The ExerScout Gait Analysis application is a non-marker-based motion tracking system that automatically gathers data of an individual’s gait while they are on a treadmill. This research began as a 12-month Innovation Partnership and R&D project with Elite Sports Performance. The Irish company is involved in appraising fitness and agility by evaluating fundamental movement patterns using the Functional Movement Screening (FMS) approach.
ExerScout Gait Analysis
Elite Sports Performance came to the TSSG Gateway with an interest in developing an automated way in which FMS could be used by evaluating subjects whereby they would perform the tests, be assessed by software, and have sets of corrective exercises prescribed to them to allow them to improve their mobility, stability and flexibility and to reduce their risk of injury.
The GlaxoSmithKline (GSK) Human Performance Lab, a close partner of Elite Sports Performance, was intrigued by the application of ExerScout and tasked Elite Sports Performance to develop a feature that allowed the analysis of a person’s gait using the Microsoft Kinect V2. This new feature would then be compared to a state of the art 24 sensor treadmill that is available in GSK.
How did TSSG help?
TSSG developed this feature on the existing ExerScout platform along with further requests of assessing standing analysis, balance analysis and sitting analysis.
A complete Windows 10 application was developed in conjunction with the Microsoft Kinect V2 that can evaluate the 7 FMS tests, score each test, identify weaknesses and provide corrective exercises that will improve the scores given. The application also has a media section that contains footage on each of the seven tests and all the corrective exercises that are associated with each test.
A series of algorithms have been developed which includes methods for calculating a user’s step width, step length and stride length. Not only does the application gather data on a person’s gait, but it will also gather data on other gestures including stance, balance, and other movements while performing the exercise on the treadmill.
The Windows 10 application gathers data from the Microsoft Kinect V2 sensor while a person is walking on the treadmill. The Kinect V2 is a motion sensor that can measure three-dimensional motions of a person. The data generated by the Kinect V2 is a frame-by-frame algorithmic calculation of various gestures. A readout is displayed in the application of the calculations for each gesture that is being generated and they are also being stored in the cloud. A skeleton representation of the person on the treadmill is also displayed within the application. For further analysis, the data can be exported to a CSV file and analysed by an expert to identified trends, etc.
Impact on the company
The client has received a new product, which opens up a wide range of new customers, target markets, and the geographical locations it can reach. The product is completely flexible and can be adapted for other exercises.
The platform was updated and contains a series of new tests and features that can be used in conjunction with research, development, and testing within the GSK Human Performance Lab. This has increased the strength of the relationship between GSK, Elite Sports Performance, and the TSSG Gateway. Future work is in the pipeline for more features to be developed on the ExerScout Platform.
Following on from the development completed under the ExerScout project, other areas of interest could be assisting in the early diagnosis of Neurodegenerative Diseases. With the algorithms that have been developed, there is an opportunity for collaborations with neurorehabilitation, WIT Biomechanics, or Alzheimer’s Association of Ireland.
https://www.technologygateway.ie/wp-content/uploads/2018/10/Surprising-results-in-gait-analysis-research-Technology-Gateway-Network.jpg400600Technology Gatewayshttps://www.technologygateway.ie/wp-content/uploads/2017/01/Enterprise-Ireland-Technology-Gateway-logo.jpgTechnology Gateways2018-10-30 18:30:402018-10-30 18:30:40Surprising results in gait analysis research
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