A Pilot Study to Quantify Free-living Physical Performance in Individuals with Chronic Pain Using Wrist Accelerometry Data (Preprint)
Year: 2026
Type: preprint
Study design: Observational Study
Abstract: BACKGROUND Chronic pain significantly impacts physical function and quality of life. Current assessments rely on patient-reported measures or clinic-based tests, which may not accurately reflect real-world activity. OBJECTIVE To provide a preliminary evaluation of quantitative methods using wrist accelerometry data to quantify physical performance in a pilot study on individuals with chronic pain. METHODS Thirteen participants wore wrist-mounted accelerometers for seven days. The mean absolute deviation (MAD) metric was computed from raw acceleration data to classify sedentary and active behaviors. The durations and accumulation patterns of time spent in sedentary and active bouts were investigated. Activity intensity levels were also analyzed using wrist-based actigraphy cut-points previously developed for the general population. Additionally, total step counts were estimated from wrist actigraphy data. Correlations between actigraphy metrics and pain scores, age, and performance on a 6-minute walk test were examined. RESULTS The average daily percentage of time spent in sedentary and active states (light intensity and higher), based on the MAD metric, was 62% and 38%, respectively. However, the wrist-based actigraphy cut-points, previously established for the general population, tended to classify a greater proportion of time as sedentary (70%) and a smaller proportion as active (30%). Sedentary time was primarily accumulated through longer sedentary bouts. The average (SD) total daily step count was 9,344 (2,403) steps per day. Only average daily activity bout duration was associated with 6MWT (ρ = 0.56, p = 0.046). CONCLUSIONS The MAD-based metrics demonstrated feasibility for capturing light-intensity activities in individuals with chronic pain, suggesting an improved method for tracking functional outcomes. These findings should be interpreted as preliminary and hypothesis-generating, informing future studies on the integration of personalized, objective metrics into chronic pain management to better assess treatment efficacy and promote meaningful activity changes.
Authors: Omid Jahanian, Emma Fortune, Louis Faust, Sey Oloyede, Jimmy Trouard, Suzanne Dixon, Erica Torres, Chris Sletten, Paul Scholten
Language: English
Topic: Physical Activity and Health
Subfield: Physiology
Field: Medicine
Domain: Health Sciences
Open Access status: green
OpenAlex ID: W7160501069