NeuroSuitUp: System Architecture and Validation of a Motor Rehabilitation Wearable Robotics and Serious Game Platform

BACKGROUND

This article presents the system architecture and validation of the NeuroSuitUp body-machine interface (BMI). The platform consists of wearable robotics jacket and gloves in combination with a serious game application for self-paced neurorehabilitation in spinal cord injury and chronic stroke.

METHODS

The wearable robotics implement a sensor layer, to approximate kinematic chain segment orientation, and an actuation layer. Sensors consist of commercial magnetic, angular rate and gravity (MARG), surface electromyography (sEMG), and flex sensors, while actuation is achieved through electrical muscle stimulation (EMS) and pneumatic actuators. On-board electronics connect to a Robot Operating System environment-based parser/controller and to a Unity-based live avatar representation game. BMI subsystems validation was performed using exercises through a Stereoscopic camera Computer Vision approach for the jacket and through multiple grip activities for the glove. Ten healthy subjects participated in system validation trials, performing three arm and three hand exercises (each 10 motor task trials) and completing user experience questionnaires.

RESULTS

Acceptable correlation was observed in 23/30 arm exercises performed with the jacket. No significant differences in glove sensor data during actuation state were observed. No difficulty to use, discomfort, or negative robotics perception were reported.

CONCLUSIONS

Subsequent design improvements will implement additional absolute orientation sensors, MARG/EMG based biofeedback to the game, improved immersion through Augmented Reality and improvements towards system robustness.

User-centered development process of an operating interface to couple a robotic glove with a virtual environment to optimize hand rehabilitation following a stroke

Introduction

Task-specific neurorehabilitation is crucial to optimize hand recovery shortly after a stroke, but intensive neurorehabilitation remains limited in resource-constrained healthcare systems. This has led to a growing interest in the use of robotic gloves as an adjunct intervention to intensify hand-specific neurorehabilitation. This study aims to develop and assess the usability of an operating interface supporting such a technology coupled with a virtual environment through a user-centered design approach.

Methods

Fourteen participants with hand hemiparesis following a stroke were invited to don the robotic glove before browsing through the operating interface and its functionalities, and perform two mobility exercises in a virtual environment. Feedback was collected for improving technology usability. Participants completed the System Usability Scale and ABILHAND questionnaires and their recommendations were gathered and prioritized in a Pugh Matrix.

Results

The System Usability Scale (SUS) score for the operating interface was excellent (M = 87.0 SD = 11.6). A total of 74 recommendations to improve the user interface, calibration process, and exercise usability were identified.

Conclusion

The application of a full cycle of user-centred design approach confirms the high level of usability of the system which is perceived by end users as acceptable and useful for intensifying neurorehabilitation.

Development and control of a home-based training device for hand rehabilitation with a spring and cable driven mechanism

Rehabilitation at home is rapidly increasing. Although successful results are achieved with treatment methods applied in rehabilitation clinics, there are also some disadvantages in this process, such as dependence on an expert and high costs. Developments in mechatronic technologies have accelerated the development of assistive devices which are designed for use at home. One of the rehabilitation applications is on a hemiplegic hand. In previous studies, some useful devices have been developed for hand rehabilitation. In this study, we suggest a new, low-cost and wearable robotic glove for hand rehabilitation. The specific component of this device is the spring and cable driven system proposed for transmission of motion and force. The device was tested on both unimpaired participants and patients with the hemiplegic hand, and it was proven to be beneficial for hand rehabilitation. As a result of trials with unimpaired participants, the muscle activation of the extensor digitorum and the flexor carpi radialis were increased by 184.1 and 197.8% respectively. The weight of the device was less than 400 g, thanks to 3D printed parts.