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Article

Using New Camera-Based Technologies for Gait Analysis in Older Adults in Comparison to the Established GAITRite System

1
Geriatrics Research Group, Charité–Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Charitéplatz 1, 10117 Berlin, Germany
2
NeuroCure Clinical Research Center, Charité-Universitaetsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Charitéplatz 1, 10117 Berlin, Germany
3
Motognosis GmbH, Schönhauser Allee 177, 10119 Berlin, Germany
*
Author to whom correspondence should be addressed.
Sensors 2020, 20(1), 125; https://doi.org/10.3390/s20010125
Received: 26 November 2019 / Revised: 20 December 2019 / Accepted: 20 December 2019 / Published: 24 December 2019
(This article belongs to the Collection Sensors for Gait, Human Movement Analysis, and Health Monitoring)
Various gait parameters can be used to assess the risk of falling in older adults. However, the state-of-the-art systems used to quantify gait parameters often come with high costs as well as training and space requirements. Gait analysis systems, which use mobile and commercially available cameras, can be an easily available, marker-free alternative. In a study with 44 participants (age ≥ 65 years), gait patterns were analyzed with three different systems: a pressure sensitive walkway system (GAITRite-System, GS) as gold standard, Motognosis Labs Software using a Microsoft Kinect Sensor (MKS), and a smartphone camera-based application (SCA). Intertrial repeatability showed moderate to excellent results for MKS (ICC(1,1) 0.574 to 0.962) for almost all measured gait parameters and moderate reliability in SCA measures for gait speed (ICC(1,1) 0.526 to 0.535). All gait parameters of MKS showed a high level of agreement with GS (ICC(2,k) 0.811 to 0.981). Gait parameters extracted with SCA showed poor reliability. The tested gait analysis systems based on different camera systems are currently only partially able to capture valid gait parameters. If the underlying algorithms are adapted and camera technology is advancing, it is conceivable that these comparatively simple methods could be used for gait analysis. View Full-Text
Keywords: gait analysis; movement; older adults; gait parameters; mobile technologies gait analysis; movement; older adults; gait parameters; mobile technologies
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MDPI and ACS Style

Steinert, A.; Sattler, I.; Otte, K.; Röhling, H.; Mansow-Model, S.; Müller-Werdan, U. Using New Camera-Based Technologies for Gait Analysis in Older Adults in Comparison to the Established GAITRite System. Sensors 2020, 20, 125. https://doi.org/10.3390/s20010125

AMA Style

Steinert A, Sattler I, Otte K, Röhling H, Mansow-Model S, Müller-Werdan U. Using New Camera-Based Technologies for Gait Analysis in Older Adults in Comparison to the Established GAITRite System. Sensors. 2020; 20(1):125. https://doi.org/10.3390/s20010125

Chicago/Turabian Style

Steinert, Anika, Igor Sattler, Karen Otte, Hanna Röhling, Sebastian Mansow-Model, and Ursula Müller-Werdan. 2020. "Using New Camera-Based Technologies for Gait Analysis in Older Adults in Comparison to the Established GAITRite System" Sensors 20, no. 1: 125. https://doi.org/10.3390/s20010125

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