Abstract
Neck pain is a prevalent condition and clinical examination techniques are limited and unable to assess out-of-plane motion. Recent works investigating cervical kinematics during neck circumduction (NC), a dynamic 3D task, has shown the ability to discern those with and without neck pain. The purposes of this study were to establish 1) confidence and prediction intervals of head-to-torso kinematics during NC in a healthy cohort, 2) a baseline summative metric to quantify the duration and magnitude of deviations outside the prediction interval, and 3) the reliability of NC. Thirty-nine participants (25.6 ± 6.3 years, 19F/20M) without neck pain completed left and right NC. A two-way smoothing spline analysis of variance was utilized to determine the mean-fitted values and 90% confidence and prediction intervals for NC. A standardized effect size was calculated and aggregated across all axes (Delta RMSD aggregate), as a summative metric of motion quality. Confidence and prediction intervals were comparable for left and right NC and demonstrated excellent reliability. The average sum of the Delta RMSD aggregate was 2.76 ± 0.55 for left NC and 2.74 ± 0.63 for right NC. The results of this study demonstrate the feasibility of utilizing normative intervals of a NC task to assess head-to-torso kinematics.
Original language | English (US) |
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Article number | 102591 |
Journal | Journal of Electromyography and Kinesiology |
Volume | 61 |
Early online date | Sep 8 2021 |
DOIs | |
State | Published - Dec 2021 |
Bibliographical note
Funding Information:Funding was provided by NIH/NICHD K12HD073945, NIH/NICHD R03HD09771, NIH/NIAMS T32AR050938, and a supported in part by a Promotion of Doctoral Studies (PODS) – Level II Scholarship from the Foundation for Physical Therapy. We also would like to thank Benjamin Hyatt, Jessica Blaisdell, Kayla Mabamba, Lisa Nguyen, Zachary Eitel, and Mary H. Foltz for their assistance in data collection.
Publisher Copyright:
© 2021 Elsevier Ltd
Keywords
- Cervical spine
- Circumduction
- Confidence interval
- Kinematics
- Motion analysis
- Prediction interval