Xin Tan;Yujie Zhang;Zhanhui Lin;Zhuozhuang Zhu;Wei Chen;Ke Xu;Chenyun Dai
{"title":"Oct-HD:用于长期监测的可穿戴分布式无线HD-sEMG同步采集系统","authors":"Xin Tan;Yujie Zhang;Zhanhui Lin;Zhuozhuang Zhu;Wei Chen;Ke Xu;Chenyun Dai","doi":"10.1109/JIOT.2025.3577047","DOIUrl":null,"url":null,"abstract":"High-density surface EMG (HD-sEMG) is gaining attention because of its noninvasive nature and high spatial resolution. However, wearable HD-sEMG measurements with over 128 channels face challenges in system integration and reliable network-free interdevice synchronization. This article presents a wireless distributed wearable HD-sEMG acquisition system named Oct-HD, which supports up to eight acquisition modules (512 channels) with microsecond-level synchronization without requiring a network. The full-channel impedance detection ensures reliable electrode-skin contact and signal acquisition. The system also includes a self-locking base station that stores, charges, and configures the modules. Both simulated and real-world validation demonstrate that the system maintains a long-term intermodule offline error within 3 ms, even under vibrations and extreme temperatures, demonstrating reliability for network-free outdoor and open-space monitoring. To support high-level signal interpretation, we further developed an integrated analysis software suite alongside the hardware. This toolkit enables motor unit decomposition, feature extraction, root mean square (RMS) map and power spectral density (PSD) analysis. Comparative experiments with a commercial system (Sessantaquattro) involving ten hand postures and 17 subjects were conducted, as hand gesture recognition is one of the most common applications in the field of electromyography. Results showed a significant performance improvement (<inline-formula> <tex-math>${p} \\lt 10^{-5}$ </tex-math></inline-formula>) of Oct-HD over the state-of-the-art system in signal quality and anti-interference capacity. Gesture classification results across four mainstream models demonstrated general accuracy improvements with Oct-HD over the commercial system in both dynamic and maintenance tasks. This highlights the effectiveness of Oct-HD in enhancing applications in prosthetic control and human-computer interaction. The Oct-HD system offers a notable advancement in wireless HD-sEMG acquisition, offering superior channel capacity, synchronization precision, signal quality, and anti-interference capacity compared to existing systems. The network-free microsecond-level synchronization and enhanced signal performance provide greater monitoring flexibility across various muscle groups, paving the way for broader applications in human-machine interaction.","PeriodicalId":54347,"journal":{"name":"IEEE Internet of Things Journal","volume":"12 15","pages":"32245-32258"},"PeriodicalIF":8.9000,"publicationDate":"2025-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Oct-HD: A Wearable Distributed Wireless HD-sEMG Synchronous Acquisition System for Long-Term Monitoring\",\"authors\":\"Xin Tan;Yujie Zhang;Zhanhui Lin;Zhuozhuang Zhu;Wei Chen;Ke Xu;Chenyun Dai\",\"doi\":\"10.1109/JIOT.2025.3577047\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"High-density surface EMG (HD-sEMG) is gaining attention because of its noninvasive nature and high spatial resolution. However, wearable HD-sEMG measurements with over 128 channels face challenges in system integration and reliable network-free interdevice synchronization. This article presents a wireless distributed wearable HD-sEMG acquisition system named Oct-HD, which supports up to eight acquisition modules (512 channels) with microsecond-level synchronization without requiring a network. The full-channel impedance detection ensures reliable electrode-skin contact and signal acquisition. The system also includes a self-locking base station that stores, charges, and configures the modules. Both simulated and real-world validation demonstrate that the system maintains a long-term intermodule offline error within 3 ms, even under vibrations and extreme temperatures, demonstrating reliability for network-free outdoor and open-space monitoring. To support high-level signal interpretation, we further developed an integrated analysis software suite alongside the hardware. This toolkit enables motor unit decomposition, feature extraction, root mean square (RMS) map and power spectral density (PSD) analysis. Comparative experiments with a commercial system (Sessantaquattro) involving ten hand postures and 17 subjects were conducted, as hand gesture recognition is one of the most common applications in the field of electromyography. Results showed a significant performance improvement (<inline-formula> <tex-math>${p} \\\\lt 10^{-5}$ </tex-math></inline-formula>) of Oct-HD over the state-of-the-art system in signal quality and anti-interference capacity. Gesture classification results across four mainstream models demonstrated general accuracy improvements with Oct-HD over the commercial system in both dynamic and maintenance tasks. This highlights the effectiveness of Oct-HD in enhancing applications in prosthetic control and human-computer interaction. The Oct-HD system offers a notable advancement in wireless HD-sEMG acquisition, offering superior channel capacity, synchronization precision, signal quality, and anti-interference capacity compared to existing systems. The network-free microsecond-level synchronization and enhanced signal performance provide greater monitoring flexibility across various muscle groups, paving the way for broader applications in human-machine interaction.\",\"PeriodicalId\":54347,\"journal\":{\"name\":\"IEEE Internet of Things Journal\",\"volume\":\"12 15\",\"pages\":\"32245-32258\"},\"PeriodicalIF\":8.9000,\"publicationDate\":\"2025-06-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Internet of Things Journal\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/11025820/\",\"RegionNum\":1,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"COMPUTER SCIENCE, INFORMATION SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Internet of Things Journal","FirstCategoryId":"94","ListUrlMain":"https://ieeexplore.ieee.org/document/11025820/","RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
Oct-HD: A Wearable Distributed Wireless HD-sEMG Synchronous Acquisition System for Long-Term Monitoring
High-density surface EMG (HD-sEMG) is gaining attention because of its noninvasive nature and high spatial resolution. However, wearable HD-sEMG measurements with over 128 channels face challenges in system integration and reliable network-free interdevice synchronization. This article presents a wireless distributed wearable HD-sEMG acquisition system named Oct-HD, which supports up to eight acquisition modules (512 channels) with microsecond-level synchronization without requiring a network. The full-channel impedance detection ensures reliable electrode-skin contact and signal acquisition. The system also includes a self-locking base station that stores, charges, and configures the modules. Both simulated and real-world validation demonstrate that the system maintains a long-term intermodule offline error within 3 ms, even under vibrations and extreme temperatures, demonstrating reliability for network-free outdoor and open-space monitoring. To support high-level signal interpretation, we further developed an integrated analysis software suite alongside the hardware. This toolkit enables motor unit decomposition, feature extraction, root mean square (RMS) map and power spectral density (PSD) analysis. Comparative experiments with a commercial system (Sessantaquattro) involving ten hand postures and 17 subjects were conducted, as hand gesture recognition is one of the most common applications in the field of electromyography. Results showed a significant performance improvement (${p} \lt 10^{-5}$ ) of Oct-HD over the state-of-the-art system in signal quality and anti-interference capacity. Gesture classification results across four mainstream models demonstrated general accuracy improvements with Oct-HD over the commercial system in both dynamic and maintenance tasks. This highlights the effectiveness of Oct-HD in enhancing applications in prosthetic control and human-computer interaction. The Oct-HD system offers a notable advancement in wireless HD-sEMG acquisition, offering superior channel capacity, synchronization precision, signal quality, and anti-interference capacity compared to existing systems. The network-free microsecond-level synchronization and enhanced signal performance provide greater monitoring flexibility across various muscle groups, paving the way for broader applications in human-machine interaction.
期刊介绍:
The EEE Internet of Things (IoT) Journal publishes articles and review articles covering various aspects of IoT, including IoT system architecture, IoT enabling technologies, IoT communication and networking protocols such as network coding, and IoT services and applications. Topics encompass IoT's impacts on sensor technologies, big data management, and future internet design for applications like smart cities and smart homes. Fields of interest include IoT architecture such as things-centric, data-centric, service-oriented IoT architecture; IoT enabling technologies and systematic integration such as sensor technologies, big sensor data management, and future Internet design for IoT; IoT services, applications, and test-beds such as IoT service middleware, IoT application programming interface (API), IoT application design, and IoT trials/experiments; IoT standardization activities and technology development in different standard development organizations (SDO) such as IEEE, IETF, ITU, 3GPP, ETSI, etc.