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. 2019 Dec 24;20(1):125.
doi: 10.3390/s20010125.

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

Anika Steinert  1 , Igor Sattler  1 , Karen Otte  2   3 , Hanna Röhling  3 , Sebastian Mansow-Model  3 , Ursula Müller-Werdan  1
Affiliations

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

Anika Steinert et al. Sensors (Basel). .

Abstract

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.

Keywords: gait analysis; gait parameters; mobile technologies; movement; older adults.

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Conflict of interest statement

The authors Anika Steinert, Igor Sattler, Hanna Röhling and Ursula Müller-Werdan declare that they have no financial or personal relationship that influence (bias) their work. Karen Otte is a shareholder of Motognosis and named as inventor on patent applications describing perceptive visual computing for tracking of motor dysfunction. She received speaker honoraria from Biogen on unrelated work. Sebastian Mansow-Model is a shareholder of Motognosis and named as inventor on patent applications describing perceptive visual computing for tracking of motor dysfunction.

Figures

Figure 1
Figure 1
Experimental setup.
See this image and copyright information in PMC

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