Purpose 

To determine and compare the accuracy of different activity monitors in assessing intermittent outdoor walking in both healthy and clinical populations through the development and validation of processing methodologies.

Methods 

In study 1, an automated algorithm was implemented and tested for the detection of short (≤1 min) walking and stopping bouts during prescribed walking protocols performed by healthy subjects in environments with low and high levels of obstruction. The following parameters obtained from activity monitors were tested, with different recording epochs0.1s/0.033s/1s/3s/10s and wearing locationsscapula/hip/wrist/ankle: GlobalSat DG100 (GS) and Qstarz BT-Q1000XT/-Q1000eX (QS) speed; ActiGraph wGT3X+ (AG) vector magnitude (VM) raw data, VM counts, and steps; and StepWatch3 (SW) steps. Further, linear mixed models were developed to estimate walking speeds and distances from the monitors parameters. Study 2 validated the performance of the activity monitors and processing methodologies in a clinical population showing profile of intermittent walking due to functional limitations during outdoor walking sessions.

Results 

In study 1, GS1s, scapula, QS1s, scapula/wrist speed, and AG0.033s, hip VM raw data provided the highest bout detection rates (>96.7%) and the lowest root-mean-square errors (RMSEs) in speed (≤0.4 km/h) and distance (<18 m) estimation. Using SW3s, ankle steps, the RMSE for walking/stopping duration estimation reached 13.6 min using proprietary software and 0.98 min using our algorithm (total recording duration =282 min). In study 2, using AG0.033s, hip VM raw data, the bout detection rate [95% CI] reached 100% [99–100], and the mean absolute percentage errors (SD) in speed and distance estimation were 9% (6.6) and 12.5% (7.9), respectively.

Conclusion 

GPS receivers and AG demonstrated high performance in assessing intermittent outdoor walking in both healthy and clinical populations.