RunBuddy: A Smartphone System for Running Rhythm Monitoring

被引:35
作者
Hao, Tian [1 ]
Xing, Guoliang [1 ]
Zhou, Gang [2 ]
机构
[1] Michigan State Univ, E Lansing, MI 48824 USA
[2] Coll William & Mary, Williamsburg, VA 23187 USA
来源
PROCEEDINGS OF THE 2015 ACM INTERNATIONAL JOINT CONFERENCE ON PERVASIVE AND UBIQUITOUS COMPUTING (UBICOMP 2015) | 2015年
基金
美国国家科学基金会;
关键词
Smartphones; Exercise Monitoring; Running Rhythm; ENTRAINMENT; COORDINATION; FREQUENCY;
D O I
10.1145/2750858.2804293
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
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.
引用
收藏
页码:133 / 144
页数:12
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