Methods for Step Count Data: Determining "Valid" Days and Quantifying Fragmentation of Walking Bouts.

BACKGROUND

Step count monitors are frequently used in clinical research to measure walking activity. Systematically determining valid days and extracting informative measures of walking beyond total daily step count are among major analytical challenges.

RESEARCH QUESTION

We introduce a novel data-driven anomaly detection algorithm to determine days representing typical walking activity (valid days) and examine the value of measures of walking fragmentation beyond total daily step count.

METHODS

StepWatch data were collected on 230 adults with severe foot or ankle fractures. Average steps per minute (SC), average steps per active minute (SCA), active to sedentary transition probability (ASTP) and sedentary to active transition probability (SATP) were computed for each participant. The joint distribution of these measures was used to identify and eliminate invalid days through a multi-step process based on the support vector machine. The value of SCA, ASTP and SATP beyond SC were assessed by regressing Short Musculoskeletal Functional Assessment (SMFA), a measure of self-reported function, on these measures and quantifying the increase in the adjusted R-squared. In an unsupervised comparison, the total joint variability of SCA, ASTP and SATP was decomposed into the variability explained by SC and the unique variability of these three measures.

RESULTS

Of the 4,448 days in the original data set, 39% were determined invalid. Individuals with higher average SC had higher SCA, lower ASTP and higher SATP. Measures of fragmentation (SCA, ASTP and SATP) explained 25% more of the variability in SMFA compared with SC alone. Approximately 41% of the variability in SCA, ASTP and SATP could not be explained by SC suggesting that these three measures provide unique information about walking patterns.

SIGNIFICANCE

Applying SVM and quantifying fragmentation in walking bouts for step count data can help to more precisely assess activity in clinical studies employing this modality.