Arthritis Western Australia & Arthritis Queensland GIA
Recipient:
Dr Amity Campbell and Tara Binnie
Intended Department
School of Physiotherapy and Exercise Science- Curtin University
Project:
Predicting knee loading using wearable sensors
Image: Tara Binnie
This study aims to validate a model for estimating knee joint loading from wearable sensor data. Currently clinicians and researchers are restricted to using expensive laboratory-based equipment to measure knee joint loading, and this method fails to provide any information on how the patient actually uses their knee in their normal activities of daily living when away from the laboratory/clinic. Several specific measures of knee loading, such as the load acting to push the knee outwards during walking, have been demonstrated to predict the progression of knee osteoarthritis and have been identified as critical measures. Thus, using wearable sensors would greatly advance the understanding of how people with knee OA load their knee in daily life, and this knowledge could assist in the development of effective treatments that slow or stop the progression of knee OA.
Once this research has been completed and it has been confirmed that wearable sensors can accurately predict knee joint loading, we will use the sensors in a range of clinically focussed studies to track how people move in their daily lives. It is hoped that this body of knowledge will better our understanding of the way people with a range of musculoskeletal disorders move and how this associates with their pain and disease progression. The results of this study provides us with great confidence that we will be successful in developing a model to accurately predict knee joint loading in individuals with knee OA, using wearable sensors.
1m 52s
Predicting knee loading using wearable sensors
Sign up to Arthritis Insights
Regular updates, news and research findings delivered to your inbox:
