Design of a VR-Based Upper Limb Gross Motor and Fine Motor Task Platform for Post-Stroke Survivors

Kumar, Sunil; Dash, Adyasha; Solanki, Dhaval; Lahiri, Uttama

doi:10.1109/icis.2018.8466538

Cited by 13 publications

(5 citation statements)

References 16 publications

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“…In contrast to the baseline 2U1D progression algorithm, we investigated the role of responsiveness by developing a second algorithm that uses a One-Up/One-Down (1U1D) variant which requires only a single, rather than double, excellent performance to increase subtask difficulty. Both forms of the staircase have been used in prior work, with 2U1D being employed for rehabilitation training in virtual environments, and its 1U1D counterpart being used de facto for neurorehabilitation, balance and gait training, and training of fine motor movements (Cameirão et al, 2010;Grimm et al, 2016;Gray, 2017;Kumar et al, 2018;Saurav et al, 2018). By comparing the outcomes on skill acquisition, transfer, and performance outcomes of 2U1D versus 1U1D, we were able to isolate the effect of heightened sensitivity and responsiveness to subject performance.…”

Section: Automated Training Algorithmsmentioning

confidence: 99%

Features of adaptive training algorithms for improved complex skill acquisition

Verniani,

Galvin,

Tredinnick

et al. 2024

Front. Virtual Real.

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Training complex skills is typically accomplished by means of a trainer or mediator who tailors instruction to the individual trainee. However, facilitated training is costly and labor intensive, and the use of a mediator is infeasible in remote or extreme environments. Imparting complex skills in applications like long-duration human spaceflight, military field operations, or remote medicine may require automated training algorithms. Virtual reality (VR) is an effective, easily programmable, immersive training medium that has been used widely across fields. However, there remain open questions in the search for the most effective algorithms for guiding automated training progression. This study investigates the effects of responsiveness, personalization, and subtask independence on the efficacy of automated training algorithms in VR for training complex, operationally relevant tasks. Thirty-two subjects (16M/16F, 18–54 years) were trained to pilot and land a spacecraft on Mars within a VR simulation using four different automated training algorithms. Performance was assessed in a physical cockpit mock-up. We found that personalization results in faster skill acquisition on average when compared with a standardized progression built for a median subject (p = 0.0050). The standardized progression may be preferable when consistent results are desired across all subjects. Independence of the difficulty adjustments between subtasks may lead to increased skill acquisition, while lockstep in the progression of each subtask increases self-reported flow experience (p = 0.01), fluency (p = 0.02), and absorption (p = 0.01) on the Flow Short Scale. Data visualization suggests that highly responsive algorithms may lead to faster learning progressions and higher skill acquisition for some subjects. Improving transfer of skills from training to testing may require either high responsiveness or a standardized training progression. Optimizing the design of automated, individually adaptive algorithms around the training needs of a group may be useful to increase skill acquisition for complex operational tasks.

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Section: Automated Training Algorithmsmentioning

confidence: 99%

Features of adaptive training algorithms for improved complex skill acquisition

Verniani,

Galvin,

Tredinnick

et al. 2024

Front. Virtual Real.

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“…Adaptive logic works by using methods such as rulebased procedures and classification algorithms to evaluate user performance measures and uses the result to adjust the parameters of a scenario appropriately (Lahiri et al, 2012;Saurav et al, 2018 ). Common classification algorithms used for this purpose make use of machine learning algorithms, such as random forests, Bayesian networks and neural networks (Zahabi & Abdul Razak, 2020).…”

Section: Adaptive Logicmentioning

confidence: 99%

An Adaptive Virtual Reality-Based Training System for Pilots

Reyes

Wozniak

Ham

et al. 2022

Proceedings of the Human Factors and Ergonomics Society Annual

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The successful operation of military aviation depends on effective pilot training. Current training capabilities of the United States Air Force might not be sufficient to meet the demand for new pilots. To help resolve this issue, this implementation study focused on developing an adaptive virtual reality (VR)-based training system for pilots. This prototype was built leveraging the three fundamental components for an adaptive training system including the trainee’s performance measures, adaptive logic, and adaptive variables. The prototype was based on the startup procedure for an F-16 cockpit and included adaptive feedback, display features, and various difficulty levels to help trainees maintain an optimal level of cognitive workload while completing their training. Implementation of adaptive VR training on a wide scale has the potential to reduce training time and cost. Future work is needed to validate the effectiveness of the approach. This prototype can assist in developing future adaptive VR-training systems.

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“…Várias pesquisas que demonstram o desenvolvimento de jogos sérios específicos para o tratamento de pacientes pós-AVC, testam sua aplicabilidade apenas em testespiloto [18], [19], [21], [22], dificultando o reconhecimento da real contribuição da terapia. Neste sentido, para ter sucesso com esta técnica, é necessário cumprir alguns pré-requisitos.…”

Section: Elaboração Da Terapia E Da Proposta Metodológicaunclassified

“…Assim, esta pesquisa cumpriu todos os pré-requisitos para uma aplicação bemsucedida de um jogo sério: [18], [23], [25], [68], [69], [83], [88]. Poucos trabalhos avaliam a ADM [21], [23], [72].…”

Section: Elaboração Da Terapia E Da Proposta Metodológicaunclassified

“…Mesmo a espasticidade sendo uma das sequelas que mais inabilitam a performance do MS[10],[35]-[37], ela foi medida somente em um dos trabalhos encontrados[88]. Como medidas de avaliação encontramos uma prevalência de escalas, como a Escala de Fulg-Meyer[18],[23],[25],[68],[69],[83],[88], a ADM foi mensurada em dois trabalhos[21],[23], medidas relacionadas à QV foram vistas somente em um trabalho[25]. Por ser um ramo relativamente novo, pôde-se observar ainda uma escassez de trabalhos que foram além de testes pilotos.…”

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Jogo sério e realidade virtual na reabilitação do AVC crônico: protocolo individualizado

Marques¹

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Stroke is the leading cause of disability in the world. Many individuals remain without upper limb (MS) function even six months after stroke. The function of MS directly affects the performance of activities of daily living, negatively affecting the quality of life (QOL) of these patients. Several researchers report the difficulty of restoring the motor function of paretic MS. Considering the above aspects, a new rehabilitation protocol was developed, applied and evaluated involving a user-centered serious virtual reality-based (VR) game in non-invasive and post-chronic chronic individuals. A total of 10 individuals with stroke sequelae who underwent 15 rehabilitation sessions, lasting between 30 and 40 minutes each, participated in the research. The quantitative parameters evaluated were: Modified Ashworth Scale (MAS), Tonic Stretch Reflex Threshold (TSRT), Brunnstrom Recovery Stages (BRS), Range of Motion (ROM), and Stroke-Specific Quality of Life Scale), and qualitative analysis made through a collection diary. For analysis of quantitative data we used the software R. The Shapiro-Wilk test was initially applied to identify if the samples had normal distribution. For data with normal distribution (ROM) the T test was used, and for non-normal data (LRET, EMA, BRS, QOL), the nonparametric Wilcoxon-Mann-Whitney test was used, both comparing pre and post evaluation. treatment. The results of the parameters measured for LRET, BRS, ADM and QL evaluation showed statistically significant differences between pre and post intervention evaluations, with 99% confidence. In this intervention it was observed, in general, that the offered protocol was able to reach the goal, since the results presented indicated that there was a decrease in muscle tone, increased range of motion and improved quality of life, besides , this intervention showed no adverse effect, was very motivating given the level of adherence of the participants and allowed a specific training for the upper limbs of these individuals.

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Design of a VR-Based Upper Limb Gross Motor and Fine Motor Task Platform for Post-Stroke Survivors

Cited by 13 publications

References 16 publications

Features of adaptive training algorithms for improved complex skill acquisition

Features of adaptive training algorithms for improved complex skill acquisition

An Adaptive Virtual Reality-Based Training System for Pilots

Jogo sério e realidade virtual na reabilitação do AVC crônico: protocolo individualizado

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