PRE2018 4 Group5: Difference between revisions
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This article reviews the issues and applications for monitoring oxygen saturation, such as detection and monitoring of cardiovascular disease(s), sleeping disorders, respiratory diseases. Some can be avoided by these (daily) measurements. The measurements are not very robust, so patients need to be explained very well how to do them correctly. | This article reviews the issues and applications for monitoring oxygen saturation, such as detection and monitoring of cardiovascular disease(s), sleeping disorders, respiratory diseases. Some can be avoided by these (daily) measurements. The measurements are not very robust, so patients need to be explained very well how to do them correctly. | ||
'''An autonomous robotic exercise tutor for elderly people''' <br> | '''An autonomous robotic exercise tutor for elderly people''' <br> | ||
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'''AI empowered context-aware smart system for medication adherence''' | '''AI empowered context-aware smart system for medication adherence''' | ||
Source: https://www.emeraldinsight.com/doi/pdfplus/10.1108/IJCS-07-2017-0006 | Source: https://www.emeraldinsight.com/doi/pdfplus/10.1108/IJCS-07-2017-0006 | ||
Summary: This article discussing the downside of many (proposed) electronic pillboxes, which use often use time-based reminders. However, these reminders can come at inopportune moments for the pill taker, resulting in suboptimal medication adherence. This article proposes a method of AI-empowered, context-aware reminders. From measurements of the user and the/his environment. This can integrated into our device very well, it seems, only the/a electronic pillbox is optional, although most elderly people have prescription medication, so it is not that strange of an option to pay attention to in our development. | Summary: This article discussing the downside of many (proposed) electronic pillboxes, which use often use time-based reminders. However, these reminders can come at inopportune moments for the pill taker, resulting in suboptimal medication adherence. This article proposes a method of AI-empowered, context-aware reminders. From measurements of the user and the/his environment. This can integrated into our device very well, it seems, only the/a electronic pillbox is optional, although most elderly people have prescription medication, so it is not that strange of an option to pay attention to in our development. | ||
== Fall detection == | == Fall detection == |
Revision as of 12:20, 5 May 2019
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Group members
Group Members | Student nr. |
Erik Wubbels | 0917805 |
Peter Visser | 0877628 |
Jeroen Bakermans | 1007330 |
Bas van Kampen | 1236216 |
Abstract
All robot ideas
Our brainstorm ideas:
- (Using datasets from Eindhoven for) IoT actuation throughout the city.
- Mobile Cloud Robotics as a service with OCCIware
- Robots to help elderly and physically impaired people with daily tasks
- Learning with augmented reality glasses / AI mentor
- Consumer dental x-ray scanner device (+service), from home
- wearable for elderly people to quickly arrange quick responders in case of falling
Problem description
This subject of this project is supporting elderly people living their live independently by assisting them with a wearable AI device. The great strides in the rise in longevity of people, have resulted in an ageing populations in most developed economies. This developed creates new challenges, for the individual as well as society. Many individuals want to live as independently as possible, but their physical and/or mental impairments make that more difficult. It is also difficult for their loved ones, since dangerous situations arise. For both individuals, their families as society as a whole, the associated increase in healthcare costs is a challenge. One of the big problems for all involved is falling. Elderly people are more likely to fall for biological reasons, and their falls can cause bigger damage as well. Additionally, for elderly people it is more risky to undergo surgery, and recovery (such as learning to walk again) is more difficult - for more feeble individuals surgery is not even possible, resulting in a big permanent disability and pain. With more elderly people living on their own, instead of in retirement homes, there is a bigger risk of people lying helplessly on the floor for hours or longer. This is a horrible experience, and it can increase injuries, and even result in death in extreme cases.
This project started with the objective to support these elderly individuals, as well as their families and hence society as a whole, by developing a wearable device to detect falling, and notify people about it. This is a solution in the core of robotics: it combines a device with various mechanical aspects, interaction with the environment, and autonomous behavior.
Subsequently, a wider range of problems our elderly users face has been identified and incorporated into the objectives for the proposed device:
- automatic fall detection, and (after checking) arrange for help
- heart-attack detection
- GPS-tracking to prevent wandering, guide the person back, or arrange help if needed
- voice-control and interaction, specifically for elderly people (training, habituation, etc.)
- medicine planning/reminders, possibly combined with a smart-dispenser
- ...
Notes:
Good subject:
Is in the core of robotics
USE aspects are leading
Can involve study, analysis, design, prototype etc.
For monday 6 may:
objectives: expand?
users
RPC
state-of-the-art: literature study, at least 25 relevant scientific
papers and/or patents studied, summary on the wiki!
approach
planning
milestones
deliverables
who will do what
State of the art
AI supported living for elderly
The Elderly’s Independent Living in Smart Homes: A Characterization of Activities and Sensing Infrastructure Survey to Facilitate Services Development
Source: https://www.mdpi.com/1424-8220/15/5/11312
Summary: an systematic review on ai-support for elderly people, it is about smarthomes, but we can adapt this to our wearable device. The analysis-unit / building block is ‘activity’, to which particular measurements and assistance-forms can be applied. The right kind of sensors, preprocessing and evaluation need to be chosen. This article has a classification of main activities of elderly people living independently, and suitable sensors and data processing for these.
Related: ai-system that uses constraint‐based scheduling technology to actively monitor a pattern of activities executed by the person. Detects temporal constraint violations which are used to trigger meaningful and contextualized proactive interactions:
https://onlinelibrary-wiley-com.dianus.libr.tue.nl/doi/full/10.1111/j.1467-8640.2010.00372.x?sid=worldcat.org
Integrated e-Healthcare System for Elderly Support
Source: https://link-springer-com.dianus.libr.tue.nl/article/10.1007%2Fs12559-015-9367-3
Summary: An unobtrusive integrated e-healthcare system for elderly support (gerontech) for monitoring biomedical parameters of a person in real time, anywhere and in any situation. The data is send to a smartphone or tablet, and can be shared with care-takers. Continunous monitoring gives a wealth of health-data-history for better diagnosing and preventive care, as well as quicker response in emergencies. It also discusses the easy use of contacting medical assistance / consultation from home, which is useful for elderly people with walking disabilities.
Current progress of photoplethysmography and SPO2 for health monitoring
Source: https://link-springer-com.dianus.libr.tue.nl/article/10.1007%2Fs13534-019-00097-w
Summary: A photoplethysmograph (PPG) is a simple medical device for monitoring blood flow and transportation of substances in the blood. It consists of a light source and a photodetector for measuring transmitted and reflected light signals. Clinically, PPGs are used to monitor the pulse rate, oxygen saturation, blood pressure, and blood vessel stiffness. Wearable unobtrusive PPG monitors are commercially available.
This article reviews the issues and applications for monitoring oxygen saturation, such as detection and monitoring of cardiovascular disease(s), sleeping disorders, respiratory diseases. Some can be avoided by these (daily) measurements. The measurements are not very robust, so patients need to be explained very well how to do them correctly.
An autonomous robotic exercise tutor for elderly people
Source: https://link-springer-com.dianus.libr.tue.nl/article/10.1007%2Fs10514-016-9598-5
Summary: Interesting application of using ai – here of a physical robot, not just a wearable device – to help elderly people learn new physical exercises, and to help them train more. ‘ambient assisted living’ is the notion to sustain the mental and physical health of elderly people in the comfort of their own homes. Perhaps we could replace the robot with an instructional videos on tv or laptop or tablet, and the placement of a camera to observe the motions of the elderly trainee, while using our device to measure the activities and use the ai-aspect to interact by providing feedback.
Related: review article about the benefits of training for elderly people, and specifically what kind of exercises are useful:
https://link-springer-com.dianus.libr.tue.nl/article/10.1007%2Fs40520-017-0863-z
AI empowered context-aware smart system for medication adherence Source: https://www.emeraldinsight.com/doi/pdfplus/10.1108/IJCS-07-2017-0006 Summary: This article discussing the downside of many (proposed) electronic pillboxes, which use often use time-based reminders. However, these reminders can come at inopportune moments for the pill taker, resulting in suboptimal medication adherence. This article proposes a method of AI-empowered, context-aware reminders. From measurements of the user and the/his environment. This can integrated into our device very well, it seems, only the/a electronic pillbox is optional, although most elderly people have prescription medication, so it is not that strange of an option to pay attention to in our development.
Fall detection
Emergency Fall Incidents Detection in Assisted Living Environments Utilizing Motion, Sound, and Visual Perceptual Components Source: https://ieeexplore-ieee-org.dianus.libr.tue.nl/document/5623343 Summary: This article discusses an advanced system with various sensors and processing to measure and verify falling, accessing the severity of the situation and arranging suitable help. The method uses semantic representation of the patient's status, context and rules-based evaluation, and advanced classification. The article also discusses various advanced classification techniques that have been and their accuracy and efficiency in detecting an emergency situation.
Inertial Sensing-Based Pre-Impact Detection of Falls Involving Near-Fall Scenarios Source: https://ieeexplore-ieee-org.dianus.libr.tue.nl/document/6905812 Summary: This article discussed two improvements of ‘general’ accelerometer fall-detection. First, it includes ‘near-fall’ scenarios in its analysis. Second, it uses a different way to measure near-fall and fall scenarios, a vertical velocity-based pre-impact fall detection method using a wearable inertial sensor. The conclusion is that this detection method was more accurate in their own experiment, compared to an accelerometer, in detecting fall scenarios from near-fall scenarios. In other words, this method is claimed to solve the issue of ‘false positives’ that ‘mere’ accelerometers have.
Related: This article has a good introduction about fall detection, with many useful references: https://link-springer-com.dianus.libr.tue.nl/article/10.1007%2Fs10015-017-0409-7
Related: increase accuracy with barometric measurements: https://ieeexplore-ieee-org.dianus.libr.tue.nl/document/5559476
Related: increase accuracy with surface electromyography: https://ieeexplore-ieee-org.dianus.libr.tue.nl/document/6399498
Non-academic but useful sources about the problem of elderly people falling
Elderly people fall quicker (biology) https://www.healthdirect.gov.au/what-causes-falls
Falling is more dangerous for an elderly person, also because they often cannot undergo surgery. (medicine) https://www.msdmanuals.com/home/older-people%E2%80%99s-health-issues/falls/falls-in-older-people
Falling elderly people is a real problem, in the US 1 in 4 falls every year! More facts about the size of the problem: (healthcare and social costs) https://www.cdc.gov/homeandrecreationalsafety/falls/adultfalls.html
USE aspects
Users
When looking at which users are to be considered it could be established that, users who seek support with independent living, for example elderly or users with physical or mental impairments, are the primary users.
Society
Independent living is important on this day. The world's older people population is growing at a high speed. So the costs to take care of these elderly people increases also. The nursery homes cannot cope with the speed of the increasing population. resulting in letting elderly people who cannot live independent anymore, live independent.
Enterprise
Living safely independent reduces costs for hospitals and healthcare institutions. Accidents will happen less and when an accident occurs it can be addressed quicker resulting in faster care for the user and probably reduced costs because damage can be fixed faster and in an earlier stage.
Approach
Deliverables
Wiki page Needs to be updated weekly, and in the end give a clear and good overview of the project.
Model Physical and/or digital?
Presentation In week 8
RPCs
Requirements
Preferences
Constraints
Aspect 1
Aspect 2
Aspect 3
Aspect 4
Final Concept
Model
Results and analysis
Detailing
General drone design
Electric circuit
Drone propulsion
Wireless transmission system
Electronic and Propulsion components
Propulsion compartment and drone frame
Specifications
= Files
= Planning
= Reflection