2023 ISAKOS Biennial Congress ePoster
Validation of Wearable Sensors for Functional Assessment Of TKA Patients in A Clinical Setting
Price Gallie, MBBS, FRACS, FAOA(Orth), Southport, QLD AUSTRALIA
Bradley Cornish, BExSc Hon, Southport AUSTRALIA
Jayishni Maharaj, PhD, Southport AUSTRALIA
David Lloyd, PhD, Gold Coast, QLD AUSTRALIA
David Saxby, PhD, MSc, BSc, Southport AUSTRALIA
Laura Diamond, PhD, Southport AUSTRALIA
Jenna Lyon, BEng, Sydney AUSTRALIA
Kevin Abbrezzese, PhD, Malwah UNITED STATES
Griffith University, Gold Coast, Queensland, AUSTRALIA
FDA Status Cleared
Summary
This study examined the use of a two sensor-IMU system to assess knee motion after robotically assisted TKA during activities of daily living (ADL) compared to 3DCGA.
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Abstract
Introduction
Total Knee Arthroplasty (TKA) is a commonly undertaken procedure in the treatment of knee osteoarthritis. TKA by any method is typically assessed qualitatively using patient reported outcome measures (PROMS) or more advanced and time-consuming quantifiable methods like 3D clinical gait analyses (3DCGA). This study examined the use of a two sensor-IMU system to assess knee motion after robotically assisted TKA during activities of daily living (ADL) compared to 3DCGA.
Method
The knee joint angles during a range of ADL were assessed for twenty patients (N=20) one-year post TKA. Two IMUs (Notch Interfaces Inc, NY) were attached to the subject where one was attached to the thigh and one to the shank of the surgically operated limb. Seventeen reflective markers were added to the same lower limb for optical motion capture. Multiple ADL (N=5) were assessed for all subjects. The ADL were sit-to-stand, walking, squatting, and stair ascent and descent. The kinematic output from the IMU and 3DCGA was compared and assessed for correlations and error.
Results
A coefficient of multiple correlation (CMC) analysis was conducted to assess sagittal plane movement for each of the activities where the knee motion was compared between systems. It was found that the CMC between systems for sagittal plane knee motion was 0.98±0.02, 0.98±0.02, 0.87±0.07, 0.88±0.02, and 0.90±0.06 for sit-to-stand, squatting, walking, stair ascent and stair descent, respectively. RMSE for the activities were computed and were 7.11±4.08°, 7.73±3.59°, 7.11±2.68°, 11.97±2.39°, 12.47±3.11°, respectively.
Conclusion
The two-IMU sensor system has the potential to reliably capture knee motion in sit-to-stand, squatting, and walking to objectively assess outcomes after robotically assisted TKA, compared to 3DCGA. These static and low velocity conditions would be ideal for clinical evaluation. There is opportunity to develop kinematic modelling approaches to improve the quantitative measurements.