RunnerPal: A Runner Monitoring and Advisory System based on Smart Devices


Running is one of the most important workouts to keep our body fit. This paper presents RunnerPal - a runner monitoring and advisory system by harmonizing the rhythms of breathing, heart beating and striding based on smart devices. RunnerPal is a convenient, biofeedback-based, automated music recommendation system, which utilizes Bluetooth headset, Apple Watch and smartphone to obtain body sensed data. To improve the accuracy of the detection, we propose a novel approach to calibrate the result by integrating ambient sensed data with a physiological model called Locomotor Respiratory Coupling (LRC), which indicates possible ratios between the striding and breathing frequencies. RunnerPal uses the sensed data and runner's contextual information to provide dynamic music suggestions to help the user achieve a target heart rate. We perform an empirical study to show the effect of music on heart rate and devise a Proportional Integral Differentiation Controller (PID-Controller) that recommends appropriate music to the user. RunnerPal has been validated by extensive experiments, and experimental results demonstrate that it can help runners achieve a target heart rate and maintain a stable running rhythm for indoor/outdoor running 91.6 percent of the time. In addition, RunnerPal can provide some advice to improve exercise effectiveness for runners.


Computer Science

Research Center/Lab(s)

Intelligent Systems Center

Second Research Center/Lab

Center for High Performance Computing Research


The authors would like to thank Dr. Debraj De and Francesco Restuccia for their careful reading and constructive suggestions to help improve the quality of the manuscript. This work was partly supported by the 973 Program (2013CB035503), National Natural Science Foundation of China (61572060, 61472024, 61170296 and 61190125). The work of S. K. Das is partially supported by the US National Science Foundation grants IIS-1404673, CNS-1355505, and IIP-1540119.

Keywords and Phrases

Biofeedback; Computer music; Heart; Physiological models; Proportional control systems; Recommender systems; Three term control systems; Two term control systems; Breathing frequency; Heart rates; Music recommending system; Running rhythm; Striding frequency; Monitoring

International Standard Serial Number (ISSN)


Document Type

Article - Journal

Document Version


File Type





© 2018 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.

Publication Date

01 Mar 2018