FeverPhone: Accessible Core-Body Temperature Sensing for Fever Monitoring Using Commodity Smartphones

Joseph Breda, Mastafa Springston, Alex Mariakakis, Shwetak Patel
An illustration of the physical interaction used to collect temperature measurements using FeverPhone.


Smartphones contain thermistors that ordinarily monitor the temperature of the device's internal components; however, these sensors are also sensitive to warm entities in contact with the device, presenting opportunities for measuring human body temperature and detecting fevers. We present FeverPhone --- a smartphone app that estimates a person's core body temperature by having the user place the capacitive touchscreen of the phone against their forehead. During the assessment, the phone logs the temperature sensed by a thermistor and the raw capacitance sensed by the touchscreen to capture features describing the rate of heat transfer from the body to the device. These features are then used in a machine learning model to infer the user's core body temperature. We validate FeverPhone through both a lab simulation with a skin-like controllable heat source and a clinical study with real patients. We found that FeverPhone's temperature estimates are comparable to commercial off-the-shelf peripheral and tympanic thermometers. In a clinical study with 37 participants, FeverPhone readings achieved a mean absolute error of 0.229 °C, a limit of agreement of ±0.731 °C, and a Pearson's correlation coefficient of 0.763. Using these results for fever classification results in a sensitivity of 0.813 and a specificity of 0.904.