Assessment of robotic patient simulators for training in manual physical therapy examination techniques.
Robots that simulate patients suffering from joint resistance caused by biomechanical and neural impairments are used to aid the training of physical therapists in manual examination techniques. However, there are few methods for assessing such robots. This article proposes two types of assessment m...
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2015-01-01
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Series: | PLoS ONE |
Online Access: | https://doi.org/10.1371/journal.pone.0126392 |
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doaj-b3103ca97ab3436d86ef379fd30e78742021-03-03T20:05:33ZengPublic Library of Science (PLoS)PLoS ONE1932-62032015-01-01104e012639210.1371/journal.pone.0126392Assessment of robotic patient simulators for training in manual physical therapy examination techniques.Shun IshikawaShogo OkamotoKaoru IsogaiYasuhiro AkiyamaNaomi YanagiharaYoji YamadaRobots that simulate patients suffering from joint resistance caused by biomechanical and neural impairments are used to aid the training of physical therapists in manual examination techniques. However, there are few methods for assessing such robots. This article proposes two types of assessment measures based on typical judgments of clinicians. One of the measures involves the evaluation of how well the simulator presents different severities of a specified disease. Experienced clinicians were requested to rate the simulated symptoms in terms of severity, and the consistency of their ratings was used as a performance measure. The other measure involves the evaluation of how well the simulator presents different types of symptoms. In this case, the clinicians were requested to classify the simulated resistances in terms of symptom type, and the average ratios of their answers were used as performance measures. For both types of assessment measures, a higher index implied higher agreement among the experienced clinicians that subjectively assessed the symptoms based on typical symptom features. We applied these two assessment methods to a patient knee robot and achieved positive appraisals. The assessment measures have potential for use in comparing several patient simulators for training physical therapists, rather than as absolute indices for developing a standard.https://doi.org/10.1371/journal.pone.0126392 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Shun Ishikawa Shogo Okamoto Kaoru Isogai Yasuhiro Akiyama Naomi Yanagihara Yoji Yamada |
spellingShingle |
Shun Ishikawa Shogo Okamoto Kaoru Isogai Yasuhiro Akiyama Naomi Yanagihara Yoji Yamada Assessment of robotic patient simulators for training in manual physical therapy examination techniques. PLoS ONE |
author_facet |
Shun Ishikawa Shogo Okamoto Kaoru Isogai Yasuhiro Akiyama Naomi Yanagihara Yoji Yamada |
author_sort |
Shun Ishikawa |
title |
Assessment of robotic patient simulators for training in manual physical therapy examination techniques. |
title_short |
Assessment of robotic patient simulators for training in manual physical therapy examination techniques. |
title_full |
Assessment of robotic patient simulators for training in manual physical therapy examination techniques. |
title_fullStr |
Assessment of robotic patient simulators for training in manual physical therapy examination techniques. |
title_full_unstemmed |
Assessment of robotic patient simulators for training in manual physical therapy examination techniques. |
title_sort |
assessment of robotic patient simulators for training in manual physical therapy examination techniques. |
publisher |
Public Library of Science (PLoS) |
series |
PLoS ONE |
issn |
1932-6203 |
publishDate |
2015-01-01 |
description |
Robots that simulate patients suffering from joint resistance caused by biomechanical and neural impairments are used to aid the training of physical therapists in manual examination techniques. However, there are few methods for assessing such robots. This article proposes two types of assessment measures based on typical judgments of clinicians. One of the measures involves the evaluation of how well the simulator presents different severities of a specified disease. Experienced clinicians were requested to rate the simulated symptoms in terms of severity, and the consistency of their ratings was used as a performance measure. The other measure involves the evaluation of how well the simulator presents different types of symptoms. In this case, the clinicians were requested to classify the simulated resistances in terms of symptom type, and the average ratios of their answers were used as performance measures. For both types of assessment measures, a higher index implied higher agreement among the experienced clinicians that subjectively assessed the symptoms based on typical symptom features. We applied these two assessment methods to a patient knee robot and achieved positive appraisals. The assessment measures have potential for use in comparing several patient simulators for training physical therapists, rather than as absolute indices for developing a standard. |
url |
https://doi.org/10.1371/journal.pone.0126392 |
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