PRE2024 3 Group19

Group members

Name	Student Number	Study
Marysia Huige	1896431	PT
Mare Hulshof	1754440	PT
Agnes Kiekebeld	1882511	PT
Lisa van den Berg	1497456	PT
Stijn Schroijen	1840150	CS

Problem Statement

In 2020, 55 million people were diagnosed with dementia worldwide. This number is expected to grow to 139 million people in 2050. (ADI - Dementia Statistics, n.d.) Two thirds of people living in care homes have dementia. (Sharp, 2007) Dementia is a general term for a syndrome that affects memory, thinking and the ability to perform daily tasks. A common symptom of dementia is agitation. When someone is agitated, they feel irritable and restless. People are uncooperative and have difficulties focusing when feeling agitated. They can also show violent or disruptive behavior and have a lack of impulse control. This negative and dangerous behavior could cause dangerous and unpleasant situations for both people with dementia but also for their family, friends, and staff of care homes.

Research has shown that music can have a positive effect on people with dementia. It can help to use music during therapy sessions with a licensed music therapist. Research also shows that music can help outside of therapy sessions. It can help agitated patients feel more calm and it can have a positive impact on a patients heart rate or blood pressure.

Currently, music needs to be played by a caregiver or a therapist; there has to be someone to start the music. But what if there is noone present? Then there is noone to play music for a patient when they are stressed or agitated. This is what our project aims to solve. Instead of needing someone to be present, our proposal is that a wearable device will monitor a patient and start playing music when applicable.

So, this project aims to create a well researched design proposal to help agitated dementia patients without needing immediate assistance of a caregiver, by monitoring a patient's stress level and playing music when they are stressed.

Objectives

The main objective of this research is to find a way to calm dementia patients down when they are feeling stressed. It is quite common for people with dementia to be distressed, which can be caused by feeling disoriented, having unmet needs, as well as many other factors (Coping with distress - Dementia UK). It has been found that music interventions lower anxiety levels and generally make patients (and even caregivers) feel more relaxed (Impacts of Music Intervention on Dementia: A Review Using Meta-Narrative Method and Agenda for Future Research). That is why music will be implemented in the design not alleviate stress In order to further assess what we want our design to achieve we will be using the MoSCoW method.

Must have

• A calming effect on the patient
• A stress sensor of some kind to determine when the music should be turned on

Should have

• Music from the patients youth
• Comfortability (if the stress sensor is wearable)

Could have

• A calming effect on the caregiver
• Slowly increase volume to limit the shock
• A wearable stress sensor, e.g. using HRV in the same way that a watch measures stress
• A stress sensor based on sound

Will not have

• Scaring the patient by sudden loud music

Users (and their requirements)

The target users of this design are people with dementia, particularly those in the mid-to-late stages of the condition. Dementia affects cognitive functions such as reasoning, memory, and emotional regulation, making patients more prone to stress, anxiety, and agitation. This has detrimental effects on their well-being.

Given the cognitive impairments associated with dementia, the design of the aid to measure stress and play music must function autonomously with minimal user input. Furthermore, as most individuals with dementia belong to an older demographic, potential physical limitations should be taken into account. It is essential that the stress sensor is easy to use and imposes minimal physical constraints to ensure comfort and practicality. Potential perceptual limitations are also important to consider. The device for playing music must be able to adjust its volume settings to an appropriate level. The music should be loud enough for the patient to actually perceive the music, but it should not be too loud, since this could only contribute to the distress.

Another crucial user requirement is the personalization of the aid. Both in the measurement of stress and for the intervention in the form of playing music personalization is needed. Personalization allows the aid to calibrate to a user's unique stress patterns, ensuring more accurate responses. Furthermore, since music preferences vary from person to person, the system must be capable of playing the specific music that elicits positive emotions for each individual. This personalization is essential for effectively reducing stress levels and providing a soothing experience.

Since the caregivers of people with dementia are often also affected by distress of these individuals, they can be considered secondary users. They play a vital role in setting up and managing the device, selecting appropriate music and monitoring its effectiveness. To avoid adding to their workload, the system must be as simple to use as possible.

Design Proposal

Our product is designed to start playing music if the measured HRV and GSR levels of the patient has trespassed a certain level. We will call this level the ‘stress-level’. (More research on what the exact stress-level is, will be performed). The HRV and GSR will be measured by a stress monitor device worn by the patient. The patient will have to download an app on their smartphone that will receive and analyse the measured data.

If the measured heartrate is above the stress-level, the app will start playing music through an extern speaker. This speaker will be connected to the smartphone through Bluetooth. Because our design is using an external speaker, it will be more affortable for users that already own a good speaker. This also makes our design more sustainable, since there is no need for producing a new speaker for our design.

The user has the option to play their own chosen music by adding the prefered music to the app. The user will also be able to turn the music off through a 'turn music off' button in the app.

When the stress-level is reached, the volume will increase from 0% to the maximum volume that is set by the user with the volume button in the app.

Actors

Stress monitor device

After researching and comparing different types of stress monitor options, it appears that the best stress monitor for our design is Healthetile's We-Be band.

The We-Be band by Healthetile is a wristband used for precise and continuous monitoring of measurements such as HRV, GSR, temperature and an estimation of blood pressure. We-Be uses Bluetooth Low Energy protocol and offers excellent connection and low-latency data transmission. Furthermore, this wristband has a battery life up to two weeks. Moreover, the We-Be band has user-friendly design which is important since our users would have to wear the band throughtout the entire day. With the We-Be band, it is possible to use the Healthetile’s iOS/Android APIs to retrieve the raw data from the wristband and develop your own app.

User

The user is wearing the stress monitor device through out the day. The user makes sure that their smartphone is charged throughout the day and that the app is downloaded on their own smartphone. Furthermore, the user gives permission to the app for accessing the EDA and HRV data from the stress monitoring device. Lastly, the user sets their preferable maximum volume and added their prefered music to the app.

Smartphone app

The app on the smartphone of the user collects and analyises the data received from the stress monitor device. If the HRV and the EDA data is above a certain stress level threshold, the app will start playing music from volume 0% to the maximum setted volume through Bluetooth via an external speaker.

Bluetooth speaker

The speaker will play the audio that is set in the app by the user starting at volume 0% and increasing to the setted maximum volume. In our design, any speaker that can be connected tot he user's smartphone through Bluetooth can be used.

Analysis of Data

When the We-Be band is connected to a gateway, which could be either a mobile phone or a PC, the data is automatically analyzed and users can visualize the data in real-time.

The We-Be band monitors a wide range of bodily functions. Some of these are particularly relevant for assessing stress, including EDA (electrodermal activity), HRV (Heart rate variability), temperature and an estimation of blood pressure.

We-Be integrates the monitoring of these physiological signals and machine learning by implementing state-of-the art algorithms. This ensures real-time stress evaluation can be provided.

In order to measure HRV, the We-Be band uses photoplethysmography (PPG). The band is equipped with four channels of PPG signals which offer accurate and stable measurement. Multiple automatic PPG annotation modules are integrated in the We-Be platform to clean the raw PPG signals and provide clean signals which can be analyzed.

To illustrate in a bit more detail how the We-Be band accomplishes the analysis raw signals, the analysis of EDA signals is detailed in the section below.

EDA analysis

Electrodermal activity (EDA) is one of the most sensitive indicators of emotional responses, arising from the spontaneous activation of sweat glands in the skin. It is intricately linked to mood, arousal, and attention. Due to its high stability, ease of measurement, and great sensitivity, EDA has become the most effective physiological parameter for reflecting changes in sympathetic nerve activity.

EDA signals are composed of two main components: a tonic component (skin conductance level - SCL), which is a slowly varying signal that establishes the baseline level of EDA, and a phasic component (skin conductance response - SCR), which is a rapidly fluctuating signal directly associated with the activity of the sweat glands, which respond to stimuli such as stress or emotional changes.

The We-Be band incorporates pyEDA, which is an open-source toolkit that can be used to process EDA signals using statistical analysis and automatic feature extraction. It is noteworthy that EDA in pyEDA should not be confused with EDA - GSR (Galvanic Skin Response). In this context, EDA refers to Electronic Design Automation, a field focused on optimizing productivity in the design and manufacturing of electronic components.

Processing EDA Signals using pyEDA

The EDA signals collected by the We-Be band come in a raw format and contain motion artifacts. To effectively use the EDA signal to predict stress, several crucial processing steps need to be undertaken to remove noise and extract a clean signal. An article by Aqajari explains how the pyEDA toolkit does this.

Processing Pipeline Architecture for pyEDA

The pyEDA toolkit processes EDA signals through a structured pipeline that includes a pre-processing and feature extraction stage.

In the pre-processing stage, the raw EDA data undergoes several steps to enhance its quality. The first step is down-sampling. EDA data is typically sampled at a higher frequency than necessary. By reducing the sampling rate, the memory usage and processing can be decreased, while retaining essential information. The next step is moving averaging. This technique smooths the data, helping to eliminate artifacts caused by physical movements and gestures, ensuring that the signal reflects true physiological responses.

Once the data is pre-processed, the meaningful features critical for stress detection are extracted in the feature extraction stage. A key component in this stage is the cvxEDA algorithm, which separates the EDA signal into its tonic and phasic components. This is needed because then rapid changes in the EDA signal which correlate with stress responses can be accurately identified.

After the EDA signals have been processed and features extracted, pyEDA uses machine learning algorithms to build predictive models. These analyze the extracted features to identify patterns associated with stress.  

Design requirements

• The app should automatically connect to the external speaker through Bluetooth.

• The data measured by the stress monitoring device should be used only for this device purposes and should be saved securaty without scolding the user’s privacy.

• The user should be able to easily stop the audio process through a ‘stop’ button in the app.

• If there is no speaker currently available, the app should continue playing music through the smartphone instead.

• The app should have a clear User Interface

Scenario

Phase 1: Start measurements

• The user downloads the app and makes sure the wristband is charged.
• The monitoring device starts measuring the HRV and the GSR.
• The measurements will be sent in real-time to the smartphone app

Phase 2: Monitoring & analyzing measurements

• The app analysis the received raw data and compares it to the stress level threshold.
• If the received data does not passes the threshold, nothing happens.

Phase 3: Stress detected

• If the received data is above the threshold, the app will connect to the external speaker through Bluetooth.
• The speaker will play the audio that is given by the user in the app. The volume will increase from 0% to the maximum volume that is set by the user in the app.

Phase 4: Stop measurements

• The music will stop playing if:
  • The user presses the ‘stop’ button in the app.
  • The measured stress level decreases and are under the threshold stress level.

Testing Possibility

Technical tests

Multiple technical tests should be performed to test the functionality of the prototype. These technical tests should:

• test whether the data is send to the smartphone continiously.

• test whether the app retreives the real-time data.

• test the bluetooth connection between the app and the speaker.

• test whether the app connects the speaker when the data reaches the stress level.

• test whether the on/off button and the volume button work in the app.

• test whether the music stops playing once the measured data is below the stress level.

User test

Once all technical tests have been performed, user tests can be conducted. This test will evaluate what the effect of our prototype on the stress levels of the patients with dementia. The user test contains a control group and a testgroup.

Test group:

The participants will be wearing the We-Be band. If the measured data reaches the stress level, a connection will be made between the app and the speaker allowing the speaker to start playing music.

Control group:

The participants will be wearing the We-Be band. If the patients reach the stress level, no music will start playing.

After conducting this experiment, data will be analyzed to find whether the stress level of the patients in the test group will decrease faster than the stress level in the control group. Furthermore, interview or questionnaries would be performed with the caregivers and/or family of the patients. From this data, we will be able tohave an insign of the effect of our prototype on the patients and the caregivers workload from the caregivers’ point of view.

Stress Measurement Techniques for Wearable Devices

Stress is a physiological and psychological response to external stimuli, influencing various bodily functions such as skin conductance, heart rate and brain activity. Wearable sensors that for monitoring stress are increasingly incorporated in consumer products such as smart watches. However, selecting the right combination of sensors for a wristband involves balancing accuracy, comfort, and practicality. In this section we explore several different stress measurement techniques and evaluate which are the best options to implement in wrist-worn wearables.

Electrocardiography (ECG) - Heart Activity Measurement

ECG measures the electrical activity of the heart, specifically heart rate variability (HRV). A lower HVR often indicates higher stress levels. In order to be able to conduct an ECG, electrodes are placed on the skin, commonly in the form of a chest strap or adhesive patches.

Advantages

- It offers a highly accurate form of stress detection

- It directly measures heart rate fluctuations related to autonomic nervous system activity.

Disadvantages

- It requires precise placement, which is difficult when used in daily life

- It produces large amounts of data, requiring professional interpretation

- It is not easily integrated into a wristband due to placement limitations

Photoplethysmography (PPG) - Optical Heart Rate Monitoring

PPG uses LED light reflection to measure blood volume changes in the capillaries, indirectly determining heart rate and HRV. An LED-light is shown onto the skin and a sensor measures the amount of light that is reflected back. The more light is reflected back, the lower the blood volume. This technology is widely integrated into smartwatches and wristbands.

Advantages:

- The sensor is small, requires little power and is suitable for wearables.

- Provides real-time heart rate and HRV data

Disadvantages:

- less accurate than ECG, especially in high-motion environments

- Affected by skin tone, environmental light, and sensor placement

Galvanic Skin Response (GSR) - Skin Conductance Measurement

GSR measures skin conductivity, which increases as sweat glands activate under stress. This is a direct indicator of autonomic nervous system activity. GSR works through electrodes on the skin that measure the electrical conductivity of the skin.

Advantages:

- Quick detection of emotional responses

- Works well for short-term stress measurement

Disadvantages:

- It is sensitive to environmental factors like humidity and temperature

- contact with the skin is needed and proper positioning for accurate results.

Skin Temperature (ST)

Stress can cause fluctuations in peripheral skin temperature due to changes in blood flow. Wrist-worn thermistors or infrared sensors can detect these changes.

Advantages:

- Non-invasive and easy to integrate.

Disadvantages:

- It is not always a direct stress indicator. Temperature can fluctuate due to other factors. It is more suitable as a secondary sensor that can complement more accurate sensors.

Blood Pressure (BP) and Blood Oxygen Saturation (SpO2)

Blood pressure increases under stress, however it can also fluctuate due to other physiological factors.

Stress and anxiety can alter an individual's breathing, thereby altering the oxygen saturation in the blood.

Advantages:

- Provides additional physiological insights

- Blood Pressure is linked to cardiovascular health, making it useful beyond stress monitoring.

Disavantages:

- Wrist-based blood pressure measurements lack clinical accuracy

- Oxygen saturation fluctuations are not always directly linked to stress.

Which indicators and sensors to use

Based on the strengths and weaknesses of each technology, the best combination of sensors to incorporate in a wristband would include either measures of heart rate variability (preferably PPG) or sensors of Galvanic skin response (GSR) as primary sensors. As an addition, skin temperature sensors or blood pressure sensors can be implemented as secondary sensors to enhance accuracy.

Questions and Answers

Dementia is typically characterized by a disturbance of the higher cortical functions. These include, among others, language, recognizing objects in physical space, and awareness. However, people with dementia can often still remember the lyrics of songs they used to listen to in the earlier stages of life. It seems that the long-term memory for music is often still in tact, even in people in the later stages of dementia and is less affected by the typical metabolic disorders and nerve cell loss. This is the case, because long-term music memory is not located in the hippocampal area, which is were most ordinary memories are stored, but in the supplementary motor cortex, which is responsible for complex motor movements.

Music is often used informally in residents for patients with dementia to strengthen the communication and to enhance the emotional, behavioral and cognitive abilities of patients. This makes contact with caregivers easier.

The effectiveness of music in the reduction of stress can be attributed to multiple mechanisms. Firstly, music can regulate mood by stabilizing the autonomic nervous system, which leads to heightened arousal in people with anxiety. Other studies have indicated that music can stimulate the release of neurotransmitters that contribute to mood regulation and anxiety reduction. It can also serve as a distraction, assisting patients in managing their stress .

When should the music be played?

Research has shown that music can best be played at moments in which a patient experiences acute distress, especially when patients show signs of agitation. However, one should be careful that the sudden playing of music is not an additional stressor for the patient.

What stage of dementia?

It has been found that in people with Alzheimer's Disease the musical memory regions are largely spared and well-preserved. For this reason, music can be very effective in retrieving musical memories for these people and reducing stress.

Music can be effective in all stages of dementia. One study studied the effect of music intervention on patients with severe dementia and found there is a short-term improvement in emotional state. They assessed this by the facial scale, used to assess and code facial expressions. Recognition of familiar music was particularly considered as emotionally meaningful for people at late stages of dementia.

In patients with beginning dementia, music can help them retrieve positive memories and improve language ability. This can improve a sense of self and in this way reduce agitation. These patients often also can still convey their musical preferences, which can help optimize the music played for them when being stressed.

The Role of Music in Stress Reduction

Numerous studies have demonstrated that music can significantly lower stress and anxiety levels. For instance, Nilsson (2008) reviewed 42 randomized control studies and found that soothing music - typically characterized by a tempo of 60 to 80 beats per minute - was particularly effective. Interestingly, the majority of participants responded best to self-selected music, whether it was their favorite songs or choices made from a curated list of genres.

Music has an influence on people's mood and stress in several ways. In this section an overview of the effect of music on different aspects of stress and mood will be presented.

How Music Affects Brain waves

The relationship between music and brain activity is profound. Research indicates that music can alter brain waves, which reflect mental states. When individuals focus on rhythmic stimuli for an extended period, they can reach new levels of awareness. As they engage with the rhythm ,their brain waves synchronize with it, promoting relaxation and reducing stress.

Biochemical Effects of Music

Listening to music also impacts brain chemistry. Multiple brain imaging studies have shown that the brain's responses of listening to pleasant music involve the same regions involved in reward and pleasure. The neurotransmitter dopamine, associated with the brain's reward system, is released when we enjoy pleasant music, contributing to feelings of happiness. Additionally, serotonin, which regulates mood, is increased by enjoyable music and decreased by unpleasant sounds. Slow music has been shown to lower levels of norepinephrine, a hormone that regulates arousal, further aiding in relaxation.

Endorphins, known for inducing feelings of well-being, are also influenced by music. While techno music may lower endorphin levels, classical music tends to elevate them, showcasing the diverse effects different genres can have on our biochemical state.

Music and Cortisol Levels

A major stress system in the human body is the hypothalamus-pituitary-adrenal (HPA) axis. The main effector of the HPA axis is cortisol, also commonly referred to as the 'stress' hormone. Cortisol levels increase in responses to stress and increased cortisol levels can reflect both psychological and behavioral stress.

Cortisol levels are commonly elevated in the elderly. These higher cortisol levels are associated with poorer cognitive abilities, a higher risk of cognitive decline and also faster cognitive decline. It is thus of reasonable importance to try and lower these levels as much as possible.

The impact of music extends to cortisol levels as well. Exposure to music has been shown to reduce elevated cortisol levels, effectively counteracting stress. Notably, major key compositions are more effective in reducing stress and cortisol than minor key pieces. Conversely, techno music can increase stress hormones, while classical music is linked to lower cortisol levels.

Physiological Responses to Music

Musical stimuli, particularly rhythm and tempo, can influence physiological responses through a process known as entrainment. This principle suggests two objects vibrating at similar frequencies will resonate together. For stress reduction, music should ideally have a tempo at or below the resting heart rate (less than 80 beats per minute), predictable dynamics, fluid melodic movement, pleasing harmonies, and regular rhythms. Instruments like strings, flutes, and pianos are particularly effective in creating soothing soundscapes.

Music with slow, steady and repetitive rhythms can exert hypnotic effects, contributing to relaxation. By occupying the brain's attention channels with meaningful and soothing auditory stimuli, music can effectively distract from stressors in the environment.

Individual Preferences and Cultural Influences

It is crucial to recognize that responses to music are not uniform; they vary based on individual factors such as familiarity, preference, current mood, and musical training. Research has shown that subjects from diverse cultures can identify emotions conveyed by music, suggesting a universal connection to musical expression. However, personal preference plays a significant role in the effectiveness of music as a stress-relief tool.

Cultural traditions greatly influence affective responses to music. Therefore, it is recommended that healthcare professionals, such as nurses, consider cultural differences in music preferences when selecting therapeutic music. Studies indicate that participants often prefer no music over prescribed music, highlighting the importance of personal choice in achieving relaxation. The correlation between relaxation and enjoyment of music emphasizes that familiarity and pas experiences can override the inherent qualities of the music itself.

Conclusion

In summary, music serves as a powerful tool for stress reduction, influencing brain activity, biochemistry, and physiological responses. The type of music, its tempo, and personal preferences all play critical roles in its effectiveness. Understanding these factors can help individuals harness the therapeutic potential of music to alleviate stress and enhance well-being.

Effective types of music

Not all types of music are equally effective in the reduction of stress. Multiple studies have shown that music that is familiar to the person with dementia has better effects than unknown music. Each person's history, identity and significant moments from their lives are intimately correlated with their musical taste. Furthermore music that the person has come to know in their youth or as young adult has the best effect. This music often elicits strong memories and emotions, which can help in the reduction of stress and mood improvement. It has been shown that both live music and pre-recorded music work in reducing anxiety.

It seems that specifically the rhythm and melody of the music stimulate calming effects, promoting relaxation and reducing stress levels .

Research indicates that relaxing music often scores high in aesthetic value, familiarity, and acoustic features. In contrast, non-relaxing music is typically marked by higher energy, loudness, and word density. While relaxing music may contain lyrics, their emotional impact is often overshadowed by melodic elements. Studies suggest that melodies, rather than lyrics, primarily influence emotional perceptions.

For people with dementia living in elderly residents, another way in which music can be a relaxing factor, is in that relaxing music can buffer the noise coming from various sources and can decrease the resident's perception of these noxious noises. This in turn lessens the physiological and psychological responses to the noise, including agitated behavior. This, however, would only be effective under the condition that the music is a few decibels above the noise level of the noxious noises. This way some of the primary sources of agitation (e.g. personnel helping other residents) may be decreased and a sound source that is intentionally relaxing is introduced.

Key Characteristics of Relaxing Music

1. Instrumentation: Relaxing music tends to be acoustic and instrumental, allowing the listener to immerse themselves in the sound without the distraction of lyrics.
2. Rhythm and Tempo: The rhythm and pace of music are crucial, with relaxing selections often featuring slow tempos, around 60 beats per minute. This tempo aligns with the natural rhythm of the human heart when at rest. Furthermore, the music should comprise mostly strings with minimal percussion and bass.
3. Dynamic Range: Sedative music typically exhibits a small dynamic range, with sustained melodic lines and minimal fluctuations in volume. Gaston (1952) noted that sedative music features slow attacks and simple rhythms with significant repetition.
4. Familiarity: Familiarity with the music plays a significant role in perceived relaxation. Listeners often prefer music that resonates with their experiences, leading to positive sensory experiences and beneficial chemical changes in the body.
5. Volume level: It has been found that loudness is a characteristic of non-relaxing music. Suggested is that music used for relaxation should have a maximum volume level of 60 dB

Limitations and future additions

Stress measurement

This technology greatly depends on the accuracy of the stress measurement. If the stress is not measured accurately, the device could turn on at undesirable moments. The effectiveness of the music intervention depends on different factors. Firstly, the sensor placement of the wearable is important, especially when measuring PPG and GSR. To get accurate measurements the wearable should have proper skin contact. If the wearer moves around a lot, that can have a negative effect. Additionally, the GSR data can be influenced by external factors such as humidity.

Stress responses are different between individuals . So a standerdized stress threshold may not be effective for everyone. That is why the threshold should be made adaptive, based on the users previous data. Hebben we dit al in ons idee zitten of niet? Hoe bepalen we nu stress?

Music choice

Based on the research we conducted, it was found that reactions to music are not uniform. This implies that a song can make one user very calm, whereas it can have the complete opposite effect on someone else. Because of this, the family and caregivers should be able to curate their own playlist. This can however be difficult if no one know what music a patient used to listen too, or what music used to calm others down. For future additions, we could implement AI to create music. It can start out with music that is generally found to be "calming" and adjust the music based on the physiological reactions of the user.

Furthermore, it has been found that other auditory cues rather than just music can exert the desired relaxing effects. For example sounds as the flowing of rivers or the falling of raindrops can also work for stress relieve. In further research and development in this device the playing of these sounds rather than music when stress is detected could be a valuable extension.

Different stages of dementia

What are the limitations here? People with dementia that is further progressed might not respond as much?

The way that the product can be implemented also greatly depends on the stage of dementia that we focus on. In our case, we decided to focus on medium to late stage dementia. This makes it hard for the patient to remember what music they like, so they will most likely not be able to express their preferences themselves. Based on our RESEARCH (stond in de samenvattingen ergens) we found that late stage dementia patients might have diminished response to music. Even if the effect is small, it always seems to be neutral to positive.

Wearable

Research indicates that individuals with dementia often struggle to accept new devices, such as wearables. A study focusing on nursing home residents and their formal and informal caregivers explored perceptions of wearable technologies. The findings revealed that for a wearable device to be accepted by residents, it must meet a specific set of criteria.

On key consideration is the size of the wearable; it should be compact and unobtrusive to avoid drawing excessive attention, which could lead to resistance from users. Additionally, the design is crucial. If the wearable resembles a watch, but does not look like a traditional watch, it may not be perceived as suitable for individuals with dementia. Caregivers noted that familiarity in design can significantly impact acceptance, as recognizable forms tend to foster comfort and ease of use.

Another important consideration is the placement of the on and off button. If this button is easily accessible to the individual wearing the device, there is a risk that the wearable could be accidentally turned off. People often have a natureal tendency to fiddle with objects around them, and a button located on a wristband becomes an invitingt target for such behavior. This highlights the need for careful design to prevent unintended disruptions in the device's functionality.

Overall, these insights highlight the importance of thoughtful design and user-centric features in developing wearable technologies for dementia patients. The WeBe band, which is used in this project, does not adhere to all these specifications. The WeBe band is quite big and does not have the look or feel of a classic watch. Furthermore, the WeBe band contains buttons which are easy to be reached by the person wearing it. This is an important limitation to consider in this project. Further research could explore other wristbands or other types of wearables to measure stress that might be more suitable for individuals with dementia.

Pavlov effect

During research and brainstorming about ideas for this device, the question arose whether a Pavlov effect could occur, creating an association between once loved music and stress. In other words, whether the music could become a stressor in itself due to the association between music and stress. The Pavlov effect is a consequence of classical conditioning, which can be described as the learning mechanism through which certain stimuli become associated with relevant events. These can be either appetitive or aversive. When a Pavlov effect occurs, a person has thus learned that a certain cue predicts a pleasant or unpleasant event.

During the project, concerns arose whether the music played when stress is detected, could be interpreted as such a cue predicting an the occurrence of a certain event - in our project, stress. In that case, the music that is supposed to be relaxing could have the opposite effect of being a sign the user is stressed, possibly making the individual even more stressed.

Of course these are only speculations and further research would be necessary to fully understand if this indeed is a legitimate concern.

Survey

In order to gather opinions about our device from individuals who have direct contact with dementia patients, we distributed surveys to several care homes and caregivers. We also sent surveys to the research group Dementia & Technology from the TU/e itself. For a more detailed overview of the questions asked in these surveys, please refer to the section "Interviews", which can be found further down this Wiki page.

While we received some valuable responses, the number of participants in our surveys was limited. With more time allocated to this project, we could have conducted more extensive interviews to gain additional insights from those closely interacting with patients.

Furthermore, we were unable to engage directly with individuals living with dementia. this would have been a significant addition to our research, and in future studies, it would be an excellent opportunity to investigate the actual effects and functioning of our device among dementia patients.

Prototype

Perhaps the most significant limitation of this project is that no physical prototype has been constructed, which hindered the ability to test the device effectively. Our group's academic backgrounds resulted in a lack of expertise in protype development, preventing us from creating a functional and testable model. Consequently, our assumptions about the workings of the device, for example what type of music should be played and the timing of it, are solely based on literature research and insights gathered from our interviews.

In future research, developing and testing a physical prototype would be invaluable for refining the device and enhancing its effectiveness. This hands-on approach could provide critical feedback and insights that are essential for the successful development of our device.

Approach, milestones and deliverables

Approach

Overall plan, steps, etc.

Start by doing a literature study. We want to make/ build a prototype and then interview healthcare workers on their opinions on our idea.

Week 1	Week 2	Week 3	Week 4	Week 5	Week 6	Week 7
13/02 Mail with topic and group	Start looking for interviewees	Start on prototype*	Work on prototype	Finalise and test the prototype (make adjustments if necessary)	Prepare presentation	Presentation
Set up project	Work on the design of the prototype	Set up the interview schedule	Make informed consent form	Interview healthcare workers on prototype*	Interpret results from interviews
Search and summarize 25 research papers	Order all necessary components	Literature Research	Make sketch for prototype
Work on Problem statement, Objectives, Users, approach, Milestones, Deliverables, and Planning

*rough estimate in planning

Milestones

What are the big checkpoints, so how long will we be working on each section e.g.

Week 1:

• Finish Problem statement, Objectives, Users, approach, Milestones, Deliverables, and Planning sections

• Finish State of the art section

Week 2:

• Finish making sketches
• Finalise the prototype design

Week 4:

• Finalise Informed consent form
• Finalise interview schedule

Week 5:

• Finalise the prototype and receive feedback

Week 6:

• Receive all data from the interviews

Week 7:

• Give final presentation

Deliverables

What we will be handing in (so are we making a prototype, literature study, etc.)

- Fuctional prototype

- Result of the interviews

- Report about the project in this Wiki

Planning

Prototype	Interviews	Literature Research
Marysia	Lisa	Mare
Stijn	Agnes

State of the art

Literature study with at least 25 relevant papers

Effects of Music on Agitation in Dementia: A Meta-Analysis

https://www.frontiersin.org/journals/psychology/articles/10.3389/fpsyg.2017.00742/full

Pedersen et al. performed a meta-analysis to (1) investigate whether music therapy has a positive effect on reducing agitation for patients with dementia. Furthermore, they (2) compare personalized and group music intervention. Besides that, Pedersen (3) evaluates the effect of preferences in music by comparing music based on patient preference without prior consultation with patients or caregivers. Lastly, the study (4) focusses on comparing the benefits of active versus passive music intervention. In active music intervention, participants actively engage by singing, dancing, or playing an instrument. In passive music intervention, participants listen to live or recorded music without actively engaging.

The results of this meta-analysis indicate that (1) music intervention does significantly decrease agitation in patients with dementia. Furthermore, the analysis (2) shows that personalized music therapy may have a larger effect in certain cases, however the effect is less consistent across the different studies used in this research. Both individual and prescribed music preferences (3) show a medium effect size. Finally, both active and passive music interventions have similar effects. Passive interventions may work better in different settings.

The study performed by Pedersen et al. indicated that music intervention has a reducing effect on agitation of patients with dementia.

The Impact of Music on the Self in Dementia

https://www.researchgate.net/publication/322358822_The_Impact_of_Music_on_the_Self_in_Dementia

This study proposes a theoretical framework which enhances the sense self in patients with dementia. To explain this framework, numerous features of music have been mentioned: Engaging, Persuasive, Social, Synchronization, Physical, Emotional, and Personal.

This framework explains how music engages the five aspects of one’s self, namely ecological, interpersonal, private, extended, and conceptual self.

The ecological self is the self has it is perceived through sensory information and the environment. Numerous features of music, such as physical, synchronous, engaging, and emotional, are important for this self. The interpersonal self can be explained as the self that socially interacts with others. Here the persuasive and engaging aspects of music play a key role. The extended self shows how the self was in the past and how it might be in the future. The different way of engaging with music, and the personal and emotional features of music contributed to engaging the extended self for people with dementia. The private self exists of experiences that others do not have access to, such as thoughts, beliefs, and experiences. Music can help this self as a new way to express themselves. Finally, the conceptual self is indicated the concept that the individual has of themselves, for example self-identity, roles, and social identity.

The researchers of this paper identify the music features and the aspects of the self using two case studies and conclude that music has a unique ability to engage with multiple aspects of the self.

Music and dementia: Observing effects and searching for underlying theories

https://pubmed.ncbi.nlm.nih.gov/21069595/

This research paper studies whether the effect of music on dementia is beneficial and if so, why that is the case. The article focusses on three key areas, namely “music and memory”, “music and depression”, and “Agitation and aggressive behaviors”.

The article states that some people with dementia remember music longer than they remember and respond to other types of information.

Reminiscence music therapy, music therapy that uses familiar songs to trigger memories of the individual with dementia, has reduced working on symptoms of depression.  This could be explained by the fact that music induced physical and emotional changes. Furthermore, music could help reduce stress, sooth pain and energize the body. Therefore, music could be used as an aid for mood regulations.

Moreover, music has a beneficial influence on reducing agitated and aggressive behaviors of individuals with dementia during various activities and various times. Playing music that is preferred by the participant has the biggest outcome. Music makes sounds more familiar and predictable. This could lead to creating a positive emotional state as people retrieve positive memories.

Music and the wellbeing of people with dementia

https://www.researchgate.net/publication/231844344_Music_and_the_wellbeing_of_people_with_dementia

In this study, Sixsmith and Gibson perform qualitative research on the influence that music has on the everyday life of participants with dementia. In-depth interviews were conducted with a sample size consisting of 26 patients with dementia living in either their own homes or in residential care. This paper highlights the benefits of music but also the problems that could arise while listening or actively participating in musical activities.

The data from the interviews shows that the beneficial effect of having music in the lives of people with dementia could enhance the feelings of wellbeing. Music could make people with dementia ready to express their happiness both physically and emotionally.

Furthermore, music supports valued activities. Playing music in the background while working on a task could make the task more enjoyable for people with dementia.

Moreover, music encourages social interaction. During musical activities, most of the participants were accompanied by their family, carers or by other people with dementia. Music therefore is a way for people with dementia to communicate with other sand have meaningful social interactions.

Lastly, music gives people with dementia a higher degree of empowerment and control over their own lives.

Sixsmith and Gibson state multiple challenges that arise when people with dementia engage with music, such as difficulties expressing their preferences, hearing difficulties, the loss of confidence, and social barriers in care homes.

The importance of music for people with dementia: the perspectives of people with dementia, family carers, staff and music therapists

https://pubmed.ncbi.nlm.nih.gov/24410398/

This research paper focused on the meaning and value of musical intervention for not only people with dementia, but also their families, care home staff and music therapists. McDermott et al. are aiming to explore the meaning and value of music from the people with dementia point of view. The paper also analyses how families, care home staff and music therapists view the effects of music. Furthermore, the paper aims to find a link between psychosocial factors and the results of the study to be able to develop a theoretical musical framework of music in dementia.

The qualitative data was ‘gotten’ from conducting focus groups and interviews with care home residents with dementia and their families, care home staff, music therapies, and day hospital clients with dementia.

From the data received, it can be concluded that meaningful musical experience could result in people with dementia feeling emotionally connected with other people. Moreover, musical activities lead to social interaction between residents and staff in care homes. That has resulted in a more positive impact on the environment of the care home.

The researchers also state that music is linked to personal identity and life history of people with dementia.

Impacts of Music Intervention on Dementia: A Review Using Meta-Narrative Method and Agenda for Future Research [1]

This paper shows a meta analysis of the effect of music on dementia patients. Several positive effects of music on patients with dementia have been established in different fields, namely biologically (hr, etc.), behaviorally (less stress, agression, etc.), cognitively (better speech e.g.) and emotionally (more enjoyment in life). It is however mainly focused on guided music intervention, where the patient is encouraged to sing along, etc.

Integrated mental stress smartwatch based on sweat cortisol and HRV sensors [2]

A measurement technique that appears to work quite nicely to measure stress based on sweat cortisol and HRV.

How and why music therapy reduces distress and improves well-being in advanced dementia care: a realist review [3]

Once again mainly focused on music therapy with a music therapist , however that appears to have great effects on patients!

Wearables for residents of nursing homes with dementia and challenging behaviour: Values, attitudes, and needs [4]

What are the requirements for a wearable for patients with dementia?

- Not too tight around the wrist, as that hurts

- Should be recognizable for patients with dementia (as a watch e.g.)

- The patient should not be able to turn the device off themselves by a button on the outside (as some patients turned it off themselves)

- Water resistance

- Small sizes (not too bulky)

- Customizable

Perceived usefulness and comfortability are the most important. There are currently no wearables that can measure stress "live" and are comfortable so there is room for improvement!

User Requirements and Perceptions of a Sensor System for Early Stress Detection in People With Dementia and People With Intellectual Disability: Qualitative Study [5]

Once again what does a stress sensor system for patients with dementia need?

- Integrating it into clothing/ wristbands for familiarity purposes

- Comfortable fabric/ fit

- Customizability to increase user acceptance

- Visibility - Not that visible to others and as discreet as possible

- Easy to put on

Most important: washable and safe!

Perceived positives: identifying stress and using early intervention methods

Perceived negatives: the system not being accepted by the users, replacing the human aspect of care

Effects of Music Therapy on Patients with Dementia—A Systematic Review

https://www.mdpi.com/2308-3417/5/4/62

A systematic review/ meta-analysis was conducted on clinical trials reported from 1 January 1946 to 1 May 2020. The results showed that 13 studies reported overall cognition as an outcome. With 4 showing significant improvements, 6 showing no improvements and 1 with a mixed effect.  The studies also showed that effects of music therapy on the memory of patients living with dementia were mixed, with 4 out of 5 studies reporting significant improvements. Music therapy also showed significant improvements for language or verbal fluency. Two studies explored the effects of singing on BPSD and it showed significant reductions in BPSD in patients with dementia. The results were mixed for listening to music and using musical instruments. Most studies also showed a significant reduction in either anxiety or depression or both. Five studies showed that music listening significantly improved mood, while 2 studies did not show this. There were mixed results for the studies of the effect of music therapy on agitation. Six out of eight studies reported significantly reduced agitation when music listening was the primary intervention, but mixed results were observed for the effects of combined music therapy. In one crossover trial in which Baroque music was played an adverse effect was observed and there was a significant increase in the number of episodes of agitated behaviour when music was played. Levels of were reduced in two of the rials and daily functioning reported no significant improvements. Mixed results were reported on the effects of music therapy on the quality of life.

Music and Other Strategies to Improve the Care of Agitated Patients with Dementia

https://onlinelibrary.wiley.com/doi/abs/10.1111/j.1471-6712.1997.tb00451.x?casa_token=NnZzIXUhdQUAAAAA%3AL6fS0EIVtkv8IdVNXRESCkM4dqy4GqrHrZhSASwlk26HXXDEnZm3whgnqyBoRzQgfXPa1vobJBxcD2I

Agitation is defined as a clinical term for inappropriate verbal or motor activity that is not an obvious expression of need or confusion. Repetitions of words, restlessness and aggression are examples of symptoms that can be included in the concept of agitation. The nursing directors of five nursing homes selected 13 staff from six different wards and the directors of four collective residential units selected four staffs. Interviews were conducted with all responders, they lasted about 45 minutes and the following questions were asked:

·      Can music be used as a nursing intervention for this group of patients?

·      Do you play radio and TV or other forms of music on the ward? If so, in what way does it influence the patients and the nursing staff?

·      What are your opinions and experiences regarding pharmacological treatment of these patients and which psychopharmacological drugs would you suggest for an elderly patient showing irritability and aggression?

And they were also asked to summarize what they regarded as the most important aspect of caring, and to draw up strategies for caring of this group of patients. The following themes were found as strategies to manage agitation in patients with dementia:

Individualized music played for agitated patients with dementia: Analysis of video-recorded sessions

https://onlinelibrary.wiley.com/doi/full/10.1046/j.1440-172X.2001.00254.x?casa_token=1utOksc2pOoAAAAA%3AzPRT6zDTi8aX-g8styz3OcN1KMNGN_MBF3IsZ05oMD2iGYERAZ836hleMNW3U-h8AduawmQKPe1UGnc

Agitation is one of the symptoms patients with dementia suffer from. This study investigated whether individualized music could be used as a nursing intervention to reduce such symptoms. The study was done on four patients. There were video recordings during four sessions in four periods. There was a control period without music and then two periods where individualized music was played, and lastly one period where classical music was played. The documented sessions were analysed and the author noted in a protocol if the patient was calm or agitated. To be considered agitated, the patient would be showing signs of being upset, such as beating the table: shrieking/shouting, trying to stand up, irritability, and/or restlessness. Samples of segments were then analysed by KA by means of Facial Action Coding System technique. This technique is used to identify distinct facial muscle movements. The music seemed to affect all patients, but the two who were most affected by dementia reacted the least to the music. Some days a patient was clearly in a bad mood and then the music did not affect them. When asked the patients told the researchers that they liked the music. The study found a decrease in agitation after individualized music was played. The effect of classical music was not as evident.

Continuous stress detection using the sensors of commercial smartwatch

https://dl.acm.org/doi/abs/10.1145/3341162.3344831?casa_token=EFOoBlgQH-YAAAAA:p-7trEGvcQvtN6qPKkwJhL5dJFvpFdixELZjFKLRNOlQNgc4kfkHBDTcLz7k5YseBX459CjjNmEG

Stress detection using wrist-worn sensors has recently been studied widely and it has been shown that it can detect stress quite reliably. An example is given where stress was measured accurately at a level of 83% at laboratory conditions. It was measured using skin temperature, electrodermal activity, heart rate, blood volume pulse and accelerometer signals. Most studies use, among other bio-sensors, electrodermal activity (EDA or galvanic skin response). The article concentrates on studying how well stress can be detected using the sensors included to commercial smartwatches. The study concludes that the best recognition rate was obtained using a combination of skin temperature, BVP, and heart rate signals ((LDA: 87.4%, QDA: 84.9%, RF: 82.4%). It concludes that EDA signals are not necessary to use in the recognition process.

The article also investigates the effect of window size to the recognition rates and finds that long windows, result in better recognition rates rather than short ones. In their case the best window was 120 seconds.

Stress Watch: The Use of Heart Rate and Heart Rate Variability to Detect Stress: A Pilot Study Using Smart Watch Wearables

https://www.mdpi.com/1424-8220/22/1/151

In this study fitbit was used to record heart rate data alone. ECG was used to generate HRV parameters. A statistical analysis was done on the results of the participants (medical students). Participants completed the DASS and the general population has significantly higher scores on all of the DASS subscales than the medical students. But it was found that both resting and stress phase HR were significantly higher in the medical student population than the general population. The study is relevant for us because it shows that HRV could be used to predict the quality of response to acute stress. And thus this may aid in developing a physiological algorithm for stress that could be incorporated into wearable technologies. Which according to the article (in 2021) there are no devices that have a rigorously validated algorithm for stress detection. Technology and Dementia: The Future is Now | Dementia and Geriatric Cognitive Disorders | Karger Publishers

https://karger.com/dem/article/47/3/131/103431

This article summarizes several key areas of technological development in dementia care. The main domains in which there is a lot of technological advancement include: 1) diagnosis assessment and monitoring, 2) maintenance of functioning, 3) leisure and activity, and 4) caregiving and management.

Examples of technological advances in the domain of leisure and activity also include systems that use music to soothe patients. In the paper a one-button radio is mentioned, but also a simple interface for making music and systems for collaborative music making.

The article ends with the conclusion that, despite numerous technological initiatives in dementia care, adoption rates remain low. Contributing factors include a lack of awareness, challenges in accessibility and insufficient support. The paper emphasizes the need for policies, funding, and practices that go beyond a purely medical approach, advocating for a holistic perspective that includes prevention strategies and ways to support a meaningful life with dementia.

Utilizing a Wristband Sensor to Measure the Stress Level for People with Dementia

https://www.mdpi.com/1424-8220/16/12/1989

This paper describes a study in which the effectiveness of measuring the stress levels in people with dementia using a single wristband sensor is explored. Stress is a common issue for individuals with dementia, and it is traditionally assessed through questionnaires completed by a caregiver. This is a time-consuming and subjective process. In this research, a wearable sensor that tracks galvanic skin response (GSR) and movement is assessed in its effectiveness of detecting stress episodes.

During the study, the sensor continuously recorded physiological data, which was processed using an online platform to classify the stress levels on a scale from 0 to 5. The goal was to find out if the identified stress episodes by the sensor correlated with those observed by the caregiver.

The results showed that there was a strong correlation between the data from the sensor and the caregiver observations. There were, however, strong variations in stress levels among individuals, which highlights the need for personalized stress thresholds. This can improve accuracy in detection.

The conclusion of the researchers is that a wristband sensor is a promising tool for monitoring stress. It provides objective, real-time data, which can help caregivers in for example recognizing stress patterns and intervening more effectively.

Stress as Experienced by People with Dementia: An Interpretative Phenomenological Analysis - Barbara K Sharp, 2019

https://journals.sagepub.com/doi/full/10.1177/1471301217713877?casa_token=qprLlfV-r48AAAAA%3AYsLodnh7jXoRgZiJGKO051DdhsOuYobA-IXvT-pItYVfJr8QPpYGWRGYYTU117SskLCd4OKROKSJ1JE

In this paper, a study is described on the subject of stress as experienced by people with dementia. The study contributes to the supporting of people with dementia, by creating a greater understanding about how people with dementia make meaning from their experience of stress. The questions of interest where how people with dementia perceive their experiences of stress and how they cope with these.

It was found that individual personality traits and established coping styles persist and sustain influence in managing stress. This is contrary to previous assumptions that dementia is paired with an inevitable decline and progressive vulnerability to stress. It was furthermore demonstrated that people with Alzheimer's disease demonstrate a preference for "emotion focused" over "problem solving" approaches.

A Review on Mental Stress Detection Using Wearable Sensors and Machine Learning Techniques | IEEE Journals & Magazine | IEEE Xplore

https://ieeexplore.ieee.org/abstract/document/9445082

This paper provides a review of several methods for detecting mental stress in different environments using wearable sensors and machine learning techniques.

Stress is defined as a psycho-physiological response to challenges that can lead to severe health issues. Wearable sensors collect biological signals that reflect the body's response to stressors. Advantages of wearable sensors include real-time monitoring and non-intrusiveness.

In the article, various physiological signals which have potential to be a measure of stress are considered. Each signal provides unique insights into how the body responds to stress. Some wearables integrate multiple of these sensors to measure stress more effectively.

The article also discusses some challenges and limitations of wearable sensor-based stress detection.

Remote Healthcare for Elderly People Using Wearables: A Review

https://www.mdpi.com/2079-6374/12/2/73

This article discusses the use of wearable sensors for the remote monitoring of elderly individuals. There is a specific focus on how wearables can contribute to healthcare. Several physiological variables that can be measured are discussed, among which heart rate (variability), blood pressure and oxygen saturation.

The article makes a distinction between commercial wearables such as smart watches and research prototypes such as smart textiles. It is stated that the commercial wearables are increasing in their reliability of sensors.

Several benefits and challenges of wearables in elderly care are discussed. Some of the challenges include the limited battery life of wearables and user acceptance. It is however concluded that wearables provide a promising solution for elderly healthcare by enabling continuous monitoring and early disease detection.

Utilising Emotion Monitoring for Developing Music Interventions for People with Dementia: A State-of-the-Art Reviewhttps://www.mdpi.com/1424-8220/23/13/5834

The Effects of Music Therapy on Cognition, Psychiatric Symptoms, and Activities of Daily Living in Patients with Alzheimer’s Disease

https://content.iospress.com/articles/journal-of-alzheimers-disease/jad180183

The effect of music therapy on cognitive functions in patients with dementia: a systematic review and meta-analysis

https://www.tandfonline.com/doi/full/10.1080/13607863.2017.1348474#abstract

Dementia and the Power of Music Therapy

https://onlinelibrary.wiley.com/doi/full/10.1111/bioe.12148

Influence of Music Therapy and Music-Based Interventions on Dementia: A Pilot Study

https://academic.oup.com/jmt/article/58/3/e12/6265007?login=true

Interviews

To get more information and opinions from people that work with people with Dementia, we have decided to conduct interviews. We contacted care homes and caregivers to ask if or how they incorporate music in their care and if they do, how it impacts their patients. We also asked them for their opinion our product proposal so we can get feedback from the people that would be the actual users of the product if it was to be made.

We also contacted the research group Dementia & Technology from the TU/e itself. This way we could ask actual experts on the topic about their opinions on our proposal.

Since caregivers are people with very busy schedules we decided to not only ask them if we can have a conversation but also send them a list of questions that they can answer if they do not have the time to have an actual conversation with us. This way we could still get their opinion, even if they could not meet with us.

For the research group we asked them if they were available to have an in person meeting with us, since we thought they would have more time and be more open to talk with students. We prepared different questions for the people from the research group since we wanted to ask them more about researching people with Dementia and how they deal with the complications that come with it, and if they had any feedback on our product proposal.

Questions for caregivers

The mail was written in Dutch, since that is the language that is used in the care homes that we contacted.

Beste persoonlijke informatie ,

Wij zijn studenten op de Technische Universiteit in Eindhoven. Hiervoor volgen een vak aan de TU/e genaamd Project robots everywhere (0LAUK0) en voor dit project willen wij een prototype ontwikkelen voor mensen met dementie. Het idee is dat wanneer een persoon met dementie onrustig wordt dat er een apparaat is dat muziek afspeelt en zo de patiënt kalmeert. Wij zijn heel erg benieuwd naar de ervaringen van zorgverleners die veel met dementie patiënten te maken hebben. Als u tijd heeft zou er dan een mogelijkheid zijn om deze email naar de zorgmedewerkers te sturen zodat deze de onderstaande vragen kunnen beantwoorden naar hun eigen professionele mening en ervaring? Als jullie er voor openstaan dan zouden wij ook graag hierover willen bellen om hier wat uitgebreider over te hebben.

• Op welke manier werkt u met patiënten met dementie?
• Waar aan merkt u bij een patiënt dat die rusteloos/ geïrriteerd is?
• Op wat voor momenten merkt dat een patiënt rusteloos/ geïrriteerd is?
• Wat zijn uw interventies normaal gesproken wanneer een patiënt gefrustreerd of rusteloos is?
• Wordt er al wel eens muziek afgespeeld bij patiënten (ook als ze rustig zijn)? Zo ja,
  • Wat voor effect heeft het?
  • Wat voor muziek zou dat dan zijn?
  • Heeft verschillende muziek dan ook een ander effect?
• Zou muziek afspelen werken terwijl een patiënt al gefrustreerd is om ze te kalmeren? Of is het beter om al eerder muziek af te spelen wanneer patiënten nog kalm zijn?
• Zou muziek afspelen op momenten dat een patiënt rusteloos/ geïrriteerd is ook een averechts effect kunnen hebben? Zo, ja op welke manier?
• Zou dit prototype ook werken in een groepssetting?
• Zou u een mogelijkheid zien om van ons boven benoemde prototype ook gebruik van maken in de praktijk?
• Zijn er bij z’n soort prototype dingen waar we rekening mee moeten houden waar we nu nog niet aan hebben gedacht?

Alvast heel erg bedankt! Voor vragen of opmerkingen kunt u altijd e-mailen naar: l.v.d.berg@student.tue.nl.

Met vriendelijke Groet,

Lisa van den Berg

The email was send to these emails:

• info@zorgvillaweisshorn.nl
• zorgadvies@vitalisgroep.nl
• info@sintannaklooster.nl
• passaathofvanstrijp@archipelzorggroep.nl
• fleuriade@archipelzorggroep.nl
• eerdbrand@archipelzorggroep.nl
• servicepunt@archipelzorggroep.nl
• familyoffice@domusvaluas.nl
• servicedesk@zorginoktober.nl
• woonzorg@bloezem.nl
• info@elkedageenfijnedag.nl
• contact@pietervanforeest.nl
• info@azora.nl
• IDA@netwerkouderenachterhoek.nl
• info@alzheimer-nederland.nl
• info@tangenborgh.nl
• contact@innoforte-zorg.nl
• adviesteam@pleyade.nl
• info@hetlaar.nl

Questions for research group

• Have you done any research on the effects of music for dementia patients? If yes,
  • What is your role inside this expertise centre?
  • What are the challenges you face when designing for dementia patients?
• What are things we should take into account in the design of our prototype?
• What are things we should take into account in the implementation of our prototype?

Mail for research group

Dear {name},

Together with 5 other students I am currently working on a project for the course Project robots everywhere (0LAUK0). We believe your expertise in the field of {field} could elevate our research, and we would love to discuss our idea with you and hear your insight. In this project we are investigating if music can have a calming effect on patients with dementia when they are distressed. We aim to create a design with a wearable stress monitor that automatically turns on specific music when the user is agitated.

If you have time this week or next week and are interested, I would like to sit together with you for 10-15 minutes. Please let me know if you would like to participate and then we can find a date and time that works for both of us!

Kind regards,

Agnes Kiekebeld

Interview Karlijn van Rijen MSc.

The interview was conducted in Dutch, but the questions were prepared before in English. Since the interview was in Dutch the notes taken during and after the interview are also in Dutch.

Interview questions for Karlijn van Rijen MSc.

• What is your role inside this expertise centre?
• I read your paper on RelivRing can you tell me a bit more about this?
• What are some steps you took in designing this device that you would advice us to take into account in the design process?
• In your information blurb on the ECDT website’s team tab, it says that for your PHd you are doing research into the implementation of technology for elderly care, can you tell me a bit more about that? What are important things to take into account  (that might be different than designing for other target groups)?
• It also says that you are researching the cooperation between researchers, entrepreneurs and healthcare, could you tell me a bit about some of your findings?
• Have you done any research on the effects of music for dementia patients? If yes,

• What are the challenges you face when designing for dementia patients?
• What are things we should take into account in the design of our prototype?
• What are things we should take into account in the implementation of our prototype?

Notes taken during and after the interview

Humesock meet stress en stressopbouw en visualiseert dit via een sock. Door een vroegtijdige waarschuwing kan je eerder reageren en escalatie voorkomen. Misschien goed als we kijken of we kunnen vinden wat voor soort algoritmes deze gebruikt. https://mentechinnovation.eu/hume/

Misschien handig om Joyce Westerink te contacteren of naar haar onderzoek te kijken want zij werkt in de HTI group en werkt veel met psychophysiology in producten en applications. Haar research focust op general wellbeing (mental balance, eudemonia, stress, happiness, arousal) en hoe dat is reflected in physiology en how unobtrusively measure that. https://www.tue.nl/en/research/researchers/joyce-westerink

Ze vertelde ook dat het belangrijk is om mee te nemen of iets pacifier technology is, en dat je dus moet kijken naar de ethische risicos en z’n device niet moet aanzetten als een quick fix want dat zorgt voor onmenselijkheid.

Het is misschien ook goed om ipv naar muziek te kijken naar ambiend sounds (dus ook andere content aanbieden) want die zijn ook veel belovend. (Maarten Houben onderzoek, al gemaild maar nog geen reactie)

De vorm van je device is ook heel belangrijk want zulk soort dingen zijn snel stigmatiserend en zitten niet lekker. Evt, kijken dus naar die sokken of iets van die tracker ringen vertelde ze. Mensen met dementie doen al deze dingen vaak heel snel af. Goed om specifiek te kijken naar fitbits en mensen met dementie was haar advies want ze dacht dat daar ook veel onderzoek naar was gedaan. En hoe zorg je dat mensen dit product in huis willen hebben.

Fitbit werkt niet goed, maar bijv. traditioneel horloge wel meer, enerzijds mooi zijn en anderzijds praktisch dat ze er wel iets mee kunnen.

Goradio is iets waar we naar kunnen kijken want dat is ene ouderwetse radio voor mensen met dementie die je met 1 knop kan aanzetten. Gemaakt door olaf mastenbroek. Ze zei dat we hem een mail konden sturen met dat we zijn gegevens via ECDT hebben. olaf@stichtinggoradio.nl

Marjolijn wintermans is ook goed om literatuur van te lezen, haar onderzoeksperspectief is muziek afspelen dat mensen op hun gemak stelt.

Zij werkt daar via luct, dat is een adviesbureau, soort van als team coordinator over bijv. hoe trekken we funcing aan en welke kant gaan we op met ECDT en ze doet een phd.

Slim om als je echt met mensen in de zorg onderzoek wil doen, zoals dementie patiënten dat je zorgt dat je wat terug doet voor zorgtehuizen, dan willen ze sneller mee werken. Dus maak er een leuke dag van bijv.

Goed om te weten wat ons product als belang is in de realiteit, moeten we goed in beeld brengen. TRL zijn technological readyness levels over hoe ver je bent met je product en wat voor stappen je hiervoor moet ondernemen. Misschien wel slim om dat uit te werken om te kunnen laten zien. Stappen zijn bijv ook zo snel mogelijk funders aantrekken en nwo subsidies, hierna investeerders. Zorg ook dat we goed in beeld hebben wie onze eingebruikers zijn. Kinderen betalen vaak voor zulk soort producten of verzekeraars. Voor wie is het, markt of zorg. Maak dit van te voren duidelijk. Denk aan dat sommige dingen te duur zijn zoals robots die rond het huis lopen maar die wel daarvoor eigenlijk bedoeld zijn.

Hoe zie je dit business model voor je? Aan welke kanalen ga je het verkopen? Is allemaal goed om duidelijk te hebben in je design process.

References

1. ADI - Dementia Statistics. (n.d.). ADI - Dementia Statistics. https://www.alzint.org/about/dementia-facts-figures/dementia-statistics/
2. 2. Sharp, S. (2007). Home From Home : A report highlighting opportunities for improving standards of dementia care in care homes. Alzheimer’s Society. https://europepmc.org/abstract/CTX/c3064

Appendix

Logbook

Log Book Add the hours of work you spent in a week, what tasks you worked on and how long those subtasks took inside of your own table. Per week we should be able to see the total and there will also be a grand total at the end of the project.

Marysia Huige

Week	Task	Hours
1	Brainstorm	1
	Search literature studies	2
	Summarize literature studies	5
	Problem statement	1
	Approach, Milestones, and Deliverables	2
	Total	11
2	Do research about design of prototype	3
	Meeting Monday	1
	Prototype meeting Thursday	1
	Meeting Friday	1
	Find components for prototype	2
	Total	8
3	Meeting Monday	1
	Update Wiki page (planning & approach)	1
	Total

Mare Hulshof

Week	Task	Hours
1	Brainstorm	1
	Search literature studies	1.5
	Summarize literature studies	5.5
	Users (and their requirements)	2
	Total	10
2	Meeting monday	1
	Research about stress sensors	3
	Summarizing findings	3
	Meeting friday	1
	Total	8

Agnes Kiekebeld

Week	Task	Hours
1	Brainstorm	1
	Setting up the wiki page	2
	Search literature studies	2
	Summarize literature studies	3
	Objectives	2
	Total	10
2	Meeting monday	1
	Prototype meeting thursday	1
	Prototype research	4
	Meeting friday	1
	Brainstorm after meeting	1
	Finish summarizing (not yet finished)
	Total	8

Lisa van den Berg

Week	Task	Hours
1	Brainstorm	1
	Search literature	1
	Total	2
2

Stijn Schroijen

Week	Task	Hours
1	Brainstorm	1
	Search literature	1.5
	Total	2.5
2