Fun and games: a scoping review of enjoyment and intensity assessment in studies of game-based interventions for gait rehabilitation in neurological disorders

PURPOSE

Exergames are used to promote gait rehabilitation in patients with neurological disorders because they are believed to heighten patient enjoyment and training intensity. This scoping review evaluated whether and how studies support these claims.

METHODS

A search for studies published up until October 2023 involving virtual reality or exergames for patients with neurological disorders (stroke, Parkinson's disease, multiple sclerosis, spinal cord injury) was conducted on PubMed and Scopus, with additional articles identified through backward and forward citation searching. Studies collecting gait measurements, with at least five participants and a control group were included. Data extracted were rationale, and whether participants' enjoyment of the intervention and training intensity were assessed.

RESULTS

1060 records were identified with 58 included in this review. There were 34 articles on stroke, 11 on multiple sclerosis, and 13 on Parkinson's disease. Participant enjoyment and greater training intensity were important rationales but were only evaluated in 12 and seven of the included studies, respectively.

CONCLUSION

Results highlight that participant enjoyment and heightened training intensity are commonly cited rationales for using exergames in gait rehabilitation, but these effects are assumed and not routinely measured or analysed. Greater consistency is needed in the design and execution of exergaming studies for neurological disorders.

The Technology to Enhance Patient Motivation in Virtual Reality Rehabilitation: A Review

Virtual reality (VR) technology has experienced a steady rise and has been widely applied in the field of rehabilitation. The integration of VR technology in rehabilitation has shown promising results in enhancing their motivation for treatment, thereby enabling patients to actively engage in rehab training. Despite the advancement, there is a dearth of comprehensive summary and analysis on the use of VR technology to enhance patient motivation in rehabilitation. Thus, this narrative review aims to evaluate the potential of VR technology in enhancing patient motivation during motor rehabilitation training. This review commences with an explanation of how enhancing motivation through the VR rehabilitation system could improve the efficiency and effectiveness of rehabilitation training. Then, the technology was analyzed to improve patient motivation in the present VR rehabilitation system in detail. Furthermore, these technologies are classified and summarized to provide a comprehensive overview of the state-of-the-art approaches for enhancing patient motivation in VR rehabilitation. Findings showed VR rehabilitation training utilizes game-like exercises to enhance the engagement and enjoyment of rehabilitation training. By immersing patients in a simulated environment with multisensory feedback, VR systems offer a unique approach to rehabilitation that can lead to improved patient motivation. Both ultimately lead to improved patient outcomes, which is not typically achievable with traditional rehabilitation methods. The review concludes that VR rehabilitation presents an opportunity to improve patient motivation and adherence to long-term rehabilitation training. However, to further enhance patient self-efficacy, VR rehabilitation should integrate psychology and incorporate methods. Moreover, it is necessary to build a game design theory for rehabilitation games, and the latest VR feedback technology should also be introduced.

Evaluating the Usability and Safety of Virtual Reality Application Combined with the SWalker for Functional Gait Rehabilitation

Objective: This research evaluates from a usability point of view the combination of a developed fully immersive virtual reality (VR) solution with the SWalker robotic device. It aims to contribute to research in the exploration of immersive experiences overground with a functional gait recovery device. Materials and Methods: We evaluated the system in a pilot study with 20 healthy participants aged 85.1 (SD: 6.29). Participants used the SWalker-VR platform while testing one VR application focused on walking and the other on balance practice. Afterward, the participants answered three usability questionnaires. Results: The platform was validated in terms of safety using the Simulator Sickness Questionnaire, obtaining less than 20 points for all subscales: nausea (4.29 ± 14.47), oculomotor (0.38 ± 14.18), and disorientation (1.39 ± 14.52). For usability evaluation, the System Usability Scale provided an overall score of 70.63 ± 11.64, and the Post-Study System Usability Questionnaire (PSSUQ) rated 1.61 ± 0.54. The usability scores reported by both questionnaires were moderate and good, respectively. These results were similar in overall scores for both groups: participants with low cognitive level and participants with high cognitive level. Finally, the possible causes for the "no answered" responses on the PSSUQ were discussed. Conclusion: It is concluded that the SWalker-VR platform is reported to have adequate usability and high security by older adults. The potential interest of studying the effects of the long-term use of this platform by older adults with gait impairment is expressed. Clinical Trials reference: NCT06025981.

The advantages of artificial intelligence-based gait assessment in detecting, predicting, and managing Parkinson's disease

Background

Parkinson's disease is a neurological disorder that can cause gait disturbance, leading to mobility issues and falls. Early diagnosis and prediction of freeze episodes are essential for mitigating symptoms and monitoring the disease.

Objective

This review aims to evaluate the use of artificial intelligence (AI)-based gait evaluation in diagnosing and managing Parkinson's disease, and to explore the potential benefits of this technology for clinical decision-making and treatment support.

Methods

A thorough review of published literature was conducted to identify studies, articles, and research related to AI-based gait evaluation in Parkinson's disease.

Results

AI-based gait evaluation has shown promise in preventing freeze episodes, improving diagnosis, and increasing motor independence in patients with Parkinson's disease. Its advantages include higher diagnostic accuracy, continuous monitoring, and personalized therapeutic interventions.

Conclusion

AI-based gait evaluation systems hold great promise for managing Parkinson's disease and improving patient outcomes. They offer the potential to transform clinical decision-making and inform personalized therapies, but further research is needed to determine their effectiveness and refine their use.

Proprioceptive Focal Stimulation (Equistasi®) for gait and postural balance rehabilitation in patients with Parkinson's disease: A systematic review

Gait and postural deficits are the most common impairments in patients with Parkinson's Disease (PD). These impairments often reduce patients' quality of life. Equistasi^® is a wearable proprioceptive stabilizer that converts body thermic energy into mechanical vibration. No systematic reviews have been published investigating the influences of Equistasi^® on gait and postural control in patients with PD. This review aimed to examine the effects of proprioceptive focal stimulation (Equistasi^®) on gait deficits and postural instability in patients with PD. PubMed, Scopus, PEDro, REHABDATA, web of science, CHAINAL, EMBASE, and MEDLINE were searched from inception to July 2021. The methodological quality of the selected studies was evaluated using the Physiotherapy Evidence Database (PEDro) scale. Five studies met the eligibility criteria. The scores on the PEDro scale ranged from 3 to 8, with a median score of 8. The results showed evidence for the benefits of the proprioceptive focal stimulation (Equistasi^®) on gait and postural stability in individuals with PD. Proprioceptive focal stimulation (Equistasi^®) appears to be safe and well-tolerated in patients with PD. Proprioceptive focal stimulation (Equistasi^®) may improve gait ability and postural stability in patients with PD. Further high-quality studies with long-term follow-ups are strongly needed to clarify the long-term effects of proprioceptive focal stimulation (Equistasi^®) in patients with PD.

Robot-assisted gait training in patients with Parkinson's disease: Implications for clinical practice. A systematic review

BACKGROUND

Gait impairments are common disabling symptoms of Parkinson's disease (PD). Among the approaches for gait rehabilitation, interest in robotic devices has grown in recent years. However, the effectiveness compared to other interventions, the optimum amount of training, the type of device, and which patients might benefit most remains unclear.

OBJECTIVE

To conduct a systematic review about the effects on gait of robot-assisted gait training (RAGT) in PD patients and to provide advice for clinical practice.

METHODS

A search was performed on PubMed, Scopus, PEDro, Cochrane library, Web of science, and guideline databases, following PRISMA guidelines. We included English articles if they used a robotic system with details about the intervention, the parameters, and the outcome measures. We evaluated the level and quality of evidence.

RESULTS

We included twenty papers out of 230 results: two systematic reviews, 9 randomized controlled trials, 4 uncontrolled studies, and 5 descriptive reports. Nine studies used an exoskeleton device and the remainders end-effector robots, with large variability in terms of subjects' disease-related disability.

CONCLUSIONS

RAGT showed benefits on gait and no adverse events were recorded. However, it does not seem superior to other interventions, except in patients with more severe symptoms and advanced disease.

Integrating virtual reality and exergaming in cognitive rehabilitation of patients with Parkinson disease: a systematic review of randomized controlled trials

INTRODUCTION

In recent years, growing attention is rising to virtual reality (VR) tools and exergaming in rehabilitation management of patients with Parkinson disease (PD). However, no strong evidence supports the effectiveness of these cutting-edge technologies on cognitive function and the integration of these promising tool in the rehabilitation framework of PD patients is still challenging. Therefore, the present systematic review of randomized controlled trials (RCTs) aimed at assessing the effects of VR and exergames/telerehabilitation in the cognitive rehabilitation management of patients with PD.

EVIDENCE ACQUISITION

PubMed, Scopus and Web of Science databases were systematically searched up to February 14^th, 2022, to identify RCTs assessing patients with PD undergoing cognitive rehabilitation including VR or exergames/telerehabilitation. The intervention was compared to conventional rehabilitation protocols. The primary outcome was cognitive function. The quality assessment was performed following the Version 2 of the Cochrane risk-of-bias tool for randomized trials (RoB 2). PROSPERO registration code: CRD42022319788.

EVIDENCE SYNTHESIS

Out of 1419 identified studies, 66 articles were assessed for eligibility, and, at the end of the screening process, 10 studies were included in the present systematic review. Five RCTs (50%) assessed the exergaming devices, reporting significant positive results on cognitive outcomes scales (Trail Making test scale, Digit Span backward, MoCA, and MyCQ score). The other 5 RTCs (50%) assessed VR approaches, reporting significant improvement in executive functions. The RoB 2 showed an overall high risk of bias for the 40% of studies included.

CONCLUSIONS

Exergaming and VR might be considered promising rehabilitation interventions in the cognitive rehabilitation framework of PD patients. Further high-quality studies are needed to define the role of exergames and VR in a comprehensive rehabilitation approach aiming at improving the multilevel cognitive impairment characterizing patients with PD.

Effects of Non-Immersive Virtual Reality and Video Games on Walking Speed in Parkinson Disease: A Systematic Review and Meta-Analysis

People with Parkinson disease suffer from a loss of dopaminergic neurons, which are involved in walking speed. Currently, virtual reality (VR) has emerged as a useful tool for the rehabilitation of people with neurological diseases, optimizing results in balance and gait. This review aimed to evaluate the effectiveness of VR or video games (through face-to-face sessions and not telerehabilitation) in improving walking speed and other spatio-temporal parameters of gait, balance, and quality of life in patients with Parkinson disease. A bibliographic search was carried out in the MEDLINE, Web of Science, Scopus, and PEDro databases. This systematic review adhered to the PRISMA guideline statement and was registered in PROSPERO (CRD42020180836). From a total of 119 records, 5 studies met the inclusion criteria for qualitative analysis, of which 3 contributed to the meta-analysis; inconclusive findings were found on gait speed, balance, and quality of life after the use of non-immersive VR systems face-to-face. A greater number of studies are necessary, with a greater number of participants, to differentiate between those VR specific systems (specifically designed for rehabilitation) from commercial video games, including immersive systems, and obtain more conclusive evidence. Furthermore, it would be interesting to compare the administration of this treatment in person versus its administration via telerehabilitation, which will help plan treatment programs.

Settings matter: a scoping review on parameters in robot-assisted gait therapy identifies the importance of reporting standards

Background

Lokomat therapy for gait rehabilitation has become increasingly popular. Most evidence suggests that Lokomat therapy is equally effective as but not superior to standard therapy approaches. One reason might be that the Lokomat parameters to personalize therapy, such as gait speed, body weight support and Guidance Force, are not optimally used. However, there is little evidence available about the influence of Lokomat parameters on the effectiveness of the therapy. Nevertheless, an appropriate reporting of the applied therapy parameters is key to the successful clinical transfer of study results. The aim of this scoping review was therefore to evaluate how the currently available clinical studies report Lokomat parameter settings and map the current literature on Lokomat therapy parameters.

Methods and results

A systematic literature search was performed in three databases: Pubmed, Scopus and Embase. All primary research articles performing therapy with the Lokomat in neurologic populations in English or German were included. The quality of reporting of all clinical studies was assessed with a framework developed for this particular purpose. We identified 208 studies investigating Lokomat therapy in patients with neurologic diseases. The reporting quality was generally poor. Less than a third of the studies indicate which parameter settings have been applied. The usability of the reporting for a clinical transfer of promising results is therefore limited.

Conclusion

Although the currently available evidence on Lokomat parameters suggests that therapy parameters might have an influence on the effectiveness, there is currently not enough evidence available to provide detailed recommendations. Nevertheless, clinicians should pay close attention to the reported therapy parameters when translating research findings to their own clinical practice. To this end, we propose that the quality of reporting should be improved and we provide a reporting framework for authors as a quality control before submitting a Lokomat-related article.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12984-022-01017-3.

Artificial intelligence applications and robotic systems in Parkinson's disease (Review)

Parkinson's disease (PD) is the second most frequent neurodegenerative disorder following Alzheimer's disease. Advanced stages of PD, 4 or 5 of the Hoehn and Yahr Scale, are characterized by severe motor complications, limited mobility without assistance, risk of falling, and non-motor complications. The aim of this review was to provide a practical overview on specific artificial intelligence (AI) systems for the management of advanced stages of PD, as well as relevant technological limitations. The authors conducted a systematic search on PubMed and EMBASE with predefined keywords searching for studies published until December 2020. Full articles that satisfied the inclusion criteria were included in the systematic review. To minimize results bias, the reference list was manually searched for pertinent articles to identify any additional relevant missed publications. Exclusion criteria included the following: Other stages of PD than 4 and 5 of the Hoehn and Yahr Scale, case reports, reviews, practice guidelines, commentaries, opinions, letters, editorials, short surveys, articles in press, conference abstracts, conference papers, and abstracts published without a full article. The search identified 21 studies analyzing AI-based applications and robotic systems used for the management of advanced stages of PD, out of which 6 articles analyzed AI-based applications for autonomous management of pharmacologic therapy, 5 articles analyzed home-based telemedicine systems and 10 articles analysed robot-assisted gait training systems. The authors identified significant evidence demonstrating that current AI-based technologies are feasible for automatic management of patients with advanced stages of PD. Improving the quality of care and reducing the cost for patients and healthcare systems are the most important advantages.

New Recovery Strategies in Motor and Cognitive Functions, before, during and after Home-Confinement COVID-19, for Healthy Adults and Patients with Neurodegenerative Diseases: Review

Distancing and confinement at home during the Coronavirus Disease 2019 (COVID-19) outbreak has led to worsening of motor and cognitive functions, both for healthy adults and for patients with neurodegenerative diseases. The decrease in physical activity, the cessation of the intervention of the recovery and the social distance imposed by the lockdown, has had a negative impact on the physical and mental health, quality of life, daily activities, as well as on the behavioral attitudes of the diet. The purpose of this paper was to evaluate the impact of decreasing physical activity and the affected emotional status in healthy adults and patients with neurodegenerative diseases in conditions imposed by the stay at home mandate of COVID-19, along with new interventions, such as telemedicine and telerehabilitation. These interventions include online surveys carried out in multi-languages, semi-structured interviews, intervention smartphones and interventions through online platforms, for instance: Google, WhatsApp, Twitter, ResearchGate, Facebook and LinkedIn. For this study, we selected original papers that were intensively processed using characteristics co-related with physical activity, mental wellbeing, sleep quality, good eating behavior and healthy lifestyle. By searching the last two years of literature, our review presents and demonstrates the benefit of online technological interventions in lockdown, which promote physical exercise patterns and rehabilitation techniques, for healthy adults and patients with neurodegenerative diseases, and the need to develop new strategic directions and governmental measures, designed procedures and health services, which are expected to improve the quality of life, the progress of physical and cognitive functions, mental health and wellbeing for all.

Addressing virtual reality misclassification: A hardware-based qualification matrix for virtual reality technology

Through its unique sensory synchronized design, virtual reality (VR) provides a convincing, user-centred experience of highly controllable scenarios. Importantly, VR is a promising modality for healthcare, where treatment efficacy has been recognized for a range of conditions. It is equally valuable across wider research disciplines. However, there is a lack of suitable criteria and consistent terminology with which to define VR technology. A considerable number of studies have misclassified VR hardware (e.g. defining laptops as VR), hindering validity and research comparisons. This review addresses these limitations and establishes a standardized VR qualification framework. As a result of a comprehensive theoretical and literature review, the hardware-based VR qualification matrix is proposed. The matrix criteria consist of (1) three-dimensional (3D) synchronized sensory stimulation; (2) degrees of freedom tracking; and (3) visual suppression of physical stimuli. To validate the model and quantify the current scale/diversity of VR misclassification, a 2019 sectional review of health-related studies was conducted. Of the 115 studies examined against standardized criteria, 35.7% utilized VR, 31.3% misclassified VR, 18.3% were considered quasi-VR, and 14.8% omitted critical specifications. The proposed model demonstrates good validity and reliability for qualifying and classifying VR. Key Practitioner Messages Virtual reality (VR) therapy has gained rapid empirical support, although many practitioners do not understand the difference between genuine and less-realistic VR variations. That has resulted from an evident lack of suitable criteria to define VR across a range of studies and protocols. Our proposed hardware-based virtual reality qualification matrix addresses issues to do with misclassification, via the introduction of standardised criteria. Applying the matrix to existing literature has revealed that more than 30% of VR studies use hardware that does not fit the high standards of rigour required for immersion in a simulated space. The model is a practical tool researchers and practitioners can use to quality and verify VR standards across research studies.

Systemic Literature Review of the Use of Virtual Reality for Rehabilitation in Parkinson Disease

Background

Functional rehabilitation is important when managing Parkinson disease (PD). Virtual reality (VR) therapy is a noninvasive, potential alternative or adjunct to conventional therapies used during rehabilitation.

Observations

The authors searched for articles in Google Scholar, PubMed, Physiotherapy Evidence Database Score (PEDro), and Cochrane after setting specific requirements starting in July 2019. Methodologic quality was assessed by PEDro for randomized controlled trials. Among 89 studies identified, 28 included in this review evaluated VR therapy for use during rehabilitation for PD: 7 used immersive VR and 21 used nonimmersive VR. Among the immersive VR studies, 6 showed improvement in primary outcomes after adding VR therapy. Among the nonimmersive VR studies, 5 showed improvement with VR therapy when compared with conventional therapy, 9 showed improvement with VR and conventional therapy with no between group difference, and the remaining 7 showed improvement in primary outcomes after adding VR intervention. The quality and diversity of studies was a major limitation.

Conclusion

VR therapy is a promising rehabilitation modality for PD but more studies are needed. Additional investigations of VR therapy and PD should include direct comparisons between immersive and nonimmersive VR therapies.

Can google glass™ technology improve freezing of gait in parkinsonism? A pilot study

PURPOSE

Freezing of gait (FOG) is a disabling phenomenon defined by the periodic absence or reduction of forward progression of the feet despite the intention to walk. We sought to understand whether Google Glass (GG), a lightweight wearable device that provides simultaneous visual-auditory cues, might improve FOG in parkinsonism.

METHODS

Patients with parkinsonism and FOG utilized GG custom-made auditory-visual cue applications: "Walk With Me" and "Unfreeze Me" in a single session intervention. We recorded ambulation time with and without GG under multiple conditions including 25 feet straight walk, dual task of performing serial 7's while straight walking, 180 degree turn after walking 25 feet, and walking through a doorway. FOG and patient experience questionnaires were administered.

RESULTS

Using the GG "Walk With Me" program, improvements were noted in the following: average 25 feet straight walk by 0.32 s (SD 2.12); average dual task of serial 7's and 25 feet straight walk by 1.79 s (SD 2.91); and average walk through doorway by 0.59 s (SD 0.81). Average 180 degree turn after 25 feet walk worsened by 1.89 s (SD 10.66). Using the "Unfreeze Me" program, only the average dual task of serial 7's and 25 feet straight walk improved (better by 0.82 s (SD 3.08 sec). All other tasks had worse performance in terms of speed of completion.

CONCLUSION

This feasibility study provides preliminary data suggesting that some walking tasks may improve with GG, which uses various musical dance programs to provide visual and auditory cueing for patients with FOG.IMPLICATIONS FOR REHABILITATIONFreezing of gait in parkinsonian syndromes is a disabling motor block described by patients as having their feet stuck to the floor leading to difficulty in initiation of gait and increased risk for falls.Wearable assistive devices such as Google Glass™ use visual and auditory cueing that may improve gait pattern in patients with freezing of gait.Augmented reality programs using wearable assistive devices are a home-based therapy, with the potential for reinforcing physical therapy techniques; this is especially meaningful during the COVID-19 pandemic when access to both medical and rehabilitative care has been curtailed.

Functional Recovery in Parkinson's Disease: Current State and Future Perspective

Parkinson’s disease (PD) is one of the most frequent neurodegenerative disorders, affecting not only the motor function but also limiting the autonomy of affected people. In the last decade, the physical exercises of different intensities carried out by kinetic therapeutic activities, by robotic technologies or with the participation of sensory cues, have become increasingly appreciated in the management of Parkinson’s disease impairments. The aim of this paper was to evaluate the impact of physical exercises with and without physical devices on the motor and cognitive variables of PD patients. In order to achieve our objectives, we performed a systematic review of available original articles based on the impact of kinetic therapeutic activity. Through the search strategy, we selected original papers that were laboriously processed using characteristics related to physical therapy, or the tools used in physiological and psychological rehabilitation strategies for PD patients. In this study, we presented the most current intervention techniques in the rehabilitation programs of patients with Parkinson’s disease, namely the use of assisted devices, virtual imagery or the performing of physical therapies that have the capacity to improve walking deficits, tremor and bradykinesia, to reduce freezing episodes of gait and postural instability, or to improve motor and cognitive functions.

Detection of Participation and Training Task Difficulty Applied to the Multi-Sensor Systems of Rehabilitation Robots

In the process of rehabilitation training for stroke patients, the rehabilitation effect is positively affected by how much physical activity the patients take part in. Most of the signals used to measure the patients' participation are EMG signals or oxygen consumption, which increase the cost and the complexity of the robotic device. In this work, we design a multi-sensor system robot with torque and six-dimensional force sensors to gauge the patients' participation in training. By establishing the static equation of the mechanical leg, the man-machine interaction force of the patient can be accurately extracted. Using the impedance model, the auxiliary force training mode is established, and the difficulty of the target task is changed by adjusting the K value of auxiliary force. Participation models with three intensities were developed offline using support vector machines, for which the C and σ parameters are optimized by the hybrid quantum particle swarm optimization and support vector machines (Hybrid QPSO-SVM) algorithm. An experimental statistical analysis was conducted on ten volunteers' motion representation in different training tasks, which are divided into three stages: over-challenge, challenge, less challenge, by choosing characteristic quantities with significant differences among the various difficulty task stages, as a training set for the support vector machines (SVM). Experimental results from 12 volunteers, with tasks conducted on the lower limb rehabilitation robot LLR-II show that the rehabilitation robot can accurately predict patient participation and training task difficulty. The prediction accuracy reflects the superiority of the Hybrid QPSO-SVM algorithm.