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.

Wireless sEMG/footswitch driven FPGA embedded digital processor for dynamic MFCV estimation / Mezzina, Giovanni; De Venuto, Daniela. - ELETTRONICO. - (2018). (Intervento presentato al convegno 13th IEEE International Conference on Design & Technology of Integrated Systems in Nanoscale Era, DTIS 2018 tenutosi a Taormina nel April 10-12 2018) [10.1109/DTIS.2018.8368575].

Wireless sEMG/footswitch driven FPGA embedded digital processor for dynamic MFCV estimation

Mezzina, Giovanni;De Venuto, Daniela
2018-01-01

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.
2018
13th IEEE International Conference on Design & Technology of Integrated Systems in Nanoscale Era, DTIS 2018
978-1-5386-5291-6
Wireless sEMG/footswitch driven FPGA embedded digital processor for dynamic MFCV estimation / Mezzina, Giovanni; De Venuto, Daniela. - ELETTRONICO. - (2018). (Intervento presentato al convegno 13th IEEE International Conference on Design & Technology of Integrated Systems in Nanoscale Era, DTIS 2018 tenutosi a Taormina nel April 10-12 2018) [10.1109/DTIS.2018.8368575].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11589/127595
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