Wearable muscle movement information measuring device based on acceleration sensor
In this paper, a wearable device designed using acceleration sensors to obtain acceleration information generated by the user's muscles during exercise follows data collection, data pre-processing, feature extraction and feature selection, classification model training, and evaluation of this m...
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| Veröffentlicht in: | Measurement : journal of the International Measurement Confederation 2021-01, Vol.167, p.108274, Article 108274 |
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| container_title | Measurement : journal of the International Measurement Confederation |
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| creator | Xu, Jichao Yuan, Kongjun |
| description | In this paper, a wearable device designed using acceleration sensors to obtain acceleration information generated by the user's muscles during exercise follows data collection, data pre-processing, feature extraction and feature selection, classification model training, and evaluation of this muscle information of human movement. Designed a relevant model verification system and wearable device, and carried out verification experiments on the model in real-time, accuracy, interactivity, and parallelism with other sensor data types. Transitional motion detection and segmentation algorithms can effectively segment out the transition actions included in the acceleration sequence, and using this method to classify and recognize nine kinds of human motion information, the average recognition rate reaches 98.56%. |
| doi_str_mv | 10.1016/j.measurement.2020.108274 |
| format | Article |
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Designed a relevant model verification system and wearable device, and carried out verification experiments on the model in real-time, accuracy, interactivity, and parallelism with other sensor data types. Transitional motion detection and segmentation algorithms can effectively segment out the transition actions included in the acceleration sequence, and using this method to classify and recognize nine kinds of human motion information, the average recognition rate reaches 98.56%.</description><identifier>ISSN: 0263-2241</identifier><identifier>EISSN: 1873-412X</identifier><identifier>DOI: 10.1016/j.measurement.2020.108274</identifier><language>eng</language><publisher>London: Elsevier Ltd</publisher><subject>Acceleration ; Acceleration sensor ; Algorithms ; Data collection ; Exercise ; Feature extraction ; Human motion ; Measuring instruments ; Model accuracy ; Motion perception ; Muscle movement measurement ; Muscles ; Muscular system ; Segmentation ; Sensors ; Verification ; Wearable computers ; Wearable device ; Wearable technology</subject><ispartof>Measurement : journal of the International Measurement Confederation, 2021-01, Vol.167, p.108274, Article 108274</ispartof><rights>2020 Elsevier Ltd</rights><rights>Copyright Elsevier Science Ltd. 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Transitional motion detection and segmentation algorithms can effectively segment out the transition actions included in the acceleration sequence, and using this method to classify and recognize nine kinds of human motion information, the average recognition rate reaches 98.56%.</description><subject>Acceleration</subject><subject>Acceleration sensor</subject><subject>Algorithms</subject><subject>Data collection</subject><subject>Exercise</subject><subject>Feature extraction</subject><subject>Human motion</subject><subject>Measuring instruments</subject><subject>Model accuracy</subject><subject>Motion perception</subject><subject>Muscle movement measurement</subject><subject>Muscles</subject><subject>Muscular system</subject><subject>Segmentation</subject><subject>Sensors</subject><subject>Verification</subject><subject>Wearable computers</subject><subject>Wearable device</subject><subject>Wearable technology</subject><issn>0263-2241</issn><issn>1873-412X</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><recordid>eNqNUMtKxDAUDaLgOPoPFdcd82qSLqX4ggFBFN2FNL2RlGkzJu2Af29rXbh0dbj3ngf3IHRJ8IZgIq7bTQcmjRE66IcNxXTeKyr5EVoRJVnOCX0_RitMBcsp5eQUnaXUYowFK8UKPb-BiabeQdaNyc4QDj9eme9diJ0ZfOizJcP3H1kDB28hq02CJpsuxlrYQVxoCfoU4jk6cWaX4OIX1-j17valesi3T_eP1c02t4yXQy6ZKSTBJVfOGVowVlJqBRaYqIJJVWPBHZWynkbXYEIkg7J0TBRcNUSCY2t0tfjuY_gcIQ26DWPsp0hNuWBCqclzYpULy8aQUgSn99F3Jn5pgvVcoW71nwr1XKFeKpy01aKF6Y2Dh6iT9dBbaHwEO-gm-H-4fAOuu3_s</recordid><startdate>20210101</startdate><enddate>20210101</enddate><creator>Xu, Jichao</creator><creator>Yuan, Kongjun</creator><general>Elsevier Ltd</general><general>Elsevier Science Ltd</general><scope>AAYXX</scope><scope>CITATION</scope></search><sort><creationdate>20210101</creationdate><title>Wearable muscle movement information measuring device based on acceleration sensor</title><author>Xu, Jichao ; Yuan, Kongjun</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c349t-73a5710948ffa2533922c6060185378b064f277b185fd01173e99f36548d17ef3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Acceleration</topic><topic>Acceleration sensor</topic><topic>Algorithms</topic><topic>Data collection</topic><topic>Exercise</topic><topic>Feature extraction</topic><topic>Human motion</topic><topic>Measuring instruments</topic><topic>Model accuracy</topic><topic>Motion perception</topic><topic>Muscle movement measurement</topic><topic>Muscles</topic><topic>Muscular system</topic><topic>Segmentation</topic><topic>Sensors</topic><topic>Verification</topic><topic>Wearable computers</topic><topic>Wearable device</topic><topic>Wearable technology</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Xu, Jichao</creatorcontrib><creatorcontrib>Yuan, Kongjun</creatorcontrib><collection>CrossRef</collection><jtitle>Measurement : journal of the International Measurement Confederation</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Xu, Jichao</au><au>Yuan, Kongjun</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Wearable muscle movement information measuring device based on acceleration sensor</atitle><jtitle>Measurement : journal of the International Measurement Confederation</jtitle><date>2021-01-01</date><risdate>2021</risdate><volume>167</volume><spage>108274</spage><pages>108274-</pages><artnum>108274</artnum><issn>0263-2241</issn><eissn>1873-412X</eissn><abstract>In this paper, a wearable device designed using acceleration sensors to obtain acceleration information generated by the user's muscles during exercise follows data collection, data pre-processing, feature extraction and feature selection, classification model training, and evaluation of this muscle information of human movement. 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| identifier | ISSN: 0263-2241 |
| ispartof | Measurement : journal of the International Measurement Confederation, 2021-01, Vol.167, p.108274, Article 108274 |
| issn | 0263-2241 1873-412X |
| language | eng |
| recordid | cdi_proquest_journals_2463688339 |
| source | Elsevier ScienceDirect Journals |
| subjects | Acceleration Acceleration sensor Algorithms Data collection Exercise Feature extraction Human motion Measuring instruments Model accuracy Motion perception Muscle movement measurement Muscles Muscular system Segmentation Sensors Verification Wearable computers Wearable device Wearable technology |
| title | Wearable muscle movement information measuring device based on acceleration sensor |
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