Early mobilization after surgery reduces the incidence of a wide range of complications. Wearable motion sensors measure movements over time and transmit this data wirelessly, which has the potential to monitor patient recovery and encourages patients to engage in their own rehabilitation. The authors sought to determine the ability of off-the-shelf activity sensors to remotely monitor patient postoperative mobility. Consecutive subjects were recruited under the Department of Neurosurgery at Columbia University. Patients were enrolled during physical therapy sessions. The total number of steps counted by the two blinded researchers was compared to the steps recorded on four activity sensors positioned at different body locations. A total of 148 motion data points were generated. The start time, end time, and duration of each walking session were accurately recorded by the devices and were remotely available for the researchers to analyze. The sensor accuracy was significantly greater when placed over the ankles than over the hips (P<.001). Our multivariate analysis showed that step length was an independent predictor of sensor accuracy. On linear regression, there was a modest positive correlation between increasing step length and increased ankle sensor accuracy (r=.640, r(2)=.397) that reached statistical significance on the multivariate model (P=.03). Increased gait speed also correlated with increased ankle sensor accuracy, although less strongly (r=.444, r(2)=.197). The authors did not note an effect of unilateral weakness on the accuracy of left- versus right-sided sensors. Accuracy was also affected by several specific measures of a patient’s level of physical assistance, for which the team generated a model to mathematically adjust for systematic underestimation as well as disease severity.
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