TEMPO 3.1: A Body Area Sensor Network Platform for Continuous Movement Assessment
BSN '09 Proceedings of the 2009 Sixth International Workshop on Wearable and Implantable Body Sensor Networks
Accurate, Fast Fall Detection Using Gyroscopes and Accelerometer-Derived Posture Information
BSN '09 Proceedings of the 2009 Sixth International Workshop on Wearable and Implantable Body Sensor Networks
Proceedings of the Fifth International Conference on Body Area Networks
Enabling longitudinal assessment of ankle-foot orthosis efficacy for children with cerebral palsy
Proceedings of the 2nd Conference on Wireless Health
Power constrained sensor sample selection for improved form factor and lifetime in localized BANs
Proceedings of the conference on Wireless Health
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Gait analysis has long been used for various medical and healthcare assessments [1]. In orthopedics and prosthetics, gait analysis is essential for identifying the pathology and assessing the efficacy of the orthopedic assistants or prosthetics prescribed. For example, the efficacy of ankle-foot orthoses (AFOs), usually prescribed to patients with muscle disorders, (e.g., cerebral palsy, spinal cord injury, muscular dystrophy, etc.) to prevent contractures [2], remains unclear. Studies on recovery and rehabilitation from knee surgery have shown that gait analysis focusing on knee joint angles is the key to evaluating the efficacy of treatment. In elderly healthcare, gait analysis has also played an important role in studies of fall risks and fall prevention [3]. Even in cognitive and neuropsychology studies, gait analysis becomes an important parameter because of the close relationship between human cognitive skills and motor function. For example, [4] and [5] have shown the research value of gait analysis in Parkinson's disease and early childhood autism diagnosis, respectively.