McClintock, F. A., Callaway, A. J., Clark, C. J., Alqhtani, R. S. and Williams, J. M., 2024. Lumbar Sitting Behavior of Individuals with Low Back Pain: A Preliminary Study Using Extended Real-World Data. Sensors, 24 (20), 6751.
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DOI: 10.3390/s24206751
Abstract
Low back pain affects 619 million people worldwide and is commonly provoked by sitting. Current assessment methods constrain task variability, removing real-world, task-switching behaviors. This study utilized accelerometers to provide an original validated method of in vivo real-world assessment of lumbar sitting behavior throughout a full day. A three-stage study design was used, which involved (1) blinded verification of our sitting detection algorithm, (2) full-day data collection from participants with low back discomfort, quantifying lumbar angles, and end-user acceptability explored, (3) case study application to two clinical low back pain (LBP) patients, incorporating measurement of provocative sitting. Focus group discussions demonstrated that data collection methods were acceptable. Sitting ‘windows’ were created and analyzed using novel histograms, amplitude probability distribution functions, and variability, demonstrating that sitting behavior was unique and varied across individuals. One LBP patient demonstrated two frequent lumbar postures (<15% flexion and ~75% flexion), with pain provocation at 62% lumbar flexion. The second patient demonstrated a single dominant posture (~90% flexion), with pain provoked at 86% lumbar flexion. Our in vivo approach offers an acceptable method to gain new insights into provocative sitting behavior in individuals with LBP, allowing individualized unconstrained data for full-day postures and pain provocation behaviors to be quantified, which are otherwise unattainable.
Item Type: | Article |
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ISSN: | 1424-8220 |
Uncontrolled Keywords: | accelerometer; acceptability; pain; posture; spine; variability; Humans; Low Back Pain; Sitting Position;Male;Female;Adult;Accelerometry;Posture;Lumbosacral Region;Algorithms;Middle Aged |
Group: | Faculty of Health & Social Sciences |
ID Code: | 40511 |
Deposited By: | Symplectic RT2 |
Deposited On: | 22 Nov 2024 09:50 |
Last Modified: | 22 Nov 2024 09:50 |
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