Quantitative analysis of the fall-risk assessment test with wearable inertia sensors

• Published in: 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) Vol. 2013; pp. 7217 - 7220
• Main Authors: Tmaura, Toshiyo, Zakaria, Nor Aini, Kuwae, Yutaka, Sekine, Masaki, Minato, Kotaro, Yoshida, Masaki
• Format: Conference Proceeding Journal Article
• Language: English
• Published: United States IEEE 01.01.2013
• Subjects: Acceleration; Accidental Falls - prevention & control; Aged; Angular velocity; Biomechanical Phenomena; Equipment Design; Exercise Test - methods; Healthy Volunteers; Hemiplegia - physiopathology; Humans; Legged locomotion; Middle Aged; Monitoring, Ambulatory - methods; Motion; Outpatients; Risk Assessment - methods; Senior citizens; Sensors; Stroke - physiopathology; Thigh; Walking - physiology; Wireless communication; Wireless sensor networks
• ISSN: 1094-687X; 1557-170X
• DOI: 10.1109/EMBC.2013.6611223

We performed a quantitative analysis of the fall-risk assessment test using a wearable inertia sensor focusing on two tests: the time up and go (TUG) test and the four square step test (FSST). These tests consist of various daily activities, such as sitting, standing, walking, stepping, and turning. The TUG test was performed by subjects at low and high fall risk, while FSST was performed by healthy elderly and hemiplegic patients with high fall risk. In general, the total performance time of activities was evaluated. Clinically, it is important to evaluate each activity for further training and management. The wearable sensor consisted of an accelerometer and angular velocity sensor. The angular velocity and angle of pitch direction were used for TUG evaluation, and those in the pitch and yaw directions at the thigh were used for FSST. Using the threshold of the angular velocity signal, we classified the phase corresponding to each activity. We then observed the characteristics of each activity and recommended suitable training and management. The wearable sensor can be used for more detailed evaluation in fall risk management. The wearable sensor can be used more detailed evaluation for fall-risk management test.