Abstract
Studies have shown that about half of the injuries sustained during long-distance running involve the knee. Cadence (steps per minute) has been identified as a factor that is strongly associated with these running-related injuries, making it a worthwhile candidate for further study. As such, it is critical for long-distance runners to minimize their risk of injury by running at an appropriate running cadence. In this paper, we present the results of a study on the feasibility and usability of RunningCoach, a mobile health (mHealth) system that remotely monitors running cadence levels of runners in a continuous fashion, among other variables, and provides immediate feedback to runners in an effort to help them optimize their running cadence.
Highlights
Researchers have found that up to 79% of long-distance runners are expected to sustain a running-related injury in the lower extremities [1]
We are interested in understanding (i) how long-distance runners interact with RunningCoach; (ii) how long-distance runners perceive the accuracy of the data collected by RunningCoach; and (iii) what running-related analyses can be performed with the collected data to provide further insights into the system and runner’s performance
Studies suggest that optimizing cadence is an important factor in reducing the risk of sustaining a running-related injury and in improving overall running performance
Summary
Researchers have found that up to 79% of long-distance runners are expected to sustain a running-related injury in the lower extremities [1] Such injuries could potentially be avoided if the long-distance runner runs within the boundaries of the recommended cadence throughout the entire run. The primary function of most of these apps is to monitor the runner’s performance and to provide an interface for the runner to view statistics related to her or his runs. Some of these apps allow the runner to import workout plans that are aimed at motivating the runner and improving her or his performance.
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