{"title":"FinePose","authors":"Shubham Rohal, S. Shriram, Vp Nguyen, Shijia Pan","doi":"10.1145/3539489.3539590","DOIUrl":null,"url":null,"abstract":"As people’s lifestyles becomes more sedentary, neck and back pain among young adults have increased. Those who spend a significant amount of time looking at digital screens (e.g., computers, tablets, smartphones) tend to assume forward head postures (FHP), which increases the load on their postural muscles and stress on the cervical spine. As a result, FHP often leads to neck and upper back muscle pains and interferes with normal functioning and quality of life. It may also result in degenerative spine issues, such as cervical degenerative disc disease and cervical osteoarthritis. We present FinePose, a system that measures the postural muscle (upper and middle trapezius muscle) stiffness levels. FinePose repurposes the haptic vibration input on the existing smart posture brace, generated by the lightweight and low-power coin vibration motor, and conducts active vibration sensing to measure the muscle elasticity. It uses an array of accelerometers at different distances from the motor to capture vibration response. Next, FinePose extracts features that describe vibration propagation properties and establishes a regression model to predict the muscle stiffness level. We conduct real world experiments with four subjects on multiple days, and demonstrate preliminary results that validate FinePose's feasibility.","PeriodicalId":278175,"journal":{"name":"Proceedings of the 2022 Workshop on Body-centric Computing Systems","volume":"48 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2022 Workshop on Body-centric Computing Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3539489.3539590","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
As people’s lifestyles becomes more sedentary, neck and back pain among young adults have increased. Those who spend a significant amount of time looking at digital screens (e.g., computers, tablets, smartphones) tend to assume forward head postures (FHP), which increases the load on their postural muscles and stress on the cervical spine. As a result, FHP often leads to neck and upper back muscle pains and interferes with normal functioning and quality of life. It may also result in degenerative spine issues, such as cervical degenerative disc disease and cervical osteoarthritis. We present FinePose, a system that measures the postural muscle (upper and middle trapezius muscle) stiffness levels. FinePose repurposes the haptic vibration input on the existing smart posture brace, generated by the lightweight and low-power coin vibration motor, and conducts active vibration sensing to measure the muscle elasticity. It uses an array of accelerometers at different distances from the motor to capture vibration response. Next, FinePose extracts features that describe vibration propagation properties and establishes a regression model to predict the muscle stiffness level. We conduct real world experiments with four subjects on multiple days, and demonstrate preliminary results that validate FinePose's feasibility.