Applied Digital Sensor Technology in the Analysis of Different Intensity Movements and Sensor Placements
dc.contributor | 相子元 | zh_TW |
dc.contributor | Tzyy-Yuang Shiang | en_US |
dc.contributor.author | 洋風 | zh_TW |
dc.contributor.author | Füle János Róbert | en_US |
dc.date.accessioned | 2019-09-05T09:15:51Z | |
dc.date.available | 2014-8-26 | |
dc.date.available | 2019-09-05T09:15:51Z | |
dc.date.issued | 2014 | |
dc.description.abstract | Purpose: The study analyzed and compared movement modes and cycles, intensity levels and digital sensor positions. The target was to identify characteristics of body movements that could pave the way to a healthy and sustainable life. Revelations of the study provide potential information for creating a new sporting equipment and experience. Method: The observation of locomotion was executed with three high-tech Inertial Measurement Units (IMUs) that were attached to participants at three locations (shoe, wrist and waist). IMU was the fusion of a gyroscope and an accelerometer. Walk, Run and Jump movements were compared at two intensities. Result: The statistical analysis revealed an applicable correlation between movements and intensities. The simple effects test resulted in non-significant interaction between movements and intensities. This interaction served as a tool for comparing movement patterns with each other. Body movements included a series of gait cycles. The gait cycle was determined by acceleration data. Peak to peak intervals caused by the heel strike of the left foot were compared. Angular velocity data of gait cycles were benchmarked among different intensities. As a result the Shoe IMU measured the angular velocity on the frontal Y axis and discovered a regular sequence of plantar and dorsiflexion. Conclusion: Angular velocity data from the frontal axis clearly identified the movement features of walking, running and jumping. The acceleration data on the sagittal plane could distinguish between low and high intensity movements. The acceleration and gyroscope data determined the intensities and the body movements. The locomotion of lower extremities was widely explored. Waist and wrist IMU data even enabled the estimation of energy expenditure. Analysis methods of sensor signals were subject to investigation. Application of multiple digital sensors provided a unique opportunity for new observations. | zh_TW |
dc.description.abstract | Purpose: The study analyzed and compared movement modes and cycles, intensity levels and digital sensor positions. The target was to identify characteristics of body movements that could pave the way to a healthy and sustainable life. Revelations of the study provide potential information for creating a new sporting equipment and experience. Method: The observation of locomotion was executed with three high-tech Inertial Measurement Units (IMUs) that were attached to participants at three locations (shoe, wrist and waist). IMU was the fusion of a gyroscope and an accelerometer. Walk, Run and Jump movements were compared at two intensities. Result: The statistical analysis revealed an applicable correlation between movements and intensities. The simple effects test resulted in non-significant interaction between movements and intensities. This interaction served as a tool for comparing movement patterns with each other. Body movements included a series of gait cycles. The gait cycle was determined by acceleration data. Peak to peak intervals caused by the heel strike of the left foot were compared. Angular velocity data of gait cycles were benchmarked among different intensities. As a result the Shoe IMU measured the angular velocity on the frontal Y axis and discovered a regular sequence of plantar and dorsiflexion. Conclusion: Angular velocity data from the frontal axis clearly identified the movement features of walking, running and jumping. The acceleration data on the sagittal plane could distinguish between low and high intensity movements. The acceleration and gyroscope data determined the intensities and the body movements. The locomotion of lower extremities was widely explored. Waist and wrist IMU data even enabled the estimation of energy expenditure. Analysis methods of sensor signals were subject to investigation. Application of multiple digital sensors provided a unique opportunity for new observations. | en_US |
dc.description.sponsorship | 體育學系 | zh_TW |
dc.identifier | GN0890300224 | |
dc.identifier.uri | http://etds.lib.ntnu.edu.tw/cgi-bin/gs32/gsweb.cgi?o=dstdcdr&s=id=%22GN0890300224%22.&%22.id.& | |
dc.identifier.uri | http://rportal.lib.ntnu.edu.tw:80/handle/20.500.12235/105902 | |
dc.language | 英文 | |
dc.subject | Movement | zh_TW |
dc.subject | Intensity | zh_TW |
dc.subject | IMU | zh_TW |
dc.subject | Digital Sensor | zh_TW |
dc.subject | Acceleration | zh_TW |
dc.subject | Angular velocity | zh_TW |
dc.subject | Movement | en_US |
dc.subject | Intensity | en_US |
dc.subject | IMU | en_US |
dc.subject | Digital Sensor | en_US |
dc.subject | Acceleration | en_US |
dc.subject | Angular velocity | en_US |
dc.title | Applied Digital Sensor Technology in the Analysis of Different Intensity Movements and Sensor Placements | zh_TW |
dc.title | Applied Digital Sensor Technology in the Analysis of Different Intensity Movements and Sensor Placements | en_US |
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