The feasibility of using exergames as a rehabilitation tool: the attitudes, awareness, opinions and experiences of physiotherapists, and older people towards exergames

Tobaigy, Abdullah; Alshehri, Mansour Abdullah; Timmons, Suzanne; Helal, Omar Farouk

doi:10.1589/jpts.30.555

Cited by 25 publications

(17 citation statements)

References 31 publications

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“…Although significantly higher post-intervention flow state scores were found in the standard exercise group, there was no evidence to show absence of flow experience in exergaming. In exergaming programmes run by certain healthcare or rehabilitation centres, clients are supported by their physiotherapist in terms of setting suitable exergaming levels for them, monitoring and prescribing rehabilitative movements for them [ 132 , 133 ]. With this, another consideration is the potential advantage that after initial instruction, exergaming may require less supervision by physiotherapy staff and rely on continuous direct feedback to each patient.…”

Section: Discussionmentioning

confidence: 99%

The effects of exergaming on pain, postural control, technology acceptance and flow experience in older people with chronic musculoskeletal pain: a randomised controlled trial

Ditchburn

Schaik

Dixon

et al. 2020

BMC Sports Sci Med Rehabil

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Background Older people with chronic musculoskeletal pain are at risk of falls. This study aimed to investigate the effects of exergaming on pain and postural control in older people with chronic musculoskeletal pain. Secondary outcomes were technology acceptance, flow experience, perceived physical exertion, expended mental effort and heart rate. Methods Fifty four older adults (age: 71 ± 5 years) with chronic musculoskeletal pain were randomised into 2 groups. Group 1 received exergaming training using the Interactive Rehabilitation and Exercise System (IREX®). Group 2 undertook traditional gym-based exercise (TGB). Both groups completed twice weekly 40-min exercise sessions for 6 weeks. Perceived pain was measured using a numeric pain rating scale and the Multidimensional Affect and Pain Survey questionnaire. Postural control was measured as sway using a Kistler™ force platform. Technology acceptance was measured with the Unified Theory of Acceptance and Use of Technology questionnaire and flow experience with the Flow State Scale. Physiological measures of perceived physical exertion, expended mental effort and heart rate were recorded during all sessions. Results The exergaming group demonstrated significant reductions in pain intensity and thermal pain including a near significant approach in physical engagement in comparison to TGB group. Although no intervention effects on postural control were found, the exergaming group showed significant improvements in three sway measures (AP SD, ML SD and AP range) over time whereas significant improvements in ML range were found in the TGB group. Relating to technology acceptance, significant intervention effects on social influence and behavioural intention were found in the TGB group instead, although both groups demonstrated increases of acceptance over time. Regarding flow experience, concentration at task was significantly influenced in the TGB group and significant increases in flow variables over time were observed in both groups. Significant increases over time in perceived physical exertion and expended mental effort were found in both groups. Conclusion Our findings support the potential of exergaming to alleviate pain and improve balance in older people with chronic musculoskeletal pain. Both forms of exercise are acceptable, intrinsically motivating and show evidence of benefit to older people with chronic musculoskeletal pain. Trial registration ClinicalTrials.gov Identifier: NCT04029285 (retrospectively registered, July 23, 2019)

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Section: Discussionmentioning

confidence: 99%

The effects of exergaming on pain, postural control, technology acceptance and flow experience in older people with chronic musculoskeletal pain: a randomised controlled trial

Ditchburn

Schaik

Dixon

et al. 2020

BMC Sports Sci Med Rehabil

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“…However, a survey conducted in physiotherapists and elderly subjects showed that the former are aware of the functions and possible applications of exergames, but they do not think that they will have a relevant influence on traditional rehabilitation tools. Conversely, older people have no interest or even information on their function but could be willing to try them for rehabilitation purposes (15).…”

Section: Discussionmentioning

confidence: 99%

The Use of Social Media and Digital Devices Among Italian Neurologists

et al. 2020

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“…The impact of serious games on physical therapy has been studied in terms of effectiveness [ 4 - 6 ] and motivational determinants [ 7 , 8 ]. However, as a virtual guide replacing or complementing a real physician, exergaming systems tend to lack objective, clinically meaningful evaluation of patient performance.…”

Section: Introductionmentioning

confidence: 99%

Rehabilitation Exergames: Use of Motion Sensing and Machine Learning to Quantify Exercise Performance in Healthy Volunteers

Osgouei¹,

Soulsby²,

Bello³

2020

JMIR Rehabil Assist Technol

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Background Performing physiotherapy exercises in front of a physiotherapist yields qualitative assessment notes and immediate feedback. However, practicing the exercises at home lacks feedback on how well patients are performing the prescribed tasks. The absence of proper feedback might result in patients performing the exercises incorrectly, which could worsen their condition. We present an approach to generate performance scores to enable tracking the progress by both the patient at home and the physiotherapist in the clinic. Objective This study aims to propose the use of 2 machine learning algorithms, dynamic time warping (DTW) and hidden Markov model (HMM), to quantitatively assess the patient’s performance with respect to a reference. Methods Movement data were recorded using a motion sensor (Kinect V2), capable of detecting 25 joints in the human skeleton model, and were compared with those of a reference. A total of 16 participants were recruited to perform 4 different exercises: shoulder abduction, hip abduction, lunge, and sit-to-stand exercises. Their performance was compared with that of a physiotherapist as a reference. Results Both algorithms showed a similar trend in assessing participant performance. However, their sensitivity levels were different. Although DTW was more sensitive to small changes, HMM captured a general view of the performance, being less sensitive to the details. Conclusions The chosen algorithms demonstrated their capacity to objectively assess the performance of physical therapy. HMM may be more suitable in the early stages of a physiotherapy program to capture and report general performance, whereas DTW could be used later to focus on the details. The scores enable the patient to monitor their daily performance. They can also be reported back to the physiotherapist to track and assess patient progress, provide feedback, and adjust the exercise program if needed.

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The feasibility of using exergames as a rehabilitation tool: the attitudes, awareness, opinions and experiences of physiotherapists, and older people towards exergames

Cited by 25 publications

References 31 publications

The effects of exergaming on pain, postural control, technology acceptance and flow experience in older people with chronic musculoskeletal pain: a randomised controlled trial

The effects of exergaming on pain, postural control, technology acceptance and flow experience in older people with chronic musculoskeletal pain: a randomised controlled trial

The Use of Social Media and Digital Devices Among Italian Neurologists

Rehabilitation Exergames: Use of Motion Sensing and Machine Learning to Quantify Exercise Performance in Healthy Volunteers

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