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      Verification of gait analysis method fusing camera-based pose estimation and an IMU sensor in various gait conditions

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          Abstract

          A markerless gait analysis system can measure useful gait metrics to determine effective clinical treatment. Although this gait analysis system does not require a large space, several markers, or time constraints, it inaccurately measure lower limb joint kinematics during gait. In particular, it has a substantial ankle joint angle error. In this study, we investigated the markerless gait analysis method capability using single RGB camera-based pose estimation by OpenPose (OP) and an inertial measurement unit (IMU) sensor on the foot segment to measure ankle joint kinematics under various gait conditions. Sixteen healthy young adult males participated in the study. We compared temporo-spatial parameters and lower limb joint angles during four gait conditions with varying gait speeds and foot progression angles. These were measured by optoelectronic motion capture, markerless gait analysis method using OP, and proposed method using OP and IMU. We found that the proposed method using OP and an IMU significantly decreased the mean absolute errors of peak ankle joint angles compared with OP in the four gait conditions. The proposed method has the potential to measure temporo-spatial gait parameters and lower limb joint angles, including ankle angles, in various gait conditions as a clinical settings gait assessment tool.

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          Two simple methods for determining gait events during treadmill and overground walking using kinematic data.

          J Zeni, J Richards, J Higginson (2008)
          The determination of gait events such as heel strike and toe-off provide the basis for defining stance and swing phases of gait cycles. Two algorithms for determining event times for treadmill and overground walking based solely on kinematic data are presented. Kinematic data from treadmill walking trials lasting 20-45s were collected from three subject populations (healthy young, n=7; multiple sclerosis, n=7; stroke, n=4). Overground walking trials consisted of approximately eight successful passes over two force plates for a healthy subject population (n=5). Time of heel strike and toe-off were determined using the two new computational techniques and compared to events detected using vertical ground reaction force (GRF) as a gold standard. The two algorithms determined 94% of the treadmill events from healthy subjects within one frame (0.0167s) of the GRF events. In the impaired populations, 89% of treadmill events were within two frames (0.0334s) of the GRF events. For overground trials, 98% of events were within two frames. Automatic event detection from the two kinematic-based algorithms will aid researchers by accurately determining gait events during the analysis of treadmill and overground walking.
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            Improvements in speed-based gait classifications are meaningful.

            Liang Wu, Subashan Perera, Lorie Richards … (2007)
            Gait velocity is a powerful indicator of function and prognosis after stroke. Gait velocity can be stratified into clinically meaningful functional ambulation classes, such as household ambulation ( 0.8 m/s). The purpose of the current study was to determine whether changes in velocity-based community ambulation classification were related to clinically meaningful changes in stroke-related function and quality of life. In subacute stroke survivors with mild to moderate deficits who participated in a randomized clinical trial of stroke rehabilitation and had a baseline gait velocity of 0.8 m/s or less, we assessed the effect of success versus failure to achieve a transition to the next class on function and quality of life according to domains of the Stroke Impact Scale (SIS). Of 64 eligible participants, 19 were initially household ambulators, and 12 of them (68%) transitioned to limited community ambulation, whereas of 45 initially limited community ambulators, 17 (38%) became full community ambulators. Function and quality-of-life SIS scores after treatment were significantly higher among survivors who achieved a favorable transition compared with those who did not. Among household ambulators, those who transitioned to limited or full community ambulation had significantly better SIS scores in mobility (P=0.0299) and participation (P=0.0277). Among limited community ambulators, those who achieved the transition to full community ambulatory status had significantly better scores in SIS participation (P=0.0085). A gait velocity gain that results in a transition to a higher class of ambulation results in better function and quality of life, especially for household ambulators. Household ambulators possibly had more severe stroke deficits, reducing the risk of "ceiling" effects in SIS-measured activities of daily living and instrumental activities of daily living. Outcome assessment based on transitions within a mobility classification scheme that is rooted in gait velocity yields potentially meaningful indicators of clinical benefit. Outcomes should be selected that are clinically meaningful for all levels of severity.
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              Classification of walking handicap in the stroke population.

              Paul Garrett, Ivan Perry, S Mulroy … (1995)
              The limited walking ability that follows a stroke restricts the patient's independent mobility about the home and community, a significant social handicap. To improve the in-hospital prediction of functional outcome, the relationships between impairment, disability, and handicap were assessed with clinical measures in 147 stroke patients. The patients' level of functional walking ability at home and in the community was assigned by expert clinicians to one of the six categories of a modified Hoffer Functional Ambulation scale at least 3 months after discharge. A 19-item questionnaire was further used to assess current customary mobility of the subjects. Functional muscle strength and proprioception were tested, and walking velocity was measured. The significant indicators of impairment, upright motor control knee flexion and extension strength, differentiated household from community ambulators. The addition of velocity improved the functional prediction. Proprioception was clinically normal in all walkers. The validity of the criteria for the six levels of walking handicap was confirmed statistically. Stepwise discriminant analysis reduced the ambulation activities on the questionnaire from 19 to 7. Redefinition of the criteria for patient classification using the coefficients and constants of the seven critical functions improved the prediction of patient walking ability to 84%. The results of this study offer a quantitative method of relating the social disadvantage of stroke patients to the impairment and disability sustained. The measurement of therapeutic outcome in relation to the social advantage for the patient would allow more efficient standardization of treatment and services.
              Article 0 comments Cited 151 times – based on 0 reviews     Review now
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                Author and article information

                Contributors
                Masataka Yamamoto: m-yamamoto@rs.tus.ac.jp
                Journal
                Journal ID (nlm-ta): Sci Rep
                Journal ID (iso-abbrev): Sci Rep
                Title: Scientific Reports
                Publisher: Nature Publishing Group UK (London )
                ISSN (Electronic): 2045-2322
                Publication date (Electronic): 21 October 2022
                Publication date PMC-release: 21 October 2022
                Publication date Collection: 2022
                Volume: 12
                Electronic Location Identifier: 17719
                Affiliations
                [1 ]GRID grid.143643.7, ISNI 0000 0001 0660 6861, Faculty of Science and Technology, , Tokyo University of Science, ; Noda, 278-8510 Japan
                [2 ]GRID grid.257022.0, ISNI 0000 0000 8711 3200, Graduate School of Advanced Science and Engineering, , Hiroshima University, ; Higashi-Hiroshima, 739-8527 Japan
                [3 ]GRID grid.412155.6, ISNI 0000 0001 0726 4429, Faculty of Health and Welfare, , Prefectural University of Hiroshima, ; Mihara, 723-0053 Japan
                Article
                Publisher ID: 22246
                DOI: 10.1038/s41598-022-22246-5
                PMC ID: 9586966
                PubMed ID: 36271241
                SO-VID: 25d8e148-119c-4ff6-b9b3-2b8b9c69e14b
                Copyright © © The Author(s) 2022
                License:

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

                History
                Date received : 23 May 2022
                Date accepted : 12 October 2022
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100001691, Japan Society for the Promotion of Science;
                Award ID: JP19K20748
                Award Recipient :
                Categories
                Subject: Article
                Custom metadata
                issue-copyright-statement © The Author(s) 2022

                ScienceOpen disciplines: Uncategorized
                Keywords: rehabilitation,biomedical engineering
                Data availability:
                ScienceOpen disciplines: Uncategorized
                Keywords: rehabilitation, biomedical engineering

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