A Biomimetic Multichannel Synergistic Calibration for Event-Driven Functional Electrical Stimulation

In this paper, we present the Profile Extraction (PE) algorithm, which allows the computation of a multi-channel profile highly correlated with voluntary muscle activity. This event-based profile can be used as biomimetic control during the calibration phase of a Functional Electrical Stimulation (FES) system. The adoption of the PE technique represents the preliminary step to extend the applicability of our event-driven paradigm to control the coordinated multi-joint movements. Through an experimental campaign, we tested the improvements made by the use of PE in the FES calibration, assessing the reproducibility between the voluntary and stimulated movements. Results show a 2 % increase of the median correlation value for a single-channel exercise and a 3.6 % increase for a dual-channel one. A statistical decrease of normalized Root Mean Square Error has been obtained for the dual-channel exercise (p < 0.05)

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

Device wearability and operating time are trending topics in recent state-of-art works on surface ElectroMyoGraphic (sEMG) muscle monitoring. No optimal trade-off, able to concurrently address several problems of the acquisition system like robustness, miniaturization, versatility, and power efficiency, has yet been found. In this tutorial we present a solution to most of these issues, embedding in a single device both an sEMG acquisition channel, with our custom event-driven hardware feature extraction technique (named Average Threshold Crossing), and a digital part, which includes a microcontroller unit, for (optionally) sEMG sampling and processing, and a Bluetooth communication, for wireless data transmission. The knowledge acquired by the research group brought to an accurate selection of each single component, resulting in a very efficient prototype, with a comfortable final size (57.8mm x 25.2mm x 22.1mm) and a consistent signal-to-noise ratio of the acquired sEMG (higher than 15 dB). Furthermore, a precise design of the firmware has been performed, handling both signal acquisition and Bluetooth transmission concurrently, thanks to a FreeRTOS custom implementation. In particular, the system adapts to both sEMG and ATC transmission, with an application throughput up to 2 kB s-1 and an average operating time of 80 h (for high resolution sEMG sampling), relaxable to 8Bs-1 throughput and about 230 h operating time (considering a 110mAh battery), in case of ATC acquisition only. Here we share our experience over the years in designing wearable systems for the sEMG detection, specifying in detail how our event-driven approach could benefit the device development phases. Some previous basic knowledge about biosignal acquisition, electronic circuits and programming would certainly ease the repeatability of this tutorial

An Event-Driven Closed-Loop System for Real-Time FES Control

The paper proposes an event-driven sEMG-control-FES system based on the ATC muscle processing approach, which allows an online and real-time FES intensity modulation. The promising outcomes of our experimental tests, both in terms of movement reproducibility and system processing latency (thanks to the low ATC computational cost), demonstrate the feasibility of the ATC-control-FES in the rehabilitation scenario, which provides satisfactory results similar to other state-of-the-art works (as reported in table II). Starting from this point, we will further investigate additional applications in which an event-driven control could be implemented, e.g. the exoskeleton or prosthetic control