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

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.Sensors 2020, 20, 1535 2 of 22 and safety of the stimulation and the resulting performance, i.e., a latency short enough to fulfill the real-time constraints and the quality of the stimulated movement.We propose an embedded bio-mimetic FES system based on the Average Threshold Crossing (ATC) event-driven technique applied to the sEMG signal. The ATC essentially compares the sEMG signal with a threshold [6]: the Threshold Crossing (TC) events generate the quasi-digital TC signal, which is characterized by a digital waveform carrying analog (time-based) information. The ATC parameter is then computed by counting the number of TC events during a time window. In [7], we have demonstrated the correlation among ATC, ARV and the muscle force: in particular, having 0.95 ± 0.02 ATC-force w.r.t. 0.97 ± 0.02 ARV-force correlation, the ATC parameter can be used as indicator of muscle activity [8]. In this way, the event-driven approach enables the implementation of a low-complexity on-board feature extraction process, divided into two steps (TC generation and ATC computing), which can be directly performed in hardware [9,10], supporting, e.g., the recognition of different gestures [11][12][13][14]. While the theoretical background of ATC is quite similar to others common sEMG features, e.g., Zero-Crossing (ZC) or Wilson Amplitude (WAMP) [15], our event-based approach could overcome signal processing limitations for embedded feature extraction [16]. In particular, ZC and WAMP calculations are achieved by analyzing an a...

Biomedical Applications with Using Embedded Systems

“…You can perform the software you make on a normal computer on image processing with an embedded system tool such as raspberry pi, arduino, nvidia or a more advanced mini computer or cards. For example, you can perform image processing such as edge detection over the image, thanks to the related software you wrote on the Raspberry pi and a monitor connected to it [16][17][18][19].…”

“…If there is enough memory, a readable code may be preferred instead of optimization. Many certification processes are required for the newly developed product (IEC 62304, EN 50128, [16][17][18][19].…”

Tutorial: A Versatile Bio-Inspired System for Processing and Transmission of Muscular Information

“…Moreover, we designed our system focusing on its versatility. Considering that our research sEMG activities cover different fields, from SoA applications (e.g., low-power muscle and force monitoring [33], [34], hand gesture recognition [35]- [37], control of Functional Electrical Stimulation (FES) [38]- [41]) to emerging ones (e.g., muscle synergies analysis, facial sEMG), we developed a prototype taking into consideration multiple needs. For this reason, in parallel to the ATC extraction, we decided to maintain available to the user the sEMG information.…”

Recent Trends on Applications of Electronics Pervading the Industry, Environment and Society

“…The Special Issue is characterized by 13 original research papers [ 1 , 2 , 3 , 4 , 5 , 6 , 7 , 8 , 9 , 10 , 11 , 12 , 13 ] that we briefly introduce in the following.…”

“…The eighth paper [ 8 ] is entitled “Embedded Bio-Mimetic System for Functional Electrical Stimulation Controlled by Event-Driven sEMG” and is authored by F. Rossi et al, a group of authors from Politecnico di Torino.…”