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Using Wearable Inertial Sensors to Track Body Kinematics During Gait

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... Previous IMU validation studies have focused on gait and have generally shown smaller discrepancies between wearable and optical motion capture systems [11] . However, a gait-based comparision is not entirely relevant to sports-related movements. ...
Article
Inertial Measurement Units (IMUs), an alternative to 3D optical motion capture, are growing in popularity to assess sports-related movements. This study validated an IMU system against a “gold-standard” optical motion capture system during common sports movements. Forty-nine healthy adults performed six movements common to a variety of sports applications (cutting, running, jumping, single leg squats, and cross-over twist) while simultaneously outfitted with standard, retroreflective markers and a wireless IMU system. Bias, RMSE, precision, and maximum absolute error (MAE) were calculated to compare the two systems at the lower extremity joints and the trunk in all planes of movement and for all activities. The MAE difference between fast and slow activities for the sagittal, transverse, and frontal planes were 11.62°, 7.41°, and 5.82°, respectively. For bias, the IMU system tended to report larger angles than the optical motion capture system in the transverse and frontal planes and smaller angles in the sagittal plane. Average intraclass correlation coefficients for the sagittal, transverse, and frontal planes were 0.81±0.17, 0.38±0.19, and 0.22±0.37, respectively. When calculating a global bias across all three planes, the IMU system reported nearly identical angles (< 3.5° difference) to the optical motion capture system. The global precision across all planes was 2-6.5°, and the global RMSE was 7-10.5°. However, the global MAE was 11-23°. Overall, and with suggestions for methodological improvement to further reduce measurement errors, these results support current applications and also indicate the need for continued validation and improvement of IMU systems.
... Self-selected gait with and without a secondary task 45 1 minute of walking at a self-selected pace with and without an auditory Stroop. ...
Article
Background: Clinical practice for rehabilitation after mild traumatic brain injury (mTBI) is variable and guidance on when to initiate physical therapy is lacking. Wearable sensor technology may aid clinical assessment, performance monitoring and exercise adherence, potentially improving rehabilitation outcomes during unsupervised home exercise programs. Objective: The objectives of this study were to 1) determine whether initiating rehabilitation earlier than typical will improve outcomes after mTBI; and 2) examine whether using wearable sensors during a home-exercise program will improve outcomes in participants with mTBI. Design: This was a randomized controlled trial. Setting: Academic hospital; Oregon Health & Science University, Portland Veterans Affairs Health Care System, and in the home environment. Participants: This study will include 160 individuals with mTBI. Intervention: The early intervention group (n = 80) will receive one-on-one physical therapy 8 times over 6 weeks and complete daily home-exercises. The standard care group (n = 80) will complete the same intervention after a 6 to 8-week wait period. Half of each group will receive wearable sensors for therapist monitoring of patient adherence and quality of movements during their home exercise program. Measurements: The primary outcome measure will be the Dizziness Handicap Inventory score. Secondary outcome measures will include: symptomatology, static and dynamic postural control, central sensorimotor integration posturography, and vestibular-ocular-motor function. Limitations: Potential limitations include variable onset of care, a wide range of ages, possible low adherence and/or withdrawal from the study in the standard of care group, and low DHI scores effecting ceiling for change after rehabilitation. Conclusions: If initiating rehabilitation earlier improves primary and secondary outcomes post-mTBI, this could help shape current clinical care guidelines for rehabilitation. Additionally, using wearable sensors to monitor performance and adherence may improve home-exercise outcomes.
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