RunBuddy

As one of the most popular exercises, running is accomplished through a tight cooperation between the respiratory and locomotor systems. Research has suggested that a proper running rhythm -- the coordination between breathing and strides -- helps improve exercise efficiency and postpone fatigue. This paper presents RunBuddy -- the first smartphone-based system for continuous running rhythm monitoring. RunBuddy is designed to be a convenient and unobtrusive exercise feedback system, and only utilizes commodity devices including smartphone and Bluetooth headset. A key challenge in designing RunBuddy is that the sound of breathing typically has very low intensity and is susceptible to interference. To reliably measure running rhythm, we propose a novel approach that integrates ambient sensing based on accelerometer and microphone, and a physiological model called Locomotor Respiratory Coupling (LRC), which indicates possible ratios between the stride and breathing frequencies. We evaluate RunBuddy through experiments involving 13 subjects and 39 runs. Our results show that, by leveraging the LRC model, RunBuddy correctly measures the running rhythm for indoor/outdoor running 92:7% of the time. Moreover, RunBuddy also provides detailed physiological profile of running that can help users better understand their running process and improve exercise self-efficacy.