Bourke, AK,Ihlen, EAF,Van de Ven, P,Nelson, J,Helbostad, JL,Patton, J,Barbieri, R,Ji, J,Jabbari, E,Dokos, S,Mukkamala, R,Guiraud, D,Jovanov, E,Dhaher, Y,Panescu, D,Vangils, M,Wheeler, B,Dhawan, AP

Video Analysis Validation of a Real-time Physical Activity Detection Algorithm based on a Single Waist Mounted Tri-axial Accelerometer Sensor

2016 38TH ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY (EMBC)

2016

January

Published

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HUMAN MOVEMENT RISK-FACTORS FALLS COMMUNITY

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We have validated a real-time activity classification algorithm based on monitoring by a body worn system which is potentially suitable for low-power applications on a relatively computationally lightweight processing unit. The algorithm output was validated using annotation data generated from video recordings of 20 elderly volunteers performing both a semi-structured protocol and a free-living protocol. The algorithm correctly identified sitting 75.1% of the time, standing 68.8% of the time, lying 50.9% of the time, and walking and other upright locomotion 82.7% of the time. This is one of the most detailed validations of a body worn sensor algorithm to date and offers an insight into the challenges of developing a real-time physical activity classification algorithm for a tri-axial accelerometer based sensor worn at the waist.