Title: OrthoSense - Improving the diagnosis and treatment of MSK conditions using low cost sensors and smart analytics
Funder: Department of Health and Social Care

Abstract: The project aims to prove the accuracy and clinical relevance of IMU sensors measuring joint movement, specifically to analyse knee biomechanics. Our objective is to ultimately design a full clinical trial which demonstrates the improvement over existing visual assessments, joint-laxity tests and goniometry. We will identify optimal sensor selection, and begin prototyping joint movement characteristics (JMC's) that correlate with specific acute knee injuries. We will also identify the most relevant clinical pathway to apply these JMC's, and test these for reliability and accuracy against 'gold standard' current diagnosis methods. We will then gather user feedback from clinicians and patients to inform scaled-up product development and evaluation to ultimately design a full clinical trial. Our product will provide complex joint movement analysis and biomechanics informatics that is not currently available; although MEMs have been introduced in sporting environments, they are expensive and not relevant to clinical settings. Our sensors will allow complex joint movements to be assessed outside laboratory conditions through functional movements, and produce reliable and accurate clinical assessment data without the use of expensive and time-consuming imaging techniques. Potential Barriers The quantity of knee injuries, challenges the scalability of the solution nationwide and globally. This can be reasonably mitigated by their low cost and simple manufacturing process. Adoption of new technology in the clinical setting is always challenging - this can be addressed with ease of use, training and strong evidence of impact Innovation The innovation lies in the fusion of highly accurate, high frequency multi dimensional data with new analytics techniques that can distill this vast amount of data into salient clinical metrics. The application of analysed rich mobility data in a clinical setting has huge potential. NQM has a number of patents pending for privacy preserving sensor analytics, and our patent attorney found no barrier to operate.

Lay abstract: The project aims to prove the accuracy and clinical relevance of IMU sensors measuring joint movement, specifically to analyse knee biomechanics. Our objective is to ultimately design a full clinical trial which demonstrates the improvement over existing visual assessments, joint-laxity tests and goniometry. We will identify optimal sensor selection, and begin prototyping joint movement characteristics (JMC's) that correlate with specific acute knee injuries. We will also identify the most relevant clinical pathway to apply these JMC's, and test these for reliability and accuracy against 'gold standard' current diagnosis methods. We will then gather user feedback from clinicians and patients to inform scaled-up product development and evaluation to ultimately design a full clinical trial. Our product will provide complex joint movement analysis and biomechanics informatics that is not currently available; although MEMs have been introduced in sporting environments, they are expensive and not relevant to clinical settings. Our sensors will allow complex joint movements to be assessed outside laboratory conditions through functional movements, and produce reliable and accurate clinical assessment data without the use of expensive and time-consuming imaging techniques. Potential Barriers The quantity of knee injuries, challenges the scalability of the solution nationwide and globally. This can be reasonably mitigated by their low cost and simple manufacturing process. Adoption of new technology in the clinical setting is always challenging - this can be addressed with ease of use, training and strong evidence of impact Innovation The innovation lies in the fusion of highly accurate, high frequency multi dimensional data with new analytics techniques that can distill this vast amount of data into salient clinical metrics. The application of analysed rich mobility data in a clinical setting has huge potential. NQM has a number of patents pending for privacy preserving sensor analytics, and our patent attorney found no barrier to operate.

Research activity codes: 4.1 DISCOVERY AND PRECLINICAL TESTING OF MARKERS AND TECHNOLOGIES
Health categories: MUSCULOSKELETAL