodopa, a dopamineprecursor, in combination with a periphery decarboxylase inhibitor. Decarboxylase converts Levedopa into dopamine. The inhibitor causes that the conversion does not only happens in the body, but also in the brain. Dopamine itself does not go direclty through the brain-barrier, but Levodopa does.
Tremor Thrihexyfenidyl

Propranolol, a betablocker

Motoric response fluctuations COMT-inhibitor: entacapon

MAO-B-inhibitor: selegilini, rasagiline (by starting therapies) Amantadine (by starting therapies)

Psychose hallucinations Clozapine, an atypical antipshychotium
Cognitive disorders Ricastigmine
Depression Citalopram

Amitriptyline, an antidepresivum

Urinating problems Oxybutynine, inhibits bladder spasms.

Alternative treatments

Operations

Operations are done in patients who respond well to treatment, but who suffer from response fluctuations. Patients should generally be <70 years of age, demonstrate a good response to levodopa and do not have severe cognitive impairment or psychiatric symptoms. During the procedure, electrodes are placed at certain places, which there stimulate the areas electrically. The procedure does not affect the progression of the disease.

Physiotherapeutic

Physiotherapeutics can be given with specific treatments for freezing and posture exercises for reflexes. By this falling can be prevented.

Logopedics

Logopedics are used when swallowing disorders and drooling are occurring.

Ergo therapeutics

Ergo therapeutics are used for giving advises when living at home and freezing and falling.

Product

Figure 3: Desired design; A sleek, comfortable band to be worn around the wrist of one arm, with no exposed mechanisms or sharp corners. Source: Aliexpress. (2020, 03 27). Aliexpress, online retailer. Opgehaald van https://www.aliexpress.com/: https://www.aliexpress.com/i/32952823575.html

The product we developed to aid the user problem is a band. The band gives a broader insight in determining a tremor disease. A patient that experiences tremors in a beginning stadium can go to a general practitioner just like in a normal situation when one goes to the doctor when having complaints. A band that is easy to use can be recommended by a doctor to run tests for determining the disease of the tremor. The test should consist of about 3-10 minutes with exercises that are easy to execute and that can be done in the general practice under the supervision of a doctor or an assistant. Shortly after, calculated data from the band of the patient will be sent to the doctor's computer system. A doctor is guided by the data and the general observations from which he can withdraw a conclusion for a disease type. Following this, correct medication or further trials can be prescribed.

The working mechanism of the band consists of a gyroscope, an accelerometer, and an Arduino. The band uses a model to process the data of the tremors and converts it into a frequency and amplitude spectrum. The band gives a broader insight in determining a tremor disease. It will quickly improve the quality of life of the patients, since if a person experiences tremors in the beginning stadium they can go to a general practitioner just like you would with any other non-lifethreatening ailments. This takes away the need to go see several specialists, e.g. a neurologist. The test consist of a couple of minutes of exercises that are easy to execute and that can be done in the general practice room under the supervision of a doctor or an assistant. While the exercises are executed by the patient, the data is processed and sent to the doctor's computer system. A doctor is guided by the data and the general observations from which he can subsequently draw a conclusion for a disease type. This way the diagnosis is less time consuming for the patient and doctor. Following this, correct medication or further trials can be prescribed. The band will be made as reliable as possible to reduce the risk of wrong diagnosis by extensive testing and constant improvement upon the design in the future.

Pro's and Cons

Pro’s:

  • Band is easy to use.
  • Band comes with an instruction manual, which explains feasible and short exercises.
  • Band can be used in general practice.
  • Band gives the doctor helpful insights in determining a tremor disease.
  • Band gives the doctor calculated data live.
  • The doctor can determine disease fast.
  • The doctor can prescribe correct medication or other further steps.

Cons:

With the use of a good manual, proper handling of the product and continuous product testing and improvement, the cons of the product can easily be prevented.

  • The band does not give a diagnosis.
    • This is done to avoid ethical complications of who would be held responsible for a wrong diagnosis.
  • Might bring the risk of incorrect diagnosis if data is processed incorrectly.
    • We plan on testing before and during the time that our product hits the market, along with a clear and complete manual, we hope to avoid this possibility as much as possible.

Requirements

Requirements for family doctors

  • Accurately measure the frequency of the tremors
  • Accurately measure the amplitude of the tremors
  • Use sensor data to compute a model
  • Send data wirelessly to the computer or phone of the doctor via an app
  • Needs to come with a good manual

Requirements for patients

  • Easy to equip
  • Comfortable (e.g. by size, weight and feeling)
  • Make the process of diagnosis faster
  • Make the process of diagnosis easier

Requirements for producers

  • Cheap to produce
  • Does not have to be so durable that it lasts for decades, since replacements mean more profit

Requirements for insurance companies

  • Cheap
  • Using it needs to be of low risk
  • Long lifetime

Objectives

  • Support and help general practitioners in diagnosing the disease of a patient correctly without the help of specialists.
  • Make the diagnosis of tremor diseases quicker, easier and more comfortable.
  • The band is user-friendly to the patient and the general practitioner.
  • The band is easy to use for every age, especially focused on the target audience of elderly tremor disease patients.

Interview

The full interview translated into English can be found here: Interview

Irene Gort-Vos, a basis physician at the Albert Schweitzer hospital in Dordrecht was interviewed to get more insight into the users as well as the necessity and usefulness of our product. The conducted interview gave great insight into the real medical world. It gave not only broader information into the subject, but also showed what a subject matter expert thought of our product. The interviewee is a physician, someone with experience on the subject and therefore a reliable source for this research. The interview that has been conducted, consisted of four main questions:

  • How complex is it to diagnose a tremor-related disease in the early stages? Is it hard to distinguish between tremor-related diseases?
  • Which factors does a doctor use to conclude a treatment for a patient with Parkinson’s Disease?
  • Is it useful to doctors to gain data about the amplitude and frequency of the tremors of patients with Parkinson’s Disease?
  • Do you think that Parkinson patients are willing to wear a glove or sleeve (About 1 day a week) for medical purposes.


The first question was answered by the interviewee very broadly, giving insight and information about many different diseases and their distinctive factors as well as listing the aspects one should look at when distinguishing between tremor diseases. Then, the interviewee goes deeper into the main tremor diseases, ET and PD, and continues to give a very detailed analysis of these diseases. The second question is answered by giving the biological cause of Parkinson’s and stating different treatments based on the symptoms and the course of the disease, as well as giving a table with symptoms and their related treatments. Before moving on to the next question, a few alternative treatment options are shortly mentioned. The third question is answered positively and as such validates the usefulness of the band. In the last question the interviewee mentions that what the band will be able to do, is already possible in hospitals using sensors, and therefore the interviewee questions the added value of the product. Lastly, the interviewee mentions that in the early phase of Parkinson’s, patients tend to be very cooperative and motivated, implying that they would not mind using the band, if it helped them get a fast and correct diagnosis.

Since conducting the experiment, slight changes and revisions have been made to the product. These changes have solved the doubts of the interviewee in the last question. The revisions include a band which is smaller than a glove and the time that a patient is supposed to wear it has been reduced to a minimal amount of about three minutes. The main doubts that the interviewee had were regarding two factors:

  • The restriction that the product would give a patient.
    • At the time of the interview, it was thought that the band should be worn for one whole day a week to gather enough data. Wearing a glove or sleeve for 1 day a week could indeed be very restricting. However, it has become clear now that the testing only has to be done once and can be done within a couple of minutes. Thus, now having to wear a small band once for a couple of minutes is not at all restricting anymore, which solves this first concern.
Figure 4: How tremors are measured now in hospitals. This seems intimidating and uncomfortable. Source: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0004-282X2014000400301
  • The added value of the product.
    • The interviewee was not sure about the added value as hospitals were able to do the same thing for an (assumed by the interviewee) cheaper price. However, the added value is that it saves multiple hospital visits and a lot of time in general. Furthermore, the estimated price of the product is relatively cheap. It should have been made more clear in the interview that we not only want to save the money of the patient or doctors, but also things like time, frustration etcetera. Our product also makes the testing process more comfortable, since testing is now done in a more comfortable, more familiar and trusted environment instead of a hospital room. This is the value we wanted to add to our product.


As shortly mentioned before, the questions can be divided into two types. The first two questions give more background information about the different tremor-related diseases and their treatments. The information from the answers to these questions have been used and integrated into the research part of the paper. The last two questions provided the paper with proof and validation of the usefulness of the product.

Design

Figure 5a: Simulation of prototype with whole mechanism exposed
Figure 5b: Prototype placed on the patient
Figure 5c: Final aesthetic view of the product

As can be seen in figure 5, three different mock-ups show the functional view of the mechanism on the band (figure 5a), the aesthetic view of the product placed on the patient (figure 5b) and the aesthetic view of the product, which is how the product will be brought on the market with the the shock-absorbing material (figure 5c). The final product looks like a normal, comfortable band.

Band

If a patient experiences tremor symptoms, they pay a visit to the family medicine doctor. Their doctor can then prescribe them to wear this band according to the instruction manual. This band then collects data about the amplitude and frequency of the tremors of the patient, from which the doctor can determine a diagnosis.

In order for the band to be easily put on by tremor patients, the band needs to have as little fastenings, zippers or buttons as possible. (Parkinson's News today, 2020) Patients can use force, however they just cannot complete actions that require detailed movement. Preferred is loose fitting clothing for easy removal. However, our band needs to stay in place, so making the band very loose would cause a hazard in case the band falls off of their arm. An elastic band that is not uncomfortably tight would be the best fit, since this band will stay in place, while the patients are able to put on or remove the band themselves without help. The desired elasticity can be compared to that of a sweatband. To cover the fragile hardware (Arduino etc.) that will be put inside the band it is important to add soft, shock absorbing material to cover these parts. These soft materials can also function in making the device more comfortable to use. Eventually all of the hardware needs to be safely concealed for the eye of the user to make the device more approachable. The size of the band needs to be 10cm making it possible that all materials can fit in, mostly concerning that the biggest piece of hardware, the Arduino, is 7.5 cm.

Instruction manual

This instruction manual will be given to the general practitioner in the form of a small booklet. He/she will then instruct the patient where to put on the band and how to perform the tests properly within his/her practice. The doctor should always be present when the band is used, and the band should only be used on the target audience of this product, namely elderly patients with a tremor related disease to avoid unnecessary risks.

For the most accurate test results of time varying tremor parameters, the band should be worn on the forearm, close to the wrist on one arm. This is because: (Gallego, Rocon, Roa, Moreno, & Pons, 2010)

  • Tremors are more prominent at joint farther away from the torso
  • Wrist tremors are the largest contributors to disability
  • Together with tremors of the finger, wrist tremors are studied the most in clinical literature


Four tests need to be performed, that are all relevant from a usability or clinical analysis standpoint. (Gallego, Rocon, Roa, Moreno, & Pons, 2010) The first three tests are also employed by neurologists to activate and analyze different types of tremors, the fourth test tests the ability of a patient to perform daily life activities. (Grimaldi & Manto, 2008)(Belda-Lois et al., 2004) All tests are done in 30 seconds or under, but can be extended to one minute, if within the patients abilities, to acquire more data. Even though test time is short, enough data is acquired within these 30 seconds. Tests can also be repeated if more data is desired.

Attention: The band needs to calibrate for 10 seconds before every use in order to receive accurate data. Let the patient assume the rest position for 10 to 15 seconds before performing a test, and do this for every new task that is performed.

Patients remain seated during testing, both of their arms resting comfortably on their laps as a starting position. The tests include:

  • Outstretched arms: Stretch your arms out if front of you and hold them in the air with your fingers abducted (spread out) during 30 seconds.
    • This test typically activates postural tremors.
  • Finger to nose: Alternate between touching your nose and knee with your finger during 30 seconds, holding your finger on the nose or knee for a few seconds each.
    • This test typically activates kinetic tremors.
  • Rest: Stay in the starting position of sitting down, both arms resting on your lap comfortably during 30 seconds. Make sure your elbow is in about a 90° angle.
    • This test typically activates rest tremors.
  • Pouring water into glass: Pour 20 cl of water from a bottle into a glass. It is not of importance how you choose to hold the glass or the bottle.
    • This test is used as a functional and usability analysis.


If you still have questions regarding the use of this product, you can call +31612345678 (fake number, will be changed by the real phone number of costumer service of the manufacturers in the actual instruction manual) from 8 am to 6 pm every day of the week.

Model

For our product we used an Arduino Uno and the MPU6050 which contains a gyroscope and accelerometer. To make it function as intended we need to write a code for the Arduino. For our product we need to have as output the relative X,Y and Z positions. After some research online, code was written that fulfilled the requirements of the product. It now correctly puts out the relative X, Y and Z components. It appears however that the device needs about 10 seconds to calibrate its position. So this needs to be taken into account, we can only start measuring after those 10 seconds. The Arduino measures about 70 per second, meaning about 0.015 seconds between measurements. Therefore the data we acquire is really accurate. The data is presented to us in the serial monitor, to do further research on this data we copied it into excel and after that into Matlab. The following code is used to analyze. We put a fast Fourier transform over the data and it puts out a graph where the amount of acceleration is plotted against the frequency. We can then see which frequency is the dominant one. This code is an example for the Y direction. We need to also look at the X and Z direction. We then look at these different axis to determine which has the highest frequency and amplitude and we select this axis to determine what the dominant frequency and amplitude is.


    data1 = Y_vect(1:2000);
    data = detrend(data1);
    fs = 1/(1/100);
    m = length(data);
    nfft = 2^nextpow2(m);
    y = fft(data,nfft)/m;
    f = fs/2 * linspace(0,1,nfft/2+1);
    power = abs(y);
    plot(f,power(1:nfft/2+1)) 
    t = (0 : m-1)/fs;
    figure
    plot(t,data);

Unfortunately, the product was not able to be tested with actual tremors patients to see what the data would show in that case. This is why tremors were simulated to illustrate how the model works. After doing the plotting and testing with different tremors (the device was vibrated manually) the following things are found. In the measurement we did the Y values were most useful to look at as these gave a distinct dominant frequency. It appears that most of the movements are in the very low frequency range therefore most of the normal movements (no tremor) gave dominant frequency peaks around the 0-1 Hz range. When we however did a measurement with a constant higher frequency and plotted this we are able to see a dominant frequency namely at around 5 Hz. When looking at the signal plotted over time this does appear to be possible. The peaks were counted by the amount of peaks that are present in this plot within 3 seconds, these are 14 peaks. Meaning there are 14 oscillations in 3 seconds. When calculating this means there are about 4.667 oscillations per second, meaning 4.667 Hz. For figure 6c we did another measurement where we tried to get an even higher frequency and as can be seen in the figure this happened we found a dominant frequency around 7 Hz.

Figure 6a: Fourier transform over signal, figure shows dominant frequency at around 5 Hz (highest peak)
Figure 6b: Signal plotted over time
Figure 6c: Another Fourier transform over signal, this figure shows a dominant frequency around 7 Hz.


We also did a zero-measurement to see what the gyroscope and accelerometer would put out if there was no movement. To do this measurement we laid the device on a table without touching it. It does appear that we see some movement in the data, most likely due to an uncertainty in the gyroscope and accelerometer. In the figure below it can be seen that these peaks in the frequency spectrum show way lower powers, in the order of 1000x smaller. Meaning that this will have no significant impact on the tremor measurements.

Figure 7: Zero-measurement

App

Data of the band can be sent to an app on the phone of the doctor using an HC06 module. (Electronoobs, 2020) This allows for the sending of data via a Bluetooth connection between the HC06 module and the phone. The app shows a graph of the data, analyzed using a Fourier transform, from which the doctor can clearly read out the amplitude and frequency of the tremors of the patients.

The interface of the app is very simple and easy to use. The data of the band will automatically be sent from the band to the app, which then analyzes the data and computes it into a graph.

Basically the interface has two buttons. One for the graph and one for the statistics. One can switch between the two easily using these buttons.

The graph page shows two buttons at the top of the page with which you are able to switch between two graphs. The first graph is the data with on the x-axis the frequency in Hertz and on the y-axis the Power of the corresponding frequency.

Figure 7a: Dominant frequency measurement

The second graph shows on the x-axis the elapsed time in seconds and on the y-axis the displacement in millimeters. This is a visualization of how the tremor behaves over time.

Figure 7b: Displacement per second measurement

The statistics show a list of the important aspects of the graphs, such as: Elapsed time, the dominant frequency and the average displacement of the graphs.

Figure 7c: Statistics of the measurement

It is of utmost importance that the doctor takes into account the graphs as well as the statistics. The graphs can still give interesting information, like other peaks with a high power or the tremor pattern, which can also aid in determining a diagnosis. This is why the graphs are still shown, despite the fact that a doctor might be intimidated by them. The statistics aid the doctor in understanding the graphs better, to further lessen the intimidation factor of the graphs.

By using this app, the doctor can examine the data on his own time and call the patient back later in the day with the results. This saves a lot of back and forth to the hospital for the patient, where they need to be examined by a neurologist or other specialists.

Costs

Table 1: Costs of prototype
Material costs
Arduino Uno R3 compatible 7.00 euro
MPU-6050 5.00 euro
DuPont Jumper cable male-male 3.50 euro
Wrist band 4.75 euro
Soft material 0.25 euro
Printer cable 2.50 euro
Total 23 euro

Validation of the product

When interviewing a basic physician, the relevancy and necessity of our product has become clear.

Willingness to wear the band

The interviewee pointed out that Parkinson patients in the beginning stages of the disease are, in her experience, a well-motivated, cooperative patient group. She thus expects that Parkinson patients will be more than willing to wear our product, if this means it can help with diagnosis and treatment and the band itself is not restrictive. This is because patients in the beginning stages of Parkinson are still cognitively well off and still have a great life to live.

Relevancy and necessity of the band

While frequency and amplitude can be measured in the hospital using several sensors, a family medicine doctor cannot do this in their practice. Our product can aid the family doctor in diagnosing a patient by analyzing data of the frequency and amplitude of the tremors. This is a very useful tool for family medicine doctors. Data should be interpreted in context with the complaints the patient expresses or that which the doctor can see in the moment, like when the tremors occur and other specific characteristics of tremor diseases. This context can be found partly by the tests that are performed when implementing the band and partly by the questions a family medicine doctor always asks the patients as a routine during their appointments. Our product also makes the testing process more comfortable than in a hospital, since testing is now done in a more comfortable, familiar and trusted environment instead of a hospital room.

Marketing

Medical

It is challenging to distinguish between Parkinson’s disease and other diseases with tremor symptoms like essential tremor, both in the beginning and progressing stages of the diseases. (Thenganatt & Louis, 2012) Both essential tremor and Parkinson’s disease show tremor types like rest, postural, kinetic an intention tremors. Both diseases could even coexist in the same patient. Now, the diagnosis is determined by looking at things like tremor frequency and amplitude and associated neurological findings. Laboratory testing may also aid in differentiating these two diseases. Tests like this include: “accelerometry and surface electromyography, spiral analysis, dopamine transporter imaging, olfactory testing and, eventually, postmortem histopathology. These tests have limitations and their diagnostic utility requires additional study.” (Thenganatt & Louis, 2012) This difficulty with diagnosis shows the practicality of a model that could acquire data from which the doctor could determined the correct diagnosis, thus bypassing extensive clinical testing.

Frustration

PD patients get frustrated when they are dependent on partners or carers for performing daily tasks. (National Tremor Foundation, 2020) They often lack necessary confidence when these helpers are not there. Simple household tasks like cleaning and cooking are really difficult or even impossible. Carrying lightly weighted objects makes these tremors even worse. (Robakis & Louis, 2014) An early and correct diagnosis is thus very important to improve the quality of life of patients with tremor symptoms.

Expected impact

User perspective

  • To improve the precision of the diagnosis.
  • To improve the life of patients, by correct medical prescriptions.
  • To improve the duration of the patient's diagnosis trial.
  • To improve the workflow of the doctor.
  • To improve the life quality of patients.
  • To improve the relationship and trust patients have with their family medicine doctors.

Society perspective

  • To decrease medical costs for other medical trials for society.
  • To decrease the pressure on the healthcare system.

Entrepreneur perspective

  • To gain financially (e.g. entrepreneurs).

Risk analysis

  • Band does not get off of the arm of the patient.
    • To prevent this, an elastic band is used and the doctor can possibly assist with putting on or taking off the band, since the tests will be performed within the practice and thus the presence of the doctor.
  • Short circuit occurs, resulting in burns or other dangerous situations.
    • Exploding batteries or other causes of burns are in almost all cases caused by misconduct. Thus it should be clearly mentioned in the prescription how the product needs to be handled with care.
  • Band is not smooth or has pointy edges, which can cause injuries.
    • The devices on the band will be covered with sponge-like material and soft, elastic fabric in order to prevent this.
  • Mechanism within the band breaks, causing the band to not be usable.
    • The working mechanism is tightly packed in spongey, shock-absorbing material as to avoid damage to the mechanism.
  • Data from the band is indiscriminately taken as fact without critically looking at the data.
    • While the strife of the product is to give accurate data 100% of the time, it is still advised that doctors look at the data with a critical eye. If the data seems inconsistent or unexpected, a doctor should follow their instincts and they should always look at the full context, like tremors the doctor can see or concerns the patient expresses.
  • Product is not used in rightful manner (e.g. physical exercises), resulting in a false diagnosis.
    • An instruction manual will be provided with the band. The doctors is advised to read this manual carefully before he intends to use the product. This manual clearly describes how to put on the band and what tests the patients should perform. If the doctors still has any questions regarding the use of the product after extensively reading the manual, they could test the band out on themselves. There are no health risks when wearing this band for healthy persons as well as patients. If something is still unclear, they can call the number provided at the end of the instruction manual. This way this user gets full support.

Concessions

Due to the limited time for this assignment, concessions have been made to make sure that everything done within this project would be achievable.

  • The first concession is that the prototype will have limited functions.

The most notable functions that the final product should have that the prototype will not have is a Bluetooth connection via which the band is able to send data wirelessly to a mobile device or computer through an app. This app would be the interface of all the data from the band and is used by the doctors to assess the data. Moreover, because of time constraints, only a mock-up of the app can be shown, not a working app.

  • This also results partly in the second concession: the prototype is very cheap and in no way reflects the price of the final product.

The material that is used for the prototype is rather basic and as mentioned before the prototype has limited functions. This makes it hard to determine a clear, definite cost of the final product.

  • The last concession that was made is related to the starting idea of the product.

It was decided that the main goal of the band would be to assist the doctors with a diagnosis instead of actually letting the band make the final diagnosis. This is to avoid the ethical complications that would come with letting a robot make decisions that impact a human life, because who is then to blame when a wrong diagnosis is determined? People generally do not like it when a technology has a final say in any important matter, hence the final call should be made by a person. The fact that people do not trust a technology as much as an educated person is even more true for the elderly. Subsequently, most cases of tremor-related diseases are with elderly people making this an even bigger issue. This led to the decision that the band should merely assist in the final say of a diagnosis instead of having the final say.

Ethical considerations

It is of utmost importance to pay attention to the balance between benefiting the patients’ quality of life, and avoiding damage, risk or injury. (Bulboacă, Bolboacă, & Bulboacă, 2017)

Most concerns around electronic health records (EHRs) like the data the model will calculate and store are around privacy, confidentiality and the jeopardization of autonomy. (Ozair, Jamshed, Sharma, & Aggarwal, 2015) EHRs are massively being implemented because of their several advantages over paper records, since they increase healthcare access, decrease costs and improve care quality. Autonomy can be taken away from patients if their data is shared without their knowledge. Because of this, a patient might choose to withhold important information in fear of their data being leaked. This can cause suboptimal treatment plans with undesired outcomes. Following privacy and confidentiality guidelines, information about a patient can only be shared with third parties with the patients’ consent. Clinical data is confidential and must always be safeguarded. When this patient cannot give informed consent because of mental capacity or old age, this decision falls upon their guardian or legal representative. Data leaks violate a patients’ privacy and thus damage trust in the health care system as a whole. The fact that the privacy and autonomy of patients can be compromised when collecting data from them in a clinical setting is an ethical question that needs to be at the forefront of the development of this band.

Moreover, when can a doctor decide if this band should be worn by a patient? Under which conditions should the band be applied? What should a patient expect from the band? These conditions should be determined before usage to avoid conflict. Little guidance exists in health care, which results in competing pressures and affects the way that the band is put into practice. (Foye et al, 2002)

Beyond conflicts also the clinical reasoning process is being affected by reimbursement or money issues and this raises significant concerns about the way in which we assess the quality of the provided services of the band. If the band is not in the family medicine budget, it will not see the light of day. If the patient needs to buy it to own it and be able to use it, they will only do so if the symptoms become severe. By this time, treatment could have been started way earlier, combating these symptoms. This product needs to not become a product only the rich can afford.

Another closely related issue that arises is that the patient will get less attention from health care professionals compared to now. This can feel less personal, so patients might not feel like they get the care they deserve, even though this model makes the diagnosis more accurate and faster.

All of these ethical concerns need to be taken into account when producing and testing this product. We are confident that a solution can be found that is at least satisfactory for everyone involved, if discussion is not avoided and proper testing is being conducted.


References

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Appendix

Literature study week 1 & 2

Literature study week 1 & 2

Deliverables

  • Wiki page
  • Model
  • A prototype band
  • Presentation

Presentation

Presentation

Peer review

Name Grade
Pim Gort 0
Chantal Vreezen 0
Jan van Leeuwen 0
Jorn Voet -0.5
Femke Ligtenberg +0.5

Planning

What has to be done Person(s)
Week 3
  • Tutor meeting 2
  • Review of previous week
  • Starting on introduction
  • Making the planning
  • Contacting people for interviews
  • Updating wiki
  • Finishing self study
  • Finishing literature
  • All
  • All
  • Femke
  • Jan
  • Pim
  • Jorn
  • Chantal, Jorn, Jan
  • All
Week 4
  • Tutor meeting 3
  • Describe different users
  • Explain why our project is relevant
  • Explain what Parkinson is (finish introduction)
  • All
  • Chantal, Jan
  • Pim, Jorn
  • Femke, Chantal, Jorn
Week 5
  • Tutor meeting 4
  • Start working on model
  • Start working on design
  • All
  • All
  • All
Week 6
  • Tutor meeting 5
  • Finishing model
  • Finishing design
  • All
  • All
  • All
Week 7
  • Tutor meeting 6
  • Putting everything on wiki
  • Checking for fault on wiki
  • All
  • All
  • All
Week 8
  • Finshing the wiki
  • Prepare presenation
  • All
  • All