{"title":"用于动态MFCV估计的无线sEMG/脚踏开关驱动FPGA嵌入式数字处理器","authors":"G. Mezzina, D. Venuto","doi":"10.1109/DTIS.2018.8368575","DOIUrl":null,"url":null,"abstract":"This paper proposes the design and the implementation of an FPGA-based Cyber-physical system for the real-time monitoring of the Muscle Fiber Conduction Velocity (MFCV). The MFCV is evaluated during the walking by using of 4 wireless surface EMG electrodes, and 2 footswitches. The implemented algorithm, for the MFCV assessment, is based on the extraction of the degree of resemblance between 2 EMG signals from the same leg. The processor architecture has been fully implemented on FPGA. The system data transmission is entrusted to a Bluetooth module, which connects the FPGA to an external device. The complete system occupies 12% ALMs, 5903 ALUTs, 5% registers, 3.28% block memory, provide of the Altera Cyclone V. The computation time is respectively 125ns for the footswitch and 316ms for the EMG data, while 63.5±0.25ms are spent for the processing and MFCV evaluation. The technique has been validated on 6 subjects and the measurement results are here reported. The in-vivo measures agree with the clinical results, providing an MFCV=7.6m/s±0.36m/s, i.e., <0.1m/s w.r.t. typical value, for healthy subjects in the same operating conditions.","PeriodicalId":328650,"journal":{"name":"2018 13th International Conference on Design & Technology of Integrated Systems In Nanoscale Era (DTIS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Wireless sEMG/footswitch driven FPGA embedded digital processor for dynamic MFCV estimation\",\"authors\":\"G. Mezzina, D. Venuto\",\"doi\":\"10.1109/DTIS.2018.8368575\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper proposes the design and the implementation of an FPGA-based Cyber-physical system for the real-time monitoring of the Muscle Fiber Conduction Velocity (MFCV). The MFCV is evaluated during the walking by using of 4 wireless surface EMG electrodes, and 2 footswitches. The implemented algorithm, for the MFCV assessment, is based on the extraction of the degree of resemblance between 2 EMG signals from the same leg. The processor architecture has been fully implemented on FPGA. The system data transmission is entrusted to a Bluetooth module, which connects the FPGA to an external device. The complete system occupies 12% ALMs, 5903 ALUTs, 5% registers, 3.28% block memory, provide of the Altera Cyclone V. The computation time is respectively 125ns for the footswitch and 316ms for the EMG data, while 63.5±0.25ms are spent for the processing and MFCV evaluation. The technique has been validated on 6 subjects and the measurement results are here reported. The in-vivo measures agree with the clinical results, providing an MFCV=7.6m/s±0.36m/s, i.e., <0.1m/s w.r.t. typical value, for healthy subjects in the same operating conditions.\",\"PeriodicalId\":328650,\"journal\":{\"name\":\"2018 13th International Conference on Design & Technology of Integrated Systems In Nanoscale Era (DTIS)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-04-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 13th International Conference on Design & Technology of Integrated Systems In Nanoscale Era (DTIS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/DTIS.2018.8368575\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 13th International Conference on Design & Technology of Integrated Systems In Nanoscale Era (DTIS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/DTIS.2018.8368575","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Wireless sEMG/footswitch driven FPGA embedded digital processor for dynamic MFCV estimation
This paper proposes the design and the implementation of an FPGA-based Cyber-physical system for the real-time monitoring of the Muscle Fiber Conduction Velocity (MFCV). The MFCV is evaluated during the walking by using of 4 wireless surface EMG electrodes, and 2 footswitches. The implemented algorithm, for the MFCV assessment, is based on the extraction of the degree of resemblance between 2 EMG signals from the same leg. The processor architecture has been fully implemented on FPGA. The system data transmission is entrusted to a Bluetooth module, which connects the FPGA to an external device. The complete system occupies 12% ALMs, 5903 ALUTs, 5% registers, 3.28% block memory, provide of the Altera Cyclone V. The computation time is respectively 125ns for the footswitch and 316ms for the EMG data, while 63.5±0.25ms are spent for the processing and MFCV evaluation. The technique has been validated on 6 subjects and the measurement results are here reported. The in-vivo measures agree with the clinical results, providing an MFCV=7.6m/s±0.36m/s, i.e., <0.1m/s w.r.t. typical value, for healthy subjects in the same operating conditions.