Gait quality evaluation method for post-stroke patients

ICASSP(2012)

引用 6|浏览11
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摘要
Proliferation of low-cost nonintrusive wearable sensors enables researchers to explore capabilities in monitoring physiological parameters remotely expanding healthcare delivery and reducing costs. One of the parameters that is known to be important in rehabilitation and exercise physiology is human motion monitoring, such as analysis of the walking gait and corresponding characteristics. This paper presents a robust on-line methodology for computing clinically relevant metrics for assessing quality of the walking gait in normal subjects and subjects with gait abnormalities, e.g. in patients with stroke. Furthermore, this paper proposes a metric vector that enables characterization of spatiotemporal features of walking quality evolution for post-stroke patients during and after rehabilitation. This method enables visualization of the gait improvement or changes as a result of the rehabilitation or other treatment techniques.
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关键词
health care,diseases,healthcare delivery,physiology,adaptive matching,biomedical measurement,patient monitoring,walking gait analysis,acceleration measurement,post-stroke patients,gait abnormalities,visualization,motion quality evaluation,patient rehabilitation,gait analysis,gait quality evaluation method,pca,exercise physiology,walking accelerometer data,spatiotemporal features,low-cost nonintrusive wearable sensors,robust on-line methodology,metric vector,walking quality evolution,vectors,human motion monitoring,physiological parameter monitoring,clustering,accelerometers,entropy
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