Measuring knee instability to facilitate the diagnosis of ACL tears
Research type
Research Study
Full title
A comparison of anterior cruciate ligament injury and healthy knee instability by motion capture, with an explorative use of IMU sensors for the diagnosis of ACL tears
IRAS ID
305240
Contact name
Natasha Allott
Contact email
Sponsor organisation
Imperial College London
Duration of Study in the UK
2 years, 7 months, 1 days
Research summary
Lay summary of study results: This study investigated how the knee moves after an anterior cruciate ligament (ACL) injury and whether new technologies can help clinicians diagnose these injuries more accurately. To do this, patients with confirmed ACL injuries and healthy volunteers took part in a research assessment involving movement testing, muscle activity measurement, and wearable sensors. Ethical approval was obtained because the study involved human participants and required them to undergo structured physical assessments.
What the study involved:
Participants attended the motion analysis laboratory for a single testing session. Reflective markers were placed on their leg so that high-speed cameras could precisely track how their knee moved. Small sensors were also placed on the skin to measure muscle activity (electromyography), and wearable motion sensors were attached to capture joint movement during testing.Each participant completed several clinical tests commonly used to assess ACL injuries, such as the anterior drawer test and the Lachman test. These tests apply gentle movement to the knee to see how much the shin bone slides forwards or rotates—key signs of ACL damage. Participants then completed a short walking assessment on a walkway so their gait could also be analysed.
What the study found:
The motion capture system showed clear differences between injured and uninjured knees. People with ACL injuries had greater forward movement of the shin bone and greater rotational looseness, supporting what clinicians feel during manual testing but providing objective numerical values. Different tests produced slightly different results, confirming that no single test fully captures knee stability.Muscle activity was recorded to check whether patients were tensing or “guarding” the knee during testing. Although guarding occurred, it did not meaningfully affect the measurements, suggesting that inconsistency in clinical diagnosis is more likely due to subjective manual assessment rather than patient muscle tension.
The walking assessment showed that people with ACL injuries walk differently from healthy individuals, including changes in knee bending and rotation. These differences were present even in people injured many months earlier, highlighting the lasting impact of ACL damage.
Finally, data from wearable sensors were used to train a machine-learning model. The model was able to distinguish between ACL-injured and healthy participants with promising accuracy, showing that wearable technology could support future clinical diagnosis.
This research project aims to improve the accuracy and efficacy of anterior cruciate ligament (ACL) injury diagnosis by using VICON optical imaging and sensors called inertial measurement units (IMUs) to facilitate biomechanical analysis of the knee. IMUs are sensors that can detect and capture movement and VICON is the gold standard for motion capture. The ACL is a commonly injured ligament in the knee that is crucial for stability. The diagnosis of an acute ACL injury is known to be difficult and consequently, it is frequently missed. Delayed diagnosis can have implications to knee health and subsequently the person’s quality of life, including post-traumatic osteoarthritis (PTOA) and damage to surrounding structures. Delayed diagnosis results in abnormal loading and therefore worsening damage and patient outcomes. The current methods used to assess for ACL injury are subjective and unreliable.
This study requires participants with an acute ACL injury to undergo gait analysis, a series of movements and joint stability tests in the MSK lab, situated in the Sir Michael Uren building at Imperial College London. IMU sensors and VICON technology will be used to measure the biomechanics of the participant, IMU accuracy will be measured against VICON, which is currently the gold standard for assessing functional movement. Healthy participants with no history of knee injuries will also be needed to compare the data of those with an injury.The study aims to determine what is considered a significant difference in biomechanical abnormalities and suggest a quantifiable threshold that could indicate a likelihood of ACL injury, alongside this, it also aims to assess the feasibility of incorporating the new technology into existing clinical pathway.
The study will approximately last for 2 years, participants will only be required to attend once for data collection, the data collection period should take approximately 2 hours per participant.
REC name
London - Westminster Research Ethics Committee
REC reference
22/LO/0464
Date of REC Opinion
10 Aug 2022
REC opinion
Further Information Favourable Opinion