Validation of an algorithm for measurement of sedentary behaviour in community-dwelling older adults

Posted by Khalid Abdul Jabbar on 7 January 2024

Tags: real-world, sedentary behaviour, validation, older adults, wearable device, digital health

 Abdul Jabbar K, Sarvestan J, Zia Ur Rehman R, Lord S, Kerse N, Teh R, Del Din S. Validation of an algorithm for measurement of sedentary behaviour in community-dwelling older adults. 2023. Sensors 23(10) doi: 10.3390/s23104605

Abstract: Accurate measurement of sedentary behaviour in older adults is informative and relevant. Yet, activities such as sitting are not accurately distinguished from non-sedentary activities (e.g., upright activities), especially in real-world conditions. This study examines the accuracy of a novel algorithm to identify sitting, lying, and upright activities in community-dwelling older people in real-world conditions. Eighteen older adults wore a single triaxial accelerometer with an onboard tri-axial gyroscope on their lower back and performed a range of scripted and non-scripted activities in their homes/retirement villages whilst being videoed. A novel algorithm was developed to identify sitting, lying, and upright activities. The algorithm’s sensitivity, specificity, positive predictive value, and negative predictive value for identifying scripted sitting activities ranged from 76.9% to 94.8%. For scripted lying activities: 70.4% to 95.7%. For scripted upright activities: 75.9% to 93.1%. For non-scripted sitting activities: 92.3% to 99.5%. No non-scripted lying activities were captured. For non-scripted upright activities: 94.3% to 99.5%. The algorithm could, at worst, overestimate or underestimate sedentary behaviour bouts by ±40 s, which is within a 5% error for sedentary behaviour bouts. These results indicate good to excellent agreement for the novel algorithm, providing a valid measure of sedentary behaviour in community-dwelling older adults.