Abstract
This study examines the predictive ability of fall risks among community dwelling elderly using wearable wireless sensors. Forty-eight community-dwelling elderly (17 non-fallers and 31 fallers) participated in the study. Timed up and go test, sit-to-stand test and ten-meter walking test were carried out. Activitiesspecific Balance Confidence (ABC) Scale was also obtained. The results showed fairly good predictive ability of fall risks among older adults, with stance time, walking velocity and timed up and go time being promising of indicating fall risks. Further investigation is warranted to better understand the signals from the wearable sensors and justify the model. Larger sample size is also warranted to validate the model.
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