Headset Bluetooth and Cell Phone based Continuous Central Body Temperature Measurement System J. Miguel Sanches 1,2 , B

1. Headset Bluetooth and Cell Phone based Continuous Central Body Temperature Measurement SystemJ. Miguel Sanches1,2, Bruno Pereira2 and Teresa Paiva3,4 1Institute for Systems and Robotics 2Instituto Superior Técnico 3Centro de Electroencefalografia e Neurofisiologia Clínica 4Faculdade de Medicina da Universidade de Lisboa Lisboa, Portugal 32nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society

2. Abstract • The accurate measure of the central temperature is a very important physiologic indicator in several clinical applications, namely, in the characterization and diagnosis of sleep disorders. • In this work, a simple system is described to continuously measure the body temperature at the ear. • An electronic temperature sensor is coupled to the microphone of a common commercial auricular Bluetooth device that sends the temperature measurements to a mobile phone to which is paired. • The measurements are stored at the mobile phone and periodically sent to a medical facility by email or SMS (short messaging service) 32nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society

3. Circadian Cycle of Melatonin Secretion • Direct measurement of melatonin secretion is difficult and it is only possible in laboratory or medical facilities. • The most used method to indirectly estimate the circadian rhythm of melatonin secretion is the central body temperature 32nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society

4. System 32nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society

5. Electronic Circuit 32nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society

6. Adaptive Sampling • Optimize the energy consumption of the auricular and increase its operation time. • The sampling rate is adaptively estimated according to the evolution of the temperature curve estimated up to the current time. • The sampling rate increases when the derivative of the signal increases and • The sampling rate decreases in the slow changes regions 32nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society

7. Adaptive Sampling 32nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society

8. Filtering 32nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society

9. Kalman Filter 32nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society

10. Kalman Filter: missing data • Filter Sequence 32nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society

11. Experimental Results 32nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society

12. References 32nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society