A sEMG-Driven Soft ExoSuit Based on Twisted String Actuators for Elbow Assistive Applications

Abstract

The scope of this work is to show the applicability of the Twisted String Actuators (TSAs) for lightweight, wearable and assistive robotic applications. To this aim, we have developed a novel surface electromyography (sEMG)-driven soft ExoSuit using the TSAs to perform both single and dual-arm elbow assistive applications. The proposed ExoSuit, with an overall weight of 1650 g, uses a pair of TSAs mounted in the back of the user, connected via tendons to the user's forearms to actuate each arm independently for supporting external loads. We confirm this new light-weight and customizable wearable solution via multiple user studies based on the biceps and tricep' sEMG measurements. We demonstrate that user's muscles can automatically activate and regulate the TSAs and compensate for the user's effort: by using our controller based on a Double Threshold Strategy (DTS) with a standard PID regulator, we report that the system was able to limit the biceps' sEMG activity under an arbitrary target threshold, compensating a muscular activity equal to 220% (related to a single arm 3 kg load) and 110% (related to a dual arm 4 kg load) of the threshold value itself. Moreover, the triceps' sEMG signal detects the external load and, depending on the threshold, returns the system to the initial state where it requires no assistance from the ExoSuit. The experimental results show the proposed ExoSuit's capabilities in both single and dualarm load compensation tasks. Therefore, the applicability of the TSAs is experimentally demonstrated for a real-case assistive device, fostering future studies and developments of this kind of actuation strategy for wearable robotic systems.

Human-in-the-Loop Weight Compensation in Upper Limb Wearable Robots Towards Total Muscles’ Effort Minimization

“…Despite of many efforts in design and control of upper limb wearable robots [1], [2], still, design of an effective control approach for upper limb assistance is a challenge; see [3][4][5][6]. And, many of the suggested methods for control of upper limb exoskeletons are not effective.…”

“…Besides, EMG signals provide sufficient information for measuring muscle activity, force, fatigue, and metabolic rate; see [27], [29]. Accordingly, there are many works which benefit the EMG sensors for upper limb exoskeleton torque adaptation; e.g., see [4][5][6], [30][31][32][33]. Nevertheless, the proposed methods require the EMG signal of all contributing muscles which make them impractical, very complex, expensive, and timecostly; e.g., [30], [31] Fig.…”

“…The adaptation rule utilizes the EMG signal of chosen muscles along with the joint positions to estimate mono-articular muscles' torque (τmm) and adapt m. The torque calculator block uses the adapted value of m to update the exoskeleton torque. EMG sensors; see [4], [6], [32], [33]. However, these works are restricted to a single joint (mostly elbow), and they are basically designed for a specific task or device.…”

“…Nevertheless, the proposed methods require the EMG signal of all contributing muscles which make them impractical, very complex, expensive, and time-costly; e.g., [30], [31] utilizes 16 EMG sensors. There are also some other works that utilized a smaller number of EMG sensors; see [4], [6], [32], [33]. However, these works are restricted to a single joint (mostly elbow), and they are basically designed for a specific task or device.…”

“…There are many works benefit the EMG sensors for upper limb exoskeleton torque adaptation; e.g., see [4-6], [28-31]. Nevertheless, the proposed methods require the EMG signal of all contributing muscles which make them impractical, very complex, expensive, and time-costly; e.g., [28], [29] utilizes 16 EMG sensors.…”