|MusicalHeart is a bio-feedback based, context aware, automated 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 the user is listening to music. The physiological information along with contextual information are then sent to a remote server, which provides dynamic music suggestions to assist 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, and the accuracy of activity level and context inference are on average 96.8% and 84.1%, respectively. We demonstrate the practicality of MusicalHeart by deploying it to 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 it's quality of recommendation improves over time.|
- Shahriar Nirjon (smn8z@virgina,edu)
- Robert Dickerson (rfd7a@virginia,edu)
- Qiang Li (lq7c@virginia,edu)
- Philip Asare (pka6qz@virginia,edu)
- John A. Stankovic (stankovic@virginia,edu)
- Dezhi Hong
- Ben Zhang
- Guobin Shen (jacky.shen@microsoft,com)
- Xiaofan Jiang (fxjiang@microsoft,com)
- Feng Zhao (zhao@microsoft,com)
MusicalHeart: A Hearty Way of Listening to Music. The 10th ACM Conference on Embedded Networked Sensor Systems (SenSys 2012).. 2012.
Demo Abstract: SEPTIMU - Continuous In-situ Human Wellness Monitoring and Feedback using Sensors Embedded in Earphones. Proceedings of The 11th ACM/IEEE Conference on Information Processing in Sensor Networks (IPSN 2012).. 2012.