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Device-free monitoring of vital signs to support emotion-aware music systems for people with dementia

Vuijk, J.G.J. (2022) Device-free monitoring of vital signs to support emotion-aware music systems for people with dementia.

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Abstract:The number of individuals diagnosed with dementia is increasing strongly and is expected to continue to do so in the years to come. Accordingly, this also increases the needed amount of healthcare and costs made for dementia. This has caused the World Health Organization to recognise dementia as a threat to society. The quality of care is at risk and new avenues to address this challenge should be explored. This thesis report builds further on the literature study performed for the course Research Topics, and reports on the project that followed naturally from the observations within Research Topics. It was found that treatments of dementia using music have gained a lot of attention in science given their strong effects on many aspects (e.g. behaviour, character and emotions). The project completed during this thesis is a comparative study of multiple device-free measuring techniques; one in which millimeter wave (mmWave) is used, another where channel state information (CSI) is collected with wireless fidelity (WiFi), and lastly colour intensity tracking using red, green, and blue (RGB) values. This is done to discover the ability of sensors to monitor vital signs. Findings of this work could guide informed decision making in designing an emotion-aware music system to address symptoms of dementia in a cost and care efficient manner. To assess the ability of the sensors to monitor vital signs to support an emotion-aware music system for people with dementia (PWD), heart rate and breathing rate measurements have been collected while subjects were seated in a comfortable chair listening to emotion-inducing music. The emotions include happiness, sadness, anger, and fear. In addition to comparing the ability of sensors to monitor vital signs, this work also includes ethical considerations and privacy risks involved when using the sensors in treatment opportunities for PWD. It was established that WiFi-CSI would be the best option to further explore in regards to the breathing rate. For the heart rate, mmWave sensing was found to be the most suitable candidate for future research. Additionally, results showed measurement-abilities were minimally affected by differences between participants or affective states. It is important that this work is continued by including elderly as participants in a similar experiment. Additionally, the sensor data should be combined with self-reported affective state labels to enable emotion-aware music provision. Eventually, this could potentially address symptoms of dementia in a cost-effective and time-efficient fashion, benefiting both the patient and the healthcare sector.
Item Type:Essay (Master)
Faculty:EEMCS: Electrical Engineering, Mathematics and Computer Science
Subject:50 technical science in general, 54 computer science, 77 psychology
Programme:Interaction Technology MSc (60030)
Link to this item:https://purl.utwente.nl/essays/90483
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