A Comparative Study of Deep Learning for Monitoring Motor Behavior in Older Adults Article Swipe
Jae‐Woo Kwon
,
Tae-Kyung Cho
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.9717/kmms.2024.27.7.768
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.9717/kmms.2024.27.7.768
Elderly people need to strengthen their muscle strength and improve their balance ability to prevent falls and chronic diseases. In this study, we modified the existing image classification-based model and performed regression analysis to accurately monitor the motor movements of the elderly. We also proposed a deep learning technique to improve the performance of the model by optimizing the network structure and learning method, and compared the performance. Through this, we derived the most suitable model for monitoring the motor movements of the elderly. This study is expected to contribute to the health care and safety of the elderly.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.9717/kmms.2024.27.7.768
- OA Status
- diamond
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4401385231
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4401385231Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.9717/kmms.2024.27.7.768Digital Object Identifier
- Title
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A Comparative Study of Deep Learning for Monitoring Motor Behavior in Older AdultsWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2024Year of publication
- Publication date
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2024-07-31Full publication date if available
- Authors
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Jae‐Woo Kwon, Tae-Kyung ChoList of authors in order
- Landing page
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https://doi.org/10.9717/kmms.2024.27.7.768Publisher landing page
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YesWhether a free full text is available
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diamondOpen access status per OpenAlex
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https://doi.org/10.9717/kmms.2024.27.7.768Direct OA link when available
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Deep learning, Physical medicine and rehabilitation, Balance (ability), Motor learning, Artificial intelligence, Computer science, Elderly people, Psychology, Machine learning, Medicine, Gerontology, NeuroscienceTop concepts (fields/topics) attached by OpenAlex
- Cited by
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0Total citation count in OpenAlex
- Related works (count)
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10Other works algorithmically related by OpenAlex
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