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.