Effects of virtual reality-based telerehabilitation for stroke patients: A systematic review and meta-analysis of randomized controlled trials

Hao, Jie; Pu, Yuqi; Chen, Zhe; Siu, Ka-Chun

doi:10.1016/j.jstrokecerebrovasdis.2022.106960

Cited by 33 publications

(41 citation statements)

References 47 publications

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“…In light of these considerations, the stimulation of cognitive function during the COVID-19 health emergency has allowed therapists to exploit the potential of TR, with remote treatments to improve cognitive performance, regardless of the diagnosis, the specific cognitive profile, and participants and the age of the patient (adult or elderly) ( 112 ). This has made it possible to stimulate alternative activities that involve and motivate patients, promoting a better quality of life ( 113 ). People could stay at home, improving their cognitive performance without exposing themselves to the risk of infection ( 2 ).…”

Section: Discussion and Future Perspectivementioning

confidence: 99%

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Cognitive telerehabilitation: an expert consensus paper on current evidence and future perspective

Maggio,

Baglio,

Arcuri

et al. 2024

Front. Neurol.

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The progressive improvement of the living conditions and medical care of the population in industrialized countries has led to improvement in healthcare interventions, including rehabilitation. From this perspective, Telerehabilitation (TR) plays an important role. TR consists of the application of telemedicine to rehabilitation to offer remote rehabilitation services to the population unable to reach healthcare. TR integrates therapy-recovery-assistance, with continuity of treatments, aimed at neurological and psychological recovery, involving the patient in a family environment, with an active role also of the caregivers. This leads to reduced healthcare costs and improves the continuity of specialist care, as well as showing efficacy for the treatment of cognitive disorders, and leading to advantages for patients and their families, such as avoiding travel, reducing associated costs, improving the frequency, continuity, and comfort of performing the rehabilitation in its own spaces, times and arrangements. The aim of this consensus paper is to investigate the current evidence on the use and effectiveness of TR in the cognitive field, trying to also suggest some recommendations and future perspectives. To the best of our knowledge, this is the first consensus paper among multiple expert researchers that comprehensively examines TR in different neurological diseases. Our results supported the efficacy and feasibility of TR with good adherence and no adverse events among patients. Our consensus summarizes the current evidence for the application of cognitive TR in neurological populations, highlighting the potential of this tool, but also the limitations that need to be explored further.

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Section: Discussion and Future Perspectivementioning

confidence: 99%

“…People could stay at home, improving their cognitive performance without exposing themselves to the risk of infection ( 2 ). Indeed, in neurological patients, to implement continuity in rehabilitation care is essential to maintain and encourage functional recovery and an adequate daily life ( 66 , 113 ).…”

Section: Discussion and Future Perspectivementioning

confidence: 99%

Cognitive telerehabilitation: an expert consensus paper on current evidence and future perspective

Maggio,

Baglio,

Arcuri

et al. 2024

Front. Neurol.

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“…Virtual reality (VR) has been another significant advancement. Laver et al’s study [ 33 ] showed that VR could be effectively employed in telerehabilitation settings, particularly for stroke rehabilitation. Patients using VR systems showed improved physical activity compared to those who underwent conventional therapy.…”

Section: Literature Reviewmentioning

confidence: 99%

Telehealth-Enabled In-Home Elbow Rehabilitation for Brachial Plexus Injuries Using Deep-Reinforcement-Learning-Assisted Telepresence Robots

Khan,

Altalbe,

Naseer

et al. 2024

Sensors

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Due to damage to the network of nerves that regulate the muscles and feeling in the shoulder, arm, and forearm, brachial plexus injuries (BPIs) are known to significantly reduce the function and quality of life of affected persons. According to the World Health Organization (WHO), a considerable share of global disability-adjusted life years (DALYs) is attributable to upper limb injuries, including BPIs. Telehealth can improve access concerns for patients with BPIs, particularly in lower-middle-income nations. This study used deep reinforcement learning (DRL)-assisted telepresence robots, specifically the deep deterministic policy gradient (DDPG) algorithm, to provide in-home elbow rehabilitation with elbow flexion exercises for BPI patients. The telepresence robots were used for a six-month deployment period, and DDPG drove the DRL architecture to maximize patient-centric exercises with its robotic arm. Compared to conventional rehabilitation techniques, patients demonstrated an average increase of 4.7% in force exertion and a 5.2% improvement in range of motion (ROM) with the assistance of the telepresence robot arm. According to the findings of this study, telepresence robots are a valuable and practical method for BPI patients’ at-home rehabilitation. This technology paves the way for further research and development in telerehabilitation and can be crucial in addressing broader physical rehabilitation challenges.

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“…Several recent reviews have been conducted on the applications of AI in the rehabilitation of different populations 8 , 10 , 18 , 19 , 44 – 46 as well as VRehab or telerehabilitation 9 , 47 – 50 . None of the published literature has addressed the combined role of AI and VRehab to support patient recovery in various rehabilitation populations.…”

Section: Introductionmentioning

confidence: 99%

Artificial intelligence-driven virtual rehabilitation for people living in the community: A scoping review

Abedi,

Colella,

Pakosh

et al. 2024

npj Digit. Med.

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Virtual Rehabilitation (VRehab) is a promising approach to improving the physical and mental functioning of patients living in the community. The use of VRehab technology results in the generation of multi-modal datasets collected through various devices. This presents opportunities for the development of Artificial Intelligence (AI) techniques in VRehab, namely the measurement, detection, and prediction of various patients’ health outcomes. The objective of this scoping review was to explore the applications and effectiveness of incorporating AI into home-based VRehab programs. PubMed/MEDLINE, Embase, IEEE Xplore, Web of Science databases, and Google Scholar were searched from inception until June 2023 for studies that applied AI for the delivery of VRehab programs to the homes of adult patients. After screening 2172 unique titles and abstracts and 51 full-text studies, 13 studies were included in the review. A variety of AI algorithms were applied to analyze data collected from various sensors and make inferences about patients’ health outcomes, most involving evaluating patients’ exercise quality and providing feedback to patients. The AI algorithms used in the studies were mostly fuzzy rule-based methods, template matching, and deep neural networks. Despite the growing body of literature on the use of AI in VRehab, very few studies have examined its use in patients’ homes. Current research suggests that integrating AI with home-based VRehab can lead to improved rehabilitation outcomes for patients. However, further research is required to fully assess the effectiveness of various forms of AI-driven home-based VRehab, taking into account its unique challenges and using standardized metrics.

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Effects of virtual reality-based telerehabilitation for stroke patients: A systematic review and meta-analysis of randomized controlled trials

Cited by 33 publications

References 47 publications

Cognitive telerehabilitation: an expert consensus paper on current evidence and future perspective

Cognitive telerehabilitation: an expert consensus paper on current evidence and future perspective

Telehealth-Enabled In-Home Elbow Rehabilitation for Brachial Plexus Injuries Using Deep-Reinforcement-Learning-Assisted Telepresence Robots

Artificial intelligence-driven virtual rehabilitation for people living in the community: A scoping review

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