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Kinect and wearable inertial sensors for motor rehabilitation programs at home: state of the art and an experimental comparison.

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Τίτλος: Kinect and wearable inertial sensors for motor rehabilitation programs at home: state of the art and an experimental comparison.
Συγγραφείς: Milosevic, Bojan, Leardini, Alberto, Farella, Elisabetta
Πηγή: BioMedical Engineering OnLine; 4/23/2020, Vol. 19 Issue 1, p1-26, 26p
Θεματικοί όροι: Treatment programs, Motion analysis, Health facilities, Motion capture (Human mechanics), Motion detectors, Telecommunication, Stereo vision (Computer science)
Περίληψη: Background: Emerging sensing and communication technologies are contributing to the development of many motor rehabilitation programs outside the standard healthcare facilities. Nowadays, motor rehabilitation exercises can be easily performed and monitored even at home by a variety of motion-tracking systems. These are cheap, reliable, easy-to-use, and allow also remote configuration and control of the rehabilitation programs. The two most promising technologies for home-based motor rehabilitation programs are inertial wearable sensors and video-based motion capture systems.Methods: In this paper, after a thorough review of the relevant literature, an original experimental analysis is reported for two corresponding commercially available solutions, a wearable inertial measurement unit and the Kinect, respectively. For the former, a number of different algorithms for rigid body pose estimation from sensor data were also tested. Both systems were compared with the measurements obtained with state-of-the-art marker-based stereophotogrammetric motion analysis, taken as a gold-standard, and also evaluated outside the lab in a home environment.Results: The results in the laboratory setting showed similarly good performance for the elementary large motion exercises, with both systems having errors in the 3-8 degree range. Usability and other possible limitations were also assessed during utilization at home, which revealed additional advantages and drawbacks for the two systems.Conclusions: The two evaluated systems use different technology and algorithms, but have similar performance in terms of human motion tracking. Therefore, both can be adopted for monitoring home-based rehabilitation programs, taking adequate precautions however for operation, user instructions and interpretation of the results. [ABSTRACT FROM AUTHOR]
Copyright of BioMedical Engineering OnLine is the property of BioMed Central and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: Kinect and wearable inertial sensors for motor rehabilitation programs at home: state of the art and an experimental comparison.
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  Data: <searchLink fieldCode="AR" term="%22Milosevic%2C+Bojan%22">Milosevic, Bojan</searchLink><br /><searchLink fieldCode="AR" term="%22Leardini%2C+Alberto%22">Leardini, Alberto</searchLink><br /><searchLink fieldCode="AR" term="%22Farella%2C+Elisabetta%22">Farella, Elisabetta</searchLink>
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  Data: BioMedical Engineering OnLine; 4/23/2020, Vol. 19 Issue 1, p1-26, 26p
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  Data: <searchLink fieldCode="DE" term="%22Treatment+programs%22">Treatment programs</searchLink><br /><searchLink fieldCode="DE" term="%22Motion+analysis%22">Motion analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Health+facilities%22">Health facilities</searchLink><br /><searchLink fieldCode="DE" term="%22Motion+capture+%28Human+mechanics%29%22">Motion capture (Human mechanics)</searchLink><br /><searchLink fieldCode="DE" term="%22Motion+detectors%22">Motion detectors</searchLink><br /><searchLink fieldCode="DE" term="%22Telecommunication%22">Telecommunication</searchLink><br /><searchLink fieldCode="DE" term="%22Stereo+vision+%28Computer+science%29%22">Stereo vision (Computer science)</searchLink>
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  Label: Abstract
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  Data: <bold>Background: </bold>Emerging sensing and communication technologies are contributing to the development of many motor rehabilitation programs outside the standard healthcare facilities. Nowadays, motor rehabilitation exercises can be easily performed and monitored even at home by a variety of motion-tracking systems. These are cheap, reliable, easy-to-use, and allow also remote configuration and control of the rehabilitation programs. The two most promising technologies for home-based motor rehabilitation programs are inertial wearable sensors and video-based motion capture systems.<bold>Methods: </bold>In this paper, after a thorough review of the relevant literature, an original experimental analysis is reported for two corresponding commercially available solutions, a wearable inertial measurement unit and the Kinect, respectively. For the former, a number of different algorithms for rigid body pose estimation from sensor data were also tested. Both systems were compared with the measurements obtained with state-of-the-art marker-based stereophotogrammetric motion analysis, taken as a gold-standard, and also evaluated outside the lab in a home environment.<bold>Results: </bold>The results in the laboratory setting showed similarly good performance for the elementary large motion exercises, with both systems having errors in the 3-8 degree range. Usability and other possible limitations were also assessed during utilization at home, which revealed additional advantages and drawbacks for the two systems.<bold>Conclusions: </bold>The two evaluated systems use different technology and algorithms, but have similar performance in terms of human motion tracking. Therefore, both can be adopted for monitoring home-based rehabilitation programs, taking adequate precautions however for operation, user instructions and interpretation of the results. [ABSTRACT FROM AUTHOR]
– Name: Abstract
  Label:
  Group: Ab
  Data: <i>Copyright of BioMedical Engineering OnLine is the property of BioMed Central and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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              Text: 4/23/2020
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