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Towards the Real-World Analysis of Lumbar Spine Standing Posture in Individuals with Low Back Pain: A Cross-Sectional Observational Study.

Muñoz-Gómez, E., McClintock, F., Callaway, A., Clark, C., Alqhtani, R. and Williams, J., 2025. Towards the Real-World Analysis of Lumbar Spine Standing Posture in Individuals with Low Back Pain: A Cross-Sectional Observational Study. Sensors, 25 (10), 2983.

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DOI: 10.3390/s25102983

Abstract

Prolonged periods of standing are linked to low back pain (LBP). Evaluating lumbar spine biomechanics in real-world contexts can provide novel insights into these links. This study aimed to determine if standing behaviour can be quantified, in individuals with LBP, in real-world environments. A three-stage design was used, (i) Verification of a bespoke algorithm characterising lumbar standing behaviour, (ii) Day-long assessment of standing behaviours of individuals with posture-related low back discomfort, and (iii) Case study application to individuals with clinical LBP. Analysis of standing posture across time included variability, fidgeting, and amplitude probability distribution function analysis. The study demonstrated that accelerometers are a valid method for extracting standing posture from everyday activity data. There was a wide variety of postures throughout the day in people with posture-related low back discomfort and people with clinical LBP. Frequency profiles ranged from slightly flexed to slightly extended postures, with skewed bell-shaped distributions common. Postural variability ranged from 3.4° to 7.7°, and fidgeting from 1.0° to 3.0°. This work presents a validated accelerometer-based method to capture, identify, and quantify real-world lumbar standing postures. The distinct characteristics of people with low back discomfort or pain highlight the importance of individualised approaches.

Item Type:Article
ISSN:1424-8220
Uncontrolled Keywords:IMU; accelerometry; low back pain; posture; spine; variability; wearable electronic devices; Humans; Low Back Pain; Standing Position; Lumbar Vertebrae; Male; Female; Cross-Sectional Studies; Adult; Accelerometry; Middle Aged; Biomechanical Phenomena; Algorithms; Posture
Group:Faculty of Health & Social Sciences
ID Code:41110
Deposited By: Symplectic RT2
Deposited On:13 Jun 2025 14:46
Last Modified:13 Jun 2025 14:46

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