Michel Hackbarth;Jessica Koschate;Sandra Lau;Tania Zieschang
{"title":"Depth-Imaging for Gait Analysis on a Treadmill in Older Adults at Risk of Falling","authors":"Michel Hackbarth;Jessica Koschate;Sandra Lau;Tania Zieschang","doi":"10.1109/JTEHM.2023.3277890","DOIUrl":null,"url":null,"abstract":"Background: Accidental falls are a major health issue in older people. One significant and potentially modifiable risk factor is reduced gait stability. Clinicians do not have sophisticated kinematic options to measure this risk factor with simple and affordable systems. Depth-imaging with AI-pose estimation can be used for gait analysis in young healthy adults. However, is it applicable for measuring gait in older adults at a risk of falling? Methods: In this methodological comparison 59 older adults with and without a history of falls walked on a treadmill while their gait pattern was recorded with multiple inertial measurement units and with an Azure Kinect depth-camera. Spatiotemporal gait parameters of both systems were compared for convergent validity and with a Bland-Altman plot. Results: Correlation between systems for stride length (r=.992, \n<inline-formula> <tex-math>$\\text{p} < 0.001$ </tex-math></inline-formula>\n) and stride time (r=0.914, \n<inline-formula> <tex-math>$\\text{p} < 0.001$ </tex-math></inline-formula>\n) was high. Bland-Altman plots revealed a moderate agreement in stride length (−0.74 ± 3.68 cm; [−7.96 cm to 6.47 cm]) and stride time (−3.7±54 ms; [−109 ms to 102 ms]). Conclusion: Gait parameters in older adults with and without a history of falls can be measured with inertial measurement units and Azure Kinect cameras. Affordable and small depth-cameras agree with IMUs for gait analysis in older adults with and without an increased risk of falling. However, tolerable accuracy is limited to the average over multiple steps of spatiotemporal parameters derived from the initial foot contact. Clinical Translation Statement— Gait parameters in older adults with and without a history of falls can be measured with inertial measurement units and Azure Kinect. Affordable and small depth-cameras, developed for various purposes in research and industry, agree with IMUs in clinical gait analysis in older adults with and without an increased risk of falling. However, tolerable accuracy to assess function or monitor changes in gait is limited to the average over multiple steps of spatiotemporal parameters derived from the initial foot contact.","PeriodicalId":54255,"journal":{"name":"IEEE Journal of Translational Engineering in Health and Medicine-Jtehm","volume":"11 ","pages":"479-486"},"PeriodicalIF":3.7000,"publicationDate":"2023-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10129931","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Journal of Translational Engineering in Health and Medicine-Jtehm","FirstCategoryId":"5","ListUrlMain":"https://ieeexplore.ieee.org/document/10129931/","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENGINEERING, BIOMEDICAL","Score":null,"Total":0}
引用次数: 0
Abstract
Background: Accidental falls are a major health issue in older people. One significant and potentially modifiable risk factor is reduced gait stability. Clinicians do not have sophisticated kinematic options to measure this risk factor with simple and affordable systems. Depth-imaging with AI-pose estimation can be used for gait analysis in young healthy adults. However, is it applicable for measuring gait in older adults at a risk of falling? Methods: In this methodological comparison 59 older adults with and without a history of falls walked on a treadmill while their gait pattern was recorded with multiple inertial measurement units and with an Azure Kinect depth-camera. Spatiotemporal gait parameters of both systems were compared for convergent validity and with a Bland-Altman plot. Results: Correlation between systems for stride length (r=.992,
$\text{p} < 0.001$
) and stride time (r=0.914,
$\text{p} < 0.001$
) was high. Bland-Altman plots revealed a moderate agreement in stride length (−0.74 ± 3.68 cm; [−7.96 cm to 6.47 cm]) and stride time (−3.7±54 ms; [−109 ms to 102 ms]). Conclusion: Gait parameters in older adults with and without a history of falls can be measured with inertial measurement units and Azure Kinect cameras. Affordable and small depth-cameras agree with IMUs for gait analysis in older adults with and without an increased risk of falling. However, tolerable accuracy is limited to the average over multiple steps of spatiotemporal parameters derived from the initial foot contact. Clinical Translation Statement— Gait parameters in older adults with and without a history of falls can be measured with inertial measurement units and Azure Kinect. Affordable and small depth-cameras, developed for various purposes in research and industry, agree with IMUs in clinical gait analysis in older adults with and without an increased risk of falling. However, tolerable accuracy to assess function or monitor changes in gait is limited to the average over multiple steps of spatiotemporal parameters derived from the initial foot contact.
期刊介绍:
The IEEE Journal of Translational Engineering in Health and Medicine is an open access product that bridges the engineering and clinical worlds, focusing on detailed descriptions of advanced technical solutions to a clinical need along with clinical results and healthcare relevance. The journal provides a platform for state-of-the-art technology directions in the interdisciplinary field of biomedical engineering, embracing engineering, life sciences and medicine. A unique aspect of the journal is its ability to foster a collaboration between physicians and engineers for presenting broad and compelling real world technological and engineering solutions that can be implemented in the interest of improving quality of patient care and treatment outcomes, thereby reducing costs and improving efficiency. The journal provides an active forum for clinical research and relevant state-of the-art technology for members of all the IEEE societies that have an interest in biomedical engineering as well as reaching out directly to physicians and the medical community through the American Medical Association (AMA) and other clinical societies. The scope of the journal includes, but is not limited, to topics on: Medical devices, healthcare delivery systems, global healthcare initiatives, and ICT based services; Technological relevance to healthcare cost reduction; Technology affecting healthcare management, decision-making, and policy; Advanced technical work that is applied to solving specific clinical needs.