Rapid prototyping of smart garments for activity-aware applications
Journal of Ambient Intelligence and Smart Environments
Gesture-Based affective computing on motion capture data
ACII'05 Proceedings of the First international conference on Affective Computing and Intelligent Interaction
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Gait and postural control are important aspects of human movement and balance. Normal movement control in human is subject to change with aging when the nervous system, comprising somatosensory, visual senses, spatial orientation senses, and neuromuscular control starts to degrade. As a result, the body movement control such as the lateral sway while walking is affected which has been shown to be a significant cause of falling among the elderly. Biofeedback has been investigated to assist elderly improve their body movement and postural ability, by supplementing the feedback to the nervous system. In this paper, we propose a wearable low-power sensor system capable of characterizing lateral sway and gait parameters. Then, it can provide corrective feedback to reduce excessive sway in real-time via vibratory feedback modules. Real-time and low-power characteristics along with wearability of our proposed system allow long-term continuous subjects' sway monitoring while giving direct feedback to enhance walking sway and prevent falling. It can also be used in the clinics as a tool for evaluating the risks of falls, and training users to better maintain their balance. The effectiveness of the biofeedback system was evaluated on 12 older adults as they performed gait and stance tasks with and without biofeedback. Significant improvement (p-value