Simon Harrison, Raymond C Z Cohen, Scott Starkey, Jayan Greenwood, Ernest Cheong, Khoi Nguyen, Phu Trinh, Tomislav Bacek, Denny Oetomo
{"title":"Evaluation of the Ergomechanic markerless motion capture system for lower body kinematics during standing, squatting and walking.","authors":"Simon Harrison, Raymond C Z Cohen, Scott Starkey, Jayan Greenwood, Ernest Cheong, Khoi Nguyen, Phu Trinh, Tomislav Bacek, Denny Oetomo","doi":"10.1115/1.4069821","DOIUrl":null,"url":null,"abstract":"<p><p>Markerless motion capture (MMC) shows promise for examining human movement across many domains because of its non-intrusive nature and negligible per-subject set up time. However published MMC systems typically require specific hardware. This validation study compared lower-body joint kinematics from Ergomechanic, a hardware-agnostic pose model-based MMC system, to an established marker-based motion capture (MBMC) system. Static trial data from eighteen people were used to register MMC keypoints within a widely used musculoskeletal model. The registered model was used to calculate joint kinematics for static pose, squatting, and walking trials. A novel perturbation analysis estimated the contributions to differences in MBMC and MMC approaches to measurement disparities. Very good (0.87 to 1.0) correlations between the systems were calculated for ankle, knee, and hip flexion-extension angles. Good (0.70-0.86) correlations were found for hip external-internal and abduction-adduction. Pelvis and lumbar spine angles had a wider range of correlation results (-0.06 to 0.95), likely due to the few MMC keypoints in these body regions. Relative contributions from the perturbation analysis were (i) 75% from variations in MMC data relative to MBMC; (ii) 8% because MMC keypoints (26) < MBMC markers (67); and (iii) 3% from differences in musculoskeletal model scaling. These results validate Ergomechanic for leg kinematics during standing, walking and squatting. Further, they suggest system improvements for pelvis and torso kinematics and provide new insights into the sources of known differences between MMC and MBMC measurements.</p>","PeriodicalId":54871,"journal":{"name":"Journal of Biomechanical Engineering-Transactions of the Asme","volume":" ","pages":"1-40"},"PeriodicalIF":1.7000,"publicationDate":"2025-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Biomechanical Engineering-Transactions of the Asme","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1115/1.4069821","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"BIOPHYSICS","Score":null,"Total":0}
引用次数: 0
Abstract
Markerless motion capture (MMC) shows promise for examining human movement across many domains because of its non-intrusive nature and negligible per-subject set up time. However published MMC systems typically require specific hardware. This validation study compared lower-body joint kinematics from Ergomechanic, a hardware-agnostic pose model-based MMC system, to an established marker-based motion capture (MBMC) system. Static trial data from eighteen people were used to register MMC keypoints within a widely used musculoskeletal model. The registered model was used to calculate joint kinematics for static pose, squatting, and walking trials. A novel perturbation analysis estimated the contributions to differences in MBMC and MMC approaches to measurement disparities. Very good (0.87 to 1.0) correlations between the systems were calculated for ankle, knee, and hip flexion-extension angles. Good (0.70-0.86) correlations were found for hip external-internal and abduction-adduction. Pelvis and lumbar spine angles had a wider range of correlation results (-0.06 to 0.95), likely due to the few MMC keypoints in these body regions. Relative contributions from the perturbation analysis were (i) 75% from variations in MMC data relative to MBMC; (ii) 8% because MMC keypoints (26) < MBMC markers (67); and (iii) 3% from differences in musculoskeletal model scaling. These results validate Ergomechanic for leg kinematics during standing, walking and squatting. Further, they suggest system improvements for pelvis and torso kinematics and provide new insights into the sources of known differences between MMC and MBMC measurements.
期刊介绍:
Artificial Organs and Prostheses; Bioinstrumentation and Measurements; Bioheat Transfer; Biomaterials; Biomechanics; Bioprocess Engineering; Cellular Mechanics; Design and Control of Biological Systems; Physiological Systems.