{"title":"用于人体睡眠姿势和动态活动识别的智能压力电子垫","authors":"Liangqi Yuan;Yuan Wei;Jia Li","doi":"10.1109/JSAS.2024.3501213","DOIUrl":null,"url":null,"abstract":"With the emphasis on healthcare, early childhood education, and fitness, noninvasive measurement and recognition methods have received more attention. Pressure sensing has been extensively studied because of its advantages of simple structure, easy access, visualization application, and harmlessness. This article introduces a Smart Pressure e-Mat (SPeM) system based on piezoresistive material, Velostat, for human monitoring applications, including recognition of sleeping postures, sports, and yoga. After a subsystem scans the e-mat readings and processes the signal, it generates a pressure image stream. Deep neural networks are used to fit and train the pressure image stream and recognize the corresponding human behavior. Four sleeping postures and 13 dynamic activities inspired by Nintendo Switch Ring Fit Adventure are used as a preliminary validation of the proposed SPeM system. The SPeM system achieves high accuracies in both applications, demonstrating the high accuracy and generalizability of the models. Compared with other pressure sensor-based systems, SPeM possesses more flexible applications and commercial application prospects, with reliable, robust, and repeatable properties.","PeriodicalId":100622,"journal":{"name":"IEEE Journal of Selected Areas in Sensors","volume":"2 ","pages":"9-20"},"PeriodicalIF":0.0000,"publicationDate":"2024-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10756666","citationCount":"0","resultStr":"{\"title\":\"Smart Pressure E-Mat for Human Sleeping Posture and Dynamic Activity Recognition\",\"authors\":\"Liangqi Yuan;Yuan Wei;Jia Li\",\"doi\":\"10.1109/JSAS.2024.3501213\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"With the emphasis on healthcare, early childhood education, and fitness, noninvasive measurement and recognition methods have received more attention. Pressure sensing has been extensively studied because of its advantages of simple structure, easy access, visualization application, and harmlessness. This article introduces a Smart Pressure e-Mat (SPeM) system based on piezoresistive material, Velostat, for human monitoring applications, including recognition of sleeping postures, sports, and yoga. After a subsystem scans the e-mat readings and processes the signal, it generates a pressure image stream. Deep neural networks are used to fit and train the pressure image stream and recognize the corresponding human behavior. Four sleeping postures and 13 dynamic activities inspired by Nintendo Switch Ring Fit Adventure are used as a preliminary validation of the proposed SPeM system. The SPeM system achieves high accuracies in both applications, demonstrating the high accuracy and generalizability of the models. Compared with other pressure sensor-based systems, SPeM possesses more flexible applications and commercial application prospects, with reliable, robust, and repeatable properties.\",\"PeriodicalId\":100622,\"journal\":{\"name\":\"IEEE Journal of Selected Areas in Sensors\",\"volume\":\"2 \",\"pages\":\"9-20\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-11-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10756666\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Journal of Selected Areas in Sensors\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/10756666/\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Journal of Selected Areas in Sensors","FirstCategoryId":"1085","ListUrlMain":"https://ieeexplore.ieee.org/document/10756666/","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
摘要
随着人们对医疗保健、幼儿教育和健身的重视,无创测量和识别方法受到越来越多的关注。压力传感因其结构简单、易于获取、可视化应用和无害等优点而被广泛研究。本文介绍了一种基于压阻材料 Velostat 的智能压力电子垫(SPeM)系统,用于人体监测应用,包括识别睡姿、运动和瑜伽。子系统扫描电子垫读数并处理信号后,会生成压力图像流。深度神经网络用于拟合和训练压力图像流,并识别相应的人类行为。受任天堂 Switch Ring Fit Adventure 启发的四种睡眠姿势和 13 种动态活动被用作对所提出的 SPeM 系统的初步验证。SPeM 系统在这两种应用中都达到了很高的准确度,证明了模型的高准确度和通用性。与其他基于压力传感器的系统相比,SPeM 具有更灵活的应用和更广阔的商业应用前景,并具有可靠、稳健和可重复的特性。
Smart Pressure E-Mat for Human Sleeping Posture and Dynamic Activity Recognition
With the emphasis on healthcare, early childhood education, and fitness, noninvasive measurement and recognition methods have received more attention. Pressure sensing has been extensively studied because of its advantages of simple structure, easy access, visualization application, and harmlessness. This article introduces a Smart Pressure e-Mat (SPeM) system based on piezoresistive material, Velostat, for human monitoring applications, including recognition of sleeping postures, sports, and yoga. After a subsystem scans the e-mat readings and processes the signal, it generates a pressure image stream. Deep neural networks are used to fit and train the pressure image stream and recognize the corresponding human behavior. Four sleeping postures and 13 dynamic activities inspired by Nintendo Switch Ring Fit Adventure are used as a preliminary validation of the proposed SPeM system. The SPeM system achieves high accuracies in both applications, demonstrating the high accuracy and generalizability of the models. Compared with other pressure sensor-based systems, SPeM possesses more flexible applications and commercial application prospects, with reliable, robust, and repeatable properties.