What music is optimal for your heart? Music recommendation via bio-feedback and collaboration. Some interesting work by folks at the University of Virginia and Microsoft. A preprint of their paper here
MusicalHeart: A Hearty Way of Listening to Music
Shahriar Nirjon, Robert F. Dickerson, Qiang Li, Philip Asare, and John A. Stankovic Department of Computer Science University of Virginia, USA
Dezhi Hong, Ben Zhang, Xiaofan Jiang, Guobin Shen, and Feng Zhao Microsoft Research Asia, Beijing, China
MusicalHeart is a biofeedback-based, context-aware, au- tomated music recommendation system for smartphones. We introduce a new wearable sensing platform, Septimu, which consists of a pair of sensor-equipped earphones that communicate to the smartphone via the audio jack. The Septimu platform enables the MusicalHeart application to continuously monitor the heart rate and activity level of the user while listening to music. The physiological information and contextual information are then sent to a remote server, which provides dynamic music suggestions to help the user maintain a target heart rate. We provide empirical evidence that the measured heart rate is 75% − 85% correlated to the ground truth with an average error of 7.5 BPM. The accu- racy of the person-specific, 3-class activity level detector is on average 96.8%, where these activity levels are separated based on their differing impacts on heart rate. We demon- strate the practicality of MusicalHeart by deploying it in two real world scenarios and show that MusicalHeart helps the user achieve a desired heart rate intensity with an average error of less than 12.2%, and its quality of recommendation improves over time.