TY - JOUR
T1 - Development of a wearable surveillance system using gait analysis
AU - Yoshida, Toshihiko
AU - Mizuno, Fumio
AU - Hayasaka, Tomoaki
AU - Tsubota, Kenichi
AU - Imai, Yousuke
AU - Ishikawa, Takuji
AU - Yamaguchi, Takami
PY - 2007/12/1
Y1 - 2007/12/1
N2 - An aging society is a reality in developed countries. An aging population requires more healthcare workers and facilities. To reduce this social problem, it is worthwhile to develop a wearable computer for elders or patients to watch over them. In this study, we developed a wearable computer, in which accelerometers were installed to detect variations of posture, falls, and gait disability. The advantages of this system include a designated database server in each patient's home, scalability and flexibility to adapt to patient's needs, and full patient access to their own information. As a first step, we adopted this system for healthy young volunteers with or without impediments to validate the system. The results show that this system can successfully detect variations in posture and falls. We also succeeded in real-time automatic gait analysis by using the Hampering Index. The present study gives useful knowledge for the development of a wearable computer to support the care of elders or other patients.
AB - An aging society is a reality in developed countries. An aging population requires more healthcare workers and facilities. To reduce this social problem, it is worthwhile to develop a wearable computer for elders or patients to watch over them. In this study, we developed a wearable computer, in which accelerometers were installed to detect variations of posture, falls, and gait disability. The advantages of this system include a designated database server in each patient's home, scalability and flexibility to adapt to patient's needs, and full patient access to their own information. As a first step, we adopted this system for healthy young volunteers with or without impediments to validate the system. The results show that this system can successfully detect variations in posture and falls. We also succeeded in real-time automatic gait analysis by using the Hampering Index. The present study gives useful knowledge for the development of a wearable computer to support the care of elders or other patients.
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U2 - 10.1089/tmj.2007.0015
DO - 10.1089/tmj.2007.0015
M3 - Article
C2 - 18177228
AN - SCOPUS:38349164407
SN - 1530-5627
VL - 13
SP - 703
EP - 713
JO - Telemedicine and e-Health
JF - Telemedicine and e-Health
IS - 6
ER -