JMIR Publications

ABSTRACT

Background:

Clinicians and athletic training specialists often assess performance of single leg, weightbearing tasks to monitor rehabilitation progress and guide exercise progression. Some of the key metrics assessed are excessive pelvic motion, balance, and duration of each repetition of the exercise. Motion can be objectively characterized using motion capture; however, motion capture is often not available in clinics due to high costs and complexity of the analyses. Smartphones have built-in sensors that can be used to measure changes in body segment orientation and acceleration, which may make them a more feasible and affordable technology to use in practice.

Objective:

This study aimed to determine if, compared to gold-standard motion capture, smartphone sensors can provide valid measures of pelvic orientation, acceleration and repetition duration during single leg tasks in healthy individuals.

Methods:

Fifty-two healthy participants performed single leg squats, and step down tasks from heights of 15 and 20 cm. Pelvic motion was assessed using motion capture and a smartphone placed over the sacrum. The Matlab Mobile application was used to collect smartphone acceleration and orientation data. Individual repetitions of each exercise were manually identified, and the following outcomes were extracted: duration of the repetition, medio-lateral acceleration, and three-dimensional pelvic orientation at peak squat. Validity was assessed by comparing metrics assessed with smartphone and motion capture using intraclass correlation coefficients (ICCs) and paired Wilcoxon tests. Differences between tasks were compared using one-way ANOVA or Friedman's test.

Results:

Across the three single leg tasks, smartphone estimates demonstrated consistently high agreement with the motion capture for all metrics (ICC point estimates: >.8 for medio-lateral acceleration and frontal plane orientation, >.9 for squat duration and orientation on the sagittal and transverse plane). Bias was identified for most outcomes (multiple p<.001). Both smartphone and motion capture recordings identified clear differences between tasks, with step down tasks usually requiring larger changes in pelvic orientation and larger medio-lateral sways. Duration did not differ between tasks.

Conclusions:

Despite a consistent bias, the smartphone demonstrated good to excellent validity relative to gold-standard motion capture for all outcomes. This demonstrates that smartphones offer an accessible and affordable tool to objectively characterize pelvic motion during different single leg weightbearing tasks. Together with earlier reports of good between-day reliability of similar measures during single leg squats, our results suggest that smartphone sensors can be used to assess and monitor single leg task performance, both in the clinic and remotely. Future studies should investigate whether personalized interventions based on motion assessment performed with smartphone sensors, and monitored using smartphone sensors, are more effective than conventional care. Clinical Trial: N/A