Development of a Low-Cost EEG-Controlled Hand Exoskeleton 3D Printed on Textiles

Abstract

Stroke survivors can be affected by motor deficits in the hand. Robotic equipment associated with brain–machine interfaces (BMI) may aid the motor rehabilitation of these patients. BMIs involving orthotic control by motor imagery practices have been successful in restoring stroke patients' movements. However, there is still little acceptance of the robotic devices available, either by patients and clinicians, mainly because of the high costs involved. Motivated by this context, this work aims to design and construct the Hand Exoskeleton for Rehabilitation Objectives (HERO) to recover extension and flexion movements of the fingers. A three-dimensional (3D) printing technique in association with textiles was used to produce a lightweight and wearable device. 3D-printed actuators have also been designed to reduce equipment costs. The actuator transforms the torque of DC motors into linear force transmitted by Bowden cables to move the fingers passively. The exoskeleton was controlled by neuroelectric signal—electroencephalography (EEG). Concept tests were performed to evaluate control performance. A healthy volunteer was submitted to a training session with the exoskeleton, according to the Graz-BCI protocol. Ergonomy was evaluated with a two-dimensional (2D) tracking software and correlation analysis. HERO can be compared to ordinary clothing. The weight over the hand was around 102 g. The participant was able to control the exoskeleton with a classification accuracy of 91.5%. HERO project resulted in a lightweight, simple, portable, ergonomic, and low-cost device. Its use is not restricted to a clinical setting. Thus, users will be able to execute motor training with the HERO at hospitals, rehabilitation clinics, and at home, increasing the rehabilitation intervention time. This may support motor rehabilitation and improve stroke survivors life quality.

Intention Detection Strategies for Robotic Upper-Limb Orthoses: A Scoping Review Considering Usability, Daily Life Application, and User Evaluation

“…Costs were defined as the financial effort to acquire or maintain usage of an IDS. However, both included studies discussed only acquisition, either as absolute price of the overall system (Webb et al, 2012 ) or relative to the performance of the IDS, i.e., cost-effectiveness (Araujo et al, 2021 ).…”

“…From all included studies, 16 used EEG-based systems based on motor imagery (Pfurtscheller et al, 2000 ; Webb et al, 2012 ; Xiao et al, 2014 ; Soekadar et al, 2015 ; Bi et al, 2017 ; Cantillo-Negrete et al, 2018 ; Kapsalyamov et al, 2019 ; Zhang et al, 2019 ; Badesa et al, 2020 ; Araujo et al, 2021 ), motor execution (Fok et al, 2011 ; King et al, 2014 ; Lee et al, 2017 ; Chowdhury et al, 2018 ), SSVEP (Ortner et al, 2011 ), or ERP (Pedrocchi et al, 2013 ; Delijorge et al, 2020 ) to control the ULO. One included study by Lee et al ( 2017 ) exploited brain activation not directly by EEG, but indirectly by measuring hemodynamic responses, using functional near-infrared spectroscopy (fNIRS), i.e., the varying concentration of oxygen in the blood in activated nerve cells in the cerebral cortex (Naseer and Hong, 2015 ).…”

Design of a 3D-Printed Hand Exoskeleton Based on Force-Myography Control for Assistance and Rehabilitation

“…A test was performed to evaluate the kinematics of the exoskeleton [37]. Videos were recorded at 240 fps while performing finger flexion (starting from the open hand position) with both the bare hand and wearing the exoskeleton.…”

“…Randazzo et al presented "mano", a wearable hand exoskeleton, designed to assist and restore hand functions of people with motor disabilities [36], controlled via a brain-computer interface (BCI). Araujo et al presented Hand Exoskeleton for Rehabilitation Objective (HERO), for the recovery of extension and flexion movements of the fingers in post-stroke patients [37], controlled by a motor imagery BCI. Wege and Zimmermann presented a hand exoskeleton for rehabilitation purposes [38], controlled via 10-channel EMG on the patient's forearm.…”

Biosignal-Based Human–Machine Interfaces for Assistance and Rehabilitation: A Survey

“…Finally, Araujo et al presented HERO, Hand Exoskeleton for Rehabilitation Objective, to recover flexion and extension of the fingers in patients following stroke. This novel, low-cost exoskeleton is 3D-printed on textiles and controlled by motor imagery-based BMI [83].…”