Inertial-Based Human Motion Capture: A Technical Summary of Current Processing Methodologies for Spatiotemporal and Kinematic Measures
Inertial-based motion capture (IMC) has been suggested to overcome many of the limitations of traditional motion capture systems. The validity of IMC is, however, suggested to be dependent on the methodologies used to process the raw data collected by the inertial device. The aim of this technical s...
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| Language: | English |
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Wiley
2021-01-01
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| Series: | Applied Bionics and Biomechanics |
| Online Access: | http://dx.doi.org/10.1155/2021/6628320 |
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| author | Benjamin R. Hindle Justin W. L. Keogh Anna V. Lorimer |
| author_facet | Benjamin R. Hindle Justin W. L. Keogh Anna V. Lorimer |
| author_sort | Benjamin R. Hindle |
| collection | DOAJ |
| description | Inertial-based motion capture (IMC) has been suggested to overcome many of the limitations of traditional motion capture systems. The validity of IMC is, however, suggested to be dependent on the methodologies used to process the raw data collected by the inertial device. The aim of this technical summary is to provide researchers and developers with a starting point from which to further develop the current IMC data processing methodologies used to estimate human spatiotemporal and kinematic measures. The main workflow pertaining to the estimation of spatiotemporal and kinematic measures was presented, and a general overview of previous methodologies used for each stage of data processing was provided. For the estimation of spatiotemporal measures, which includes stride length, stride rate, and stance/swing duration, measurement thresholding and zero-velocity update approaches were discussed as the most common methodologies used to estimate such measures. The methodologies used for the estimation of joint kinematics were found to be broad, with the combination of Kalman filtering or complimentary filtering and various sensor to segment alignment techniques including anatomical alignment, static calibration, and functional calibration methods identified as being most common. The effect of soft tissue artefacts, device placement, biomechanical modelling methods, and ferromagnetic interference within the environment, on the accuracy and validity of IMC, was also discussed. Where a range of methods have previously been used to estimate human spatiotemporal and kinematic measures, further development is required to reduce estimation errors, improve the validity of spatiotemporal and kinematic estimations, and standardize data processing practices. It is anticipated that this technical summary will reduce the time researchers and developers require to establish the fundamental methodological components of IMC prior to commencing further development of IMC methodologies, thus increasing the rate of development and utilisation of IMC. |
| format | Article |
| id | doaj-art-5a023ec9d3f7489b8458c2d798ccc0bf |
| institution | OA Journals |
| issn | 1176-2322 1754-2103 |
| language | English |
| publishDate | 2021-01-01 |
| publisher | Wiley |
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| series | Applied Bionics and Biomechanics |
| spelling | doaj-art-5a023ec9d3f7489b8458c2d798ccc0bf2025-08-20T02:05:29ZengWileyApplied Bionics and Biomechanics1176-23221754-21032021-01-01202110.1155/2021/66283206628320Inertial-Based Human Motion Capture: A Technical Summary of Current Processing Methodologies for Spatiotemporal and Kinematic MeasuresBenjamin R. Hindle0Justin W. L. Keogh1Anna V. Lorimer2Faculty of Health Sciences and Medicine, Bond University, Gold Coast 4226, AustraliaFaculty of Health Sciences and Medicine, Bond University, Gold Coast 4226, AustraliaFaculty of Health Sciences and Medicine, Bond University, Gold Coast 4226, AustraliaInertial-based motion capture (IMC) has been suggested to overcome many of the limitations of traditional motion capture systems. The validity of IMC is, however, suggested to be dependent on the methodologies used to process the raw data collected by the inertial device. The aim of this technical summary is to provide researchers and developers with a starting point from which to further develop the current IMC data processing methodologies used to estimate human spatiotemporal and kinematic measures. The main workflow pertaining to the estimation of spatiotemporal and kinematic measures was presented, and a general overview of previous methodologies used for each stage of data processing was provided. For the estimation of spatiotemporal measures, which includes stride length, stride rate, and stance/swing duration, measurement thresholding and zero-velocity update approaches were discussed as the most common methodologies used to estimate such measures. The methodologies used for the estimation of joint kinematics were found to be broad, with the combination of Kalman filtering or complimentary filtering and various sensor to segment alignment techniques including anatomical alignment, static calibration, and functional calibration methods identified as being most common. The effect of soft tissue artefacts, device placement, biomechanical modelling methods, and ferromagnetic interference within the environment, on the accuracy and validity of IMC, was also discussed. Where a range of methods have previously been used to estimate human spatiotemporal and kinematic measures, further development is required to reduce estimation errors, improve the validity of spatiotemporal and kinematic estimations, and standardize data processing practices. It is anticipated that this technical summary will reduce the time researchers and developers require to establish the fundamental methodological components of IMC prior to commencing further development of IMC methodologies, thus increasing the rate of development and utilisation of IMC.http://dx.doi.org/10.1155/2021/6628320 |
| spellingShingle | Benjamin R. Hindle Justin W. L. Keogh Anna V. Lorimer Inertial-Based Human Motion Capture: A Technical Summary of Current Processing Methodologies for Spatiotemporal and Kinematic Measures Applied Bionics and Biomechanics |
| title | Inertial-Based Human Motion Capture: A Technical Summary of Current Processing Methodologies for Spatiotemporal and Kinematic Measures |
| title_full | Inertial-Based Human Motion Capture: A Technical Summary of Current Processing Methodologies for Spatiotemporal and Kinematic Measures |
| title_fullStr | Inertial-Based Human Motion Capture: A Technical Summary of Current Processing Methodologies for Spatiotemporal and Kinematic Measures |
| title_full_unstemmed | Inertial-Based Human Motion Capture: A Technical Summary of Current Processing Methodologies for Spatiotemporal and Kinematic Measures |
| title_short | Inertial-Based Human Motion Capture: A Technical Summary of Current Processing Methodologies for Spatiotemporal and Kinematic Measures |
| title_sort | inertial based human motion capture a technical summary of current processing methodologies for spatiotemporal and kinematic measures |
| url | http://dx.doi.org/10.1155/2021/6628320 |
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