Virtual/Augmented Reality for Rehabilitation Applications Using Electromyography as Control/Biofeedback: Systematic Literature Review

Toledo-Peral, Cinthya Lourdes; Vega-Martínez, G.; Mercado-Gutierrez, Jorge A.; Rodríguez-Reyes, Gerardo; Vera, A.; Salas, Lorenzo Leija; Gutiérrez-Martínez, Josefina

doi:10.3390/electronics11142271

Cited by 31 publications

(14 citation statements)

References 95 publications

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“…VR and AR technologies can be utilized as a visual aid for performing a task or immersing oneself in a different environment [ 76 ]. A BCI paradigm in VR has also been suggested, which allows motor priming for patients with limited motor control [ 77 ].…”

Section: Discussionmentioning

confidence: 99%

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

Mitsopoulos

Fiska

Tagaras

et al. 2023

Sensors

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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.

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Section: Discussionmentioning

confidence: 99%

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

Mitsopoulos

Fiska

Tagaras

et al. 2023

Sensors

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“…As Future work regarding this development will focus on the implementation of a small detachable acquisition system aimed at transforming the FELT into a wearable that can be used in different applications. An important one has to do with virtual/augmented reality (VR/AR) interfaces and serious games (Toledo-Peral et al, 2022). We believe that the proposal of arrays such as the one in this article may provide a better starting point for these developments, and that VR/AR applications will certainly benefit from sEMG signals as a control for present and future movements, in addition to being an evaluation stage for previous ones, thus closing the biofeedback loop.…”

Section: Source: Authorsmentioning

confidence: 97%

Development and Validation of a Dry Electrode Array for sEMG Recording and Hand Movement Recognition

Toledo-Peral,

Martín-Vignon-Whaley,

Mercado-Gutierrez

et al. 2024

Ing. Inv.

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Surface electromyography (sEMG) signals are an indirect measurement of muscle activity, and their applications range from biomechanics to control and rehabilitation. Hand movement recognition is a very difficult endeavor due to forearm anatomy. Hence, a multichannel approach for signal acquisition and processing is required. Conventional electrodes can limit the ease-of-use and repeatability of multi-channel sEMG recordings. New techniques have been proposed in this regard, with dry electrodes being one of them. Dry electrode technology has enabled the design of better donning and doffing procedures for multichannel sEMG recording, particularly for rehabilitation and prosthetic applications. However, there is a debate about the quality of the signals recorded with them and their usefulness for the recognition of multiple hand movements. To mitigate these quality issues, this work proposes an array of reusable stainless steel dry electrodes for multichannel sEMG recording with a design that facilitates its positioning on the forearm. The dry electrodes were characterized through electrical impedance measures and a Bland-Altman test. They were found to have similar characteristics to standard, disposable sEMG pre-gelled electrodes. For placement repeatability and application feasibility, an anatomy-based electrode positioning protocol was implemented with 17 healthy subjects and six hand movements. To evaluate the application feasibility of the electrode array, a feed-forward artificial neural network was trained to classify signals from the six movements, with a 97,86±0,58% accuracy. The amplitude of the sEMG signals for two antagonist movements was compared, finding a 24,81% variation. The dry electrode array showed feasibility in acquiring and classifying sEMG signals of hand movements with high accuracy.

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“…[ 91 , 92 , 93 ] In addition, exoskeletons and prostheses linked with the XR platforms can increase rehabilitation efficiency and enable remote training. [ 94 , 95 , 96 ] A customized exoskeleton with cost‐effective fabrication and low power consumption has been developed to detect and display the joint movements of users ( Figure 6 a ). [ 97 ] The triboelectric bidirectional sensors embedded in the exoskeleton monitor multidimensional motions such as rotation, twisting, and linear motion.…”

Section: Metaverse Wearables Coupled With Xr Technologymentioning

confidence: 99%

Metaverse Wearables for Immersive Digital Healthcare: A Review

Kim,

Yang,

Lee

et al. 2023

Advanced Science

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The recent exponential growth of metaverse technology has been instrumental in reshaping a myriad of sectors, not least digital healthcare. This comprehensive review critically examines the landscape and future applications of metaverse wearables toward immersive digital healthcare. The key technologies and advancements that have spearheaded the metamorphosis of metaverse wearables are categorized, encapsulating all‐encompassed extended reality, such as virtual reality, augmented reality, mixed reality, and other haptic feedback systems. Moreover, the fundamentals of their deployment in assistive healthcare (especially for rehabilitation), medical and nursing education, and remote patient management and treatment are investigated. The potential benefits of integrating metaverse wearables into healthcare paradigms are multifold, encompassing improved patient prognosis, enhanced accessibility to high‐quality care, and high standards of practitioner instruction. Nevertheless, these technologies are not without their inherent challenges and untapped opportunities, which span privacy protection, data safeguarding, and innovation in artificial intelligence. In summary, future research trajectories and potential advancements to circumvent these hurdles are also discussed, further augmenting the incorporation of metaverse wearables within healthcare infrastructures in the post‐pandemic era.

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Virtual/Augmented Reality for Rehabilitation Applications Using Electromyography as Control/Biofeedback: Systematic Literature Review

Cited by 31 publications

References 95 publications

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

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

Development and Validation of a Dry Electrode Array for sEMG Recording and Hand Movement Recognition

Metaverse Wearables for Immersive Digital Healthcare: A Review

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