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Integrated Wearable Sensing and Smart Computing for Mobile Parkinsonian Healthcare.
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Integrated Wearable Sensing and Smart Computing for Mobile Parkinsonian Healthcare./
作者:
Cai, Yi.
面頁冊數:
1 online resource (144 pages)
附註:
Source: Dissertations Abstracts International, Volume: 83-04, Section: B.
Contained By:
Dissertations Abstracts International83-04B.
標題:
Systems science. -
電子資源:
http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=28730819click for full text (PQDT)
ISBN:
9798535577166
Integrated Wearable Sensing and Smart Computing for Mobile Parkinsonian Healthcare.
Cai, Yi.
Integrated Wearable Sensing and Smart Computing for Mobile Parkinsonian Healthcare.
- 1 online resource (144 pages)
Source: Dissertations Abstracts International, Volume: 83-04, Section: B.
Thesis (Ph.D.)--Case Western Reserve University, 2021.
Includes bibliographical references
Parkinson's disease (PD) is the second most common degenerative neurological disorder. The exact cause of PD is still unknown to the public so far. People are at high risk of PD with age increasing. The PD symptoms develop gradually due to the degeneration of brain functions and losing cognitive control abilities. Traditional treatments for PD are under professional nursing and guidance in the hospital. Therefore, PD patients usually face significant challenges to complete the rehabilitation programs effectively without professional nursing after discharge from the hospital. Meanwhile, the absence of long-term reliable medical observations and treatments could result in worse situations for PD rehabilitation.In this dissertation, mobile health technology is utilized to implement applications for mobile parkinsonian healthcare. It is an interdisciplinary study, which integrated Internet of Medical Things, artificial intelligence, and big data analysis. In the aspect of PD gait healthcare, we present a closed-loop sensing and computing system to facilitate long-term medical care. The proposed system comprises wearable sensing, data streaming, online data processing, real-time auditory cueing for PD gait rehabilitation, and data services for their medical carers. Specifically, a smart shoe sensing device is proposed, which contains a customizable insole shaped pressure sensor array and embedded accelerometer and gyroscope. Moreover, the smart shoe takes an unobtrusive design with a hierarchical structure and a wrapped shoe to address the potential issues of user-friendly and comforts. The device combined with the mobile applications could provide comprehensive and robust gait measurements and evaluations. Quantitative gait measurements are implemented and tested to address the sustainability of parkinsonian health assessments. Furthermore, the imports of artificial intelligence for activity recognition and stride length estimation make gait analysis much flexible. It realizes gait analysis in terms of various gait activities. In addition, the closed-loop digital health services drive the medical carers' intervention for the progress of gait rehabilitation easy and convenient. With the closed-loop rhythmic auditory cueing mechanism deployed on the streaming platform, PD patients could perform gait rehabilitations efficiently under self-contained conditions. This research study reveals that integrated wearable sensing and smart computing have enormous potential in improving parkinsonian healthcare.
Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2023
Mode of access: World Wide Web
ISBN: 9798535577166Subjects--Topical Terms:
3168411
Systems science.
Subjects--Index Terms:
Smart computingIndex Terms--Genre/Form:
542853
Electronic books.
Integrated Wearable Sensing and Smart Computing for Mobile Parkinsonian Healthcare.
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Advisor: Huang, Ming-Chun.
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Parkinson's disease (PD) is the second most common degenerative neurological disorder. The exact cause of PD is still unknown to the public so far. People are at high risk of PD with age increasing. The PD symptoms develop gradually due to the degeneration of brain functions and losing cognitive control abilities. Traditional treatments for PD are under professional nursing and guidance in the hospital. Therefore, PD patients usually face significant challenges to complete the rehabilitation programs effectively without professional nursing after discharge from the hospital. Meanwhile, the absence of long-term reliable medical observations and treatments could result in worse situations for PD rehabilitation.In this dissertation, mobile health technology is utilized to implement applications for mobile parkinsonian healthcare. It is an interdisciplinary study, which integrated Internet of Medical Things, artificial intelligence, and big data analysis. In the aspect of PD gait healthcare, we present a closed-loop sensing and computing system to facilitate long-term medical care. The proposed system comprises wearable sensing, data streaming, online data processing, real-time auditory cueing for PD gait rehabilitation, and data services for their medical carers. Specifically, a smart shoe sensing device is proposed, which contains a customizable insole shaped pressure sensor array and embedded accelerometer and gyroscope. Moreover, the smart shoe takes an unobtrusive design with a hierarchical structure and a wrapped shoe to address the potential issues of user-friendly and comforts. The device combined with the mobile applications could provide comprehensive and robust gait measurements and evaluations. Quantitative gait measurements are implemented and tested to address the sustainability of parkinsonian health assessments. Furthermore, the imports of artificial intelligence for activity recognition and stride length estimation make gait analysis much flexible. It realizes gait analysis in terms of various gait activities. In addition, the closed-loop digital health services drive the medical carers' intervention for the progress of gait rehabilitation easy and convenient. With the closed-loop rhythmic auditory cueing mechanism deployed on the streaming platform, PD patients could perform gait rehabilitations efficiently under self-contained conditions. This research study reveals that integrated wearable sensing and smart computing have enormous potential in improving parkinsonian healthcare.
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