Anterior cruciate ligament (ACL) injuries are common, costly to treat if repaired, and often lead to post-traumatic osteoarthritis. ACL injuries are commonly attributed to a single rare, acute, high loading event. However, evidence in the literature supports an alternative injury mechanism - sub-failure ACL cyclic loading causes microtrauma that accumulates over time, compromising ACL mechanical properties and making it more likely to fail at lower loads. To test hypotheses related to this cyclic loading injury mechanism, a method is needed to record and track in-vivo the frequency and magnitude of ACL loading events. Inertial measurement unit (IMU) based wearable devices offer a means to measure the frequency and magnitude of these loading events throughout the duration of physical activities in an ecologically valid environment (a real-world setting as opposed to a lab environment).

The goal of this research was to develop and evaluate an IMU-based approach to quantify a metric clinically relevant to tracking ACL loading events in-vivo. Anterior displacement of the tibia relative to the femur is a primary loading mechanism of the ACL. Reliable measurement of this mm-scale displacement using IMU data is not feasible, but relative anterior tibial acceleration (RATA - the second time derivative of anterior tibial translation) is a potential surrogate metric of ACL loading that can be measured with IMUs. The objectives of this thesis were:​ (1) to develop data processing algorithms to utilize signals from two IMUs, secured in arbitrary locations and orientations on the thigh and shank, and calculate the RATA metric theorized to be sensitive to ACL loading, (2) to characterize the performance of the algorithms, (3) to identify any effects soft-tissue has on IMU-measured RATA, and (4) to demonstrate the feasibility and utility of the proposed wearable device for collecting useful ACL loading event history, from athletes in the field, that have the potential for being prognostic for ACL injury. The RATA algorithm was evaluated using a rigid mechanical human-leg analog test rig, with and without a ballistic gel to mimic soft tissue, prior to testing with human participants. RATA was measured simultaneously using IMUs and using an optical motion capture system as a reference RATA measurement. IMU-measured peak RATA was within ± 20% of the optical motion capture measurement for 91% of trials without ballistic gel and 60% of the trials with ballistic gel. Due to the soft-tissue on the mechanical thigh being relatively thick and the softtissue on the mechanical shank being relatively thin (more like a rigid-body) there was a phase lag between the femoral and tibial acceleration used to calculate RATA. Modifying the RATA algorithm to compensate for phase lag, the percentage of trials that had IMU-measured peak RATA within ± 20% of the optical motion capture measurement increased from 60% to 83%. Compensating for phase lag was applied to the data from the human participant experiment. Two human participants performed six different common athletic movements, three of which were anticipated to be relatively low ACL loading and three were anticipated to involve relatively high ACL loading. Peak RATA measurements occurred in distinct ranges for the low and the high ACL loading movements for each participant. Thus, a clear peak RATA threshold for each participant could be established that separated the data into the two movement categories. For both participants, at least 93% of low ACL loading activity trials were below the subject-specific peak RATA threshold and at least 67% of the high ACL loading activity trials were above the threshold. The results indicate the wearable device has strong potential to track in-vivo the frequency and magnitude of ACL loading events and thus acquire data needed to test theories of a cyclic microtrauma accumulation mechanism of ACL injury.