Embedded Bio-Mimetic System for Functional Electrical Stimulation Controlled by Event-Driven sEMG

Sensors (Basel). 2020 Mar 10;20(5):1535. doi: 10.3390/s20051535.

Abstract

The analysis of the surface ElectroMyoGraphic (sEMG) signal for controlling the Functional Electrical Stimulation (FES) therapy is being widely accepted as an active rehabilitation technique for the restoration of neuro-muscular disorders. Portability and real-time functionalities are major concerns, and, among others, two correlated challenges are the development of an embedded system and the implementation of lightweight signal processing approaches. In this respect, the event-driven nature of the Average Threshold Crossing (ATC) technique, considering its high correlation with the muscle force and the sparsity of its representation, could be an optimal solution. In this paper we present an embedded ATC-FES control system equipped with a multi-platform software featuring an easy-to-use Graphical User Interface (GUI). The system has been first characterized and validated by analyzing CPU and memory usage in different operating conditions, as well as measuring the system latency (fulfilling the real-time requirements with a 140 ms FES definition process). We also confirmed system effectiveness, testing it on 11 healthy subjects: The similarity between the voluntary movement and the stimulate one has been evaluated, computing the cross-correlation coefficient between the angular signals acquired during the limbs motion. We obtained high correlation values of 0.87 ± 0.07 and 0.93 ± 0.02 for the elbow flexion and knee extension exercises, respectively, proving good stimulation application in real therapy-scenarios.

Keywords: embedded system; event-driven; functional electrical stimulation; surface electromyography.

MeSH terms

  • Adult
  • Biomimetics*
  • Computer Graphics
  • Computers
  • Electric Stimulation Therapy / instrumentation*
  • Electric Stimulation Therapy / methods*
  • Electrodes
  • Electromyography / instrumentation*
  • Electromyography / methods*
  • Equipment Design
  • Female
  • Humans
  • Male
  • Movement
  • Muscle, Skeletal / physiology
  • Signal Processing, Computer-Assisted
  • Software
  • User-Computer Interface
  • Wearable Electronic Devices
  • Young Adult