Abstract
It is difficult to recognize and classify movement patterns correctly. We have developed and evaluated a method to classify movement using contact forces during sit-to-stand (STS) movement in elderly people. We used the key points of the ground reaction force (GRF) to identify the sequence of important time points in the STS movement of elderly people. The data showed that the reaction forces had three distinctive patterns: typical-modal (t-modal), multi-modal (m-modal), and incompetent-modal (i-modal). This is the first study to identify STS patterns based on objective force data and key points. The STS patterns can be used to supplement the subjective Berg Balance Scale (BBS) score to provide a more precise analysis of STS movement in the elderly.
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Chang, CS., Leung, CY., Liou, JJ. (2011). PC-Based Warning Mechanism System of Fall Risk in Elderly. In: Stephanidis, C. (eds) HCI International 2011 – Posters’ Extended Abstracts. HCI 2011. Communications in Computer and Information Science, vol 174. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-22095-1_2
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DOI: https://doi.org/10.1007/978-3-642-22095-1_2
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