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The observation and management of a person after a medical, surgical or any health care intervention is important to avoid preventable complications, to identify general health deterioration, and to assist with post intervention recovery. A person's walking gait is a key indicator of neurological and musculoskeletal health and by examining the way a person walks, it is immediately apparent to a trained neuro/spine surgeon if there are issues and how amenable they may be to surgical intervention . However, this subjective assessment that is supported by questionnaires and undertaken at arbitrary fixed time points could be improved by a data-driven approach with continual measurement . Despite the ubiquitous growth of fitness wearables, there are few devices and corresponding analytical tools for objective and continual monitoring of gait.

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The WAGAR (Wearable and Gait Assessment Research) Group has developed several scoring algorithms for the objective assessment of gait and mobility.  Key metrics such as step count, gait velocity, step length and posture feed into a general Gait Posture Index. This index has been improved with research to integrate gait quality measures such as cadence, stability, symmetry, and single/double foot support time. The algorithms can then be used to analyse hip/knee pathologies and a range of specific conditions such as degenerative lumbar spine diseases and disc herniation, as well as neurological conditions such as stroke recovery, multiple sclerosis and Parkinson's.  

A key feature of the WAGAR Group research is the ability to analyse gait issues arising from multiple locations such as spine, hip and knee, using a single point of measurement leveraging a 9-axis accelerometer. Data extracted from a measurement device is put through a program that is able to extract multiple gait features. As the group expands its research and moves toward commercialisation, it is integrating data into its algorithms from multiple other health sensor types, requiring an optimised yet flexible platform that can support its product evolution pathway.

To date WAGAR has been using commercially available wearables to undertake their research. WAGAR reached out to Genesys to develop a system comprising a patch that is worn by the patient and a mobile App that displays data and communicates information to a backend platform for AI processing. Genesys is using its Wireless Wearable Sensing platform (see above) as a proof of concept for the WAGAR system and to provide a pathway for product development. 

Using this platform, a custom sensor board containing specific sensors required for WAGAR's next phase of research and commercialisation is being developed. This is plugged onto a base board that provides enabling features including data egress via Bluetooth, battery management and more. The custom sensor board and corresponding enclosure can be redeveloped through multiple product iterations. When WAGAR is ready to commercialise its product, a miniaturised single board version of the device will be developed.

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WWS Patch Exploded Render - Branch 1
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