Enhancing Virtual Rehabilitation in Upper Limbs With Biocybernetic Adaptation: The Effects of Virtual Reality on Perceived Muscle Fatigue, Game Performance and User Experience

Montoya, Maria F.; Muñoz, John Edison; Henao, Oscar

doi:10.1109/tnsre.2020.2968869

Cited by 27 publications

(16 citation statements)

References 24 publications

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“…Hwang et al explored the effects of robot-assisted (RA) virtual reality (VR) intervention on motor function (MF) and neurological function (NF) in patients with stroke (CS) [ 7 ]. Montoya et al outlined the application of immersive virtual reality-assisted rehabilitation technology in gait rehabilitation of stroke patients and compared it with traditional rehabilitation methods [ 8 ]. Hwang et al discussed the effects of virtual reality-based upper limb rehabilitation training on upper limb function, muscle activity, daily living activities, and quality of life of stroke patients [ 7 ].…”

Section: Introductionmentioning

confidence: 99%

Clinical Effect of Virtual Reality Technology on Rehabilitation Training of Sports Injury

Chen

2021

Journal of Healthcare Engineering

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In order to make most patients recover most of their limb functions after rehabilitation training, virtual reality technology is an emerging human-computer interaction technology, which uses the computer and the corresponding application software to build the virtual reality environment. Completing the training tasks in the virtual environment attracts the patients to conduct repeated training in the game and task-based training mode and gradually realizes the rehabilitation training goals. For the rehabilitation population with certain exercise ability, the kinematics of human upper limbs is mainly analyzed, and the virtual reality system based on HTC VIVE is developed. The feasibility and work efficiency of the upper limb rehabilitation training system were verified by experiments. Adult volunteers who are healthy and need rehabilitation training to participate in the experiment were recruited, and experimental data were recorded. The virtual reality upper limb rehabilitation system was a questionnaire. By extracting the motion data, the system application effect is analyzed and evaluated by the simulation diagram. Follow-up results of rehabilitation training showed that the average score of healthy subjects was more than 4 points and 3.8 points per question. Therefore, it is feasible to perform upper limb rehabilitation training using the HTC VIVE virtual reality rehabilitation system.

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Section: Introductionmentioning

confidence: 99%

Clinical Effect of Virtual Reality Technology on Rehabilitation Training of Sports Injury

Chen

2021

Journal of Healthcare Engineering

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“…can not only enhance the user performance (reduced task completion time) but also regulate users to gain the required motor skills. Previous VR studies have shown that virtual environments that can provide a high sense of "immersion" can help users to improve task performance [33]. In this study, we designed high-fidelity static and dynamic visual stimuli to provide a high sense of "immersion" as well as to represent real-world HRC task scenarios.…”

Section: Discussionmentioning

confidence: 99%

A Physics-based Virtual Reality System Design and Evaluation by Simulating Human-Robot Collaboration

Chowdhury¹,

Mubarrat²,

Fernandes³

2022

Preprint

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Recent advancements in VR technology facilitate tracking real-world objects and users' movements in the virtual environment (VE) and inspire researchers to develop a physics-based haptic system (i.e., real object haptics) instead of computer-generated haptic feedback. However, there is limited research on the efficacy of such VR systems in enhancing operators’ sensorimotor learning for tasks that require high motor and physical demands. Therefore, this study aimed to design and evaluate the efficacy of a physics-based virtual reality (VR) system that provides users realistic cutaneous and kinesthetic haptic feedback. We designed a physics-based VR system, named PhyVirtual, and simulated human-robot collaborative (HRC) sequential pick-and-place lifting tasks in the VE. Participants performed the same tasks in the real environment (RE) with human-human collaboration instead of human-robot collaboration. We used a custom-designed questionnaire, the NASA-TLX, and electromyography activities from biceps, middle and anterior deltoid muscles to determine user experience, workload, and neuromuscular dynamics, respectively. Overall, the majority of responses (>65%) demonstrated that the system is easy-to-use, easy-to-learn, and effective in improving motor skill performance. While compared to tasks performed in the RE, the PhyVirtual system placed significantly lower physical demand (124.90%; p < 0.05) on the user. The electromyography data exhibited similar trends (p > 0.05; r > 0.89) for both environments. These results show that the PhyVirtual system is an effective tool to simulate safe human-robot collaboration commonly seen in many modern warehousing settings. Moreover, it can be used as a viable replacement for live sensorimotor training in a wide range of fields.

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“…Thus, it provides a functional parameter for the assessment of neuromuscular and metabolic mechanisms that underlie fatigue, not motor function. However, muscle fatigue does influence performance in motor impairment, and it has been explored as a complementary biomarker for rehabilitation, for quantifying the effects of fatigue in the performance of different interventions, such as virtual reality (Montoya et al, 2020). Muscle fatigue has been widely studied in robot-based rehabilitation to address the phenomenon of fatigue compensation during rehabilitation, which can lead patients to recruit trunk and shoulder during arm movements, causing an undesirable rehabilitation and risks of injury (Huang et al, 2019)…”

Section: Muscle Fatiguementioning

confidence: 99%

Neuromechanical Biomarkers for Robotic Neurorehabilitation

et al. 2021

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One of the current challenges for translational rehabilitation research is to develop the strategies to deliver accurate evaluation, prediction, patient selection, and decision-making in the clinical practice. In this regard, the robot-assisted interventions have gained popularity as they can provide the objective and quantifiable assessment of the motor performance by taking the kinematics parameters into the account. Neurophysiological parameters have also been proposed for this purpose due to the novel advances in the non-invasive signal processing techniques. In addition, other parameters linked to the motor learning and brain plasticity occurring during the rehabilitation have been explored, looking for a more holistic rehabilitation approach. However, the majority of the research done in this area is still exploratory. These parameters have shown the capability to become the “biomarkers” that are defined as the quantifiable indicators of the physiological/pathological processes and the responses to the therapeutical interventions. In this view, they could be finally used for enhancing the robot-assisted treatments. While the research on the biomarkers has been growing in the last years, there is a current need for a better comprehension and quantification of the neuromechanical processes involved in the rehabilitation. In particular, there is a lack of operationalization of the potential neuromechanical biomarkers into the clinical algorithms. In this scenario, a new framework called the “Rehabilomics” has been proposed to account for the rehabilitation research that exploits the biomarkers in its design. This study provides an overview of the state-of-the-art of the biomarkers related to the robotic neurorehabilitation, focusing on the translational studies, and underlying the need to create the comprehensive approaches that have the potential to take the research on the biomarkers into the clinical practice. We then summarize some promising biomarkers that are being under investigation in the current literature and provide some examples of their current and/or potential applications in the neurorehabilitation. Finally, we outline the main challenges and future directions in the field, briefly discussing their potential evolution and prospective.

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Enhancing Virtual Rehabilitation in Upper Limbs With Biocybernetic Adaptation: The Effects of Virtual Reality on Perceived Muscle Fatigue, Game Performance and User Experience

Cited by 27 publications

References 24 publications

Clinical Effect of Virtual Reality Technology on Rehabilitation Training of Sports Injury

Clinical Effect of Virtual Reality Technology on Rehabilitation Training of Sports Injury

A Physics-based Virtual Reality System Design and Evaluation by Simulating Human-Robot Collaboration

Neuromechanical Biomarkers for Robotic Neurorehabilitation

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