每年專案
摘要
Exercise monitoring systems for rehabilitation are usually not able to pinpoint the exact part for patients' exercise. The research objective is to develop the projection-based motion recognition (PMR) algorithm based on depth data and wide-accepted methods to solve this matter. We regard a motion trajectory as a combination of basic posture units, and then project the basic posture units onto a 2-D space via a projection mapping. Each motion trajectory is transformed to a 2-D motion trajectory map by sequentially connecting the basic posture units involved in the motion trajectory. Finally, we employ a convolutional neural network (CNN)-based classifier to classify the trajectory maps. Accurate classification rate reaches as high as 95.21%. The originality of PMR algorithm lies in (1) it has the generalization capability to some extent since it only adopts popular methods and contains an essential and comprehensive mechanism; (2) the resultant trajectory map may reveal the information about how well a patient execute the rehabilitation assignments.
原文 | ???core.languages.en_GB??? |
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文章編號 | 9430536 |
頁(從 - 到) | 16990-16996 |
頁數 | 7 |
期刊 | IEEE Sensors Journal |
卷 | 21 |
發行號 | 15 |
DOIs | |
出版狀態 | 已出版 - 1 8月 2021 |
指紋
深入研究「A Projection-Based Human Motion Recognition Algorithm Based on Depth Sensors」主題。共同形成了獨特的指紋。專案
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