Prediction of stroke patients’ bedroom-stay duration: machine-learning approach using wearable sensor data

Prediction of stroke patients’ bedroom-stay duration: machine-learning approach using wearable sensor data

Background: The importance of being physically active and avoiding staying in bed has been recognized in stroke rehabilitation. However, studies have pointed out that stroke patients admitted to rehabilitation units often spend most of their day immobile and inactive, with limited opportunities for...

Full description

Bibliographic Details
Main Authors: Takayuki Ogasawara, Masahiko Mukaino, Kenichi Matsunaga, Yoshitaka Wada, Takuya Suzuki, Yasushi Aoshima, Shotaro Furuzawa, Yuji Kono, Eiichi Saitoh, Masumi Yamaguchi, Yohei Otaka, Shingo Tsukada
Format: Article
Language:English
Published: Frontiers Media S.A. 2024-01-01
Series:Frontiers in Bioengineering and Biotechnology
Subjects:
bedroom-stay duration
location tracking
rehabilitation
stroke
machine learning
wearable sensors
Online Access:https://www.frontiersin.org/articles/10.3389/fbioe.2023.1285945/full

Internet

https://www.frontiersin.org/articles/10.3389/fbioe.2023.1285945/full

Similar Items