Integrating Biomechanical Technologies with Orthopaedic Clinics to Improve Surgical Outcomes for Knee Osteoarthritis

About the Project

Osteoarthritis (OA) affects millions of Canadians and involves a loss of joint cartilage and changes to nearby bone and soft tissue. This serious and incurable disease is also accompanied by increased pain, reduced function and an elevated risk of frailty. The end-stage treatment for OA is a total joint replacement but identifying those most in need for this treatment is challenging. Assessing the movement and loading of the lower limbs during walking and functional tasks can be an excellent way to support clinical decisions for the ever-increasing number of older adults with this disease.

Unfortunately, no previous technology offered a clinically viable method to do so. Thankfully, recent advancements in motion capture cameras, wearable sensors, and artificial intelligence have changed that. We now have the capabilities to accurately and efficiently collect this information in-clinic and during a patient’s daily life. Nevertheless, this state-of-the-art technology has yet to be incorporated in an orthopaedic clinic and there is a need to determine the feasibility and accuracy of these data before they can support clinical decision making. Additionally, there is a need to understand the declines that occur while people are awaiting surgery. Therefore, the current project aims to implement these technologies at the Fracture and Orthopedics Clinic at St. Joseph’s Healthcare Hamilton and lay the foundation for a world-class translation research program that can provide clinicians with a complete picture of their patient’s joint function and specific deficits to ultimately facilitate innovations and customizations of treatment.

Project Team

Principal Investigator:

Dylan Kobsar – McMaster University


Anthony Aldili – McMaster University
Janie Astephen Wilson – Dalhousie University
Paula Gardner – McMaster University
Kim Madden – McMaster University
Rong Zheng – McMaster University

Keywords: osteoarthritis; gait; walking; functional status; arthroplasty; replacement; knee; technology; frailty; aging

Background & Rationale


Osteoarthritis is a serious disease where the structure of a joint deteriorates resulting in significant pain and functional limitations for the patient. There is no cure for osteoarthritis, but a total joint replacement can greatly improve pain and function. Unfortunately, wait times are increasing as this disease affects millions across Canada. Therefore, there is a need to develop new technology and clinical practices that can find those who are most in need of treatment and may be at risk increased functional limitations and frailty if forced to wait.


Advanced camera and sensor technology has the potential to collect detailed information on a patient’s movement pattern both in-clinic and in their daily life. Unfortunately, we still need to understand how feasibility this equipment is in a clinical setting and how this information can be best used to optimize surgical decisions.

Research Plan & Hypothesis

Research Plan

This work will look to compare how repeatable the collection of in-clinic lower limb movement patterns is during walking and functional tasks. Also, this work will examine how feasible it is to collect this information during standard clinical visits. We will use advanced video technology and wearable sensor technology to look at the consistency of this information, as well as the changes that patients undergo as they wait for surgery.


We expect that this technology will provide a feasible approach to collect important information on a patient’s movement patterns. Further, we expect that the functional declines we see while patients are waiting for surgery will help us to understand those who are most in need of surgery.


Our objectives are to establish the quality of the information we can collect with this technology both in-clinic and out-of-clinic. Additionally, we aim to examine the feasibility of implementing these technologies in regular clinical visits that will allow for this technology to help personalize treatment decisions.