4.7 Article Proceedings Paper

Neural Network Estimation of Eardrum Temperature Using Multiple Sensors Integrated on a Wristwatch-Sized Device

Journal

IEEE SENSORS JOURNAL
Volume 21, Issue 8, Pages 9742-9748

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/JSEN.2020.2990745

Keywords

Temperature sensors; Temperature measurement; Neural networks; Estimation; Heating systems; Temperature distribution; Eardrum temperature; neural network; wearable device

Ask authors/readers for more resources

This study demonstrates a novel system using neural networks and data from multiple sensors to estimate eardrum temperature. By inputting time series data and optimizing the system, the estimation accuracy was improved, confirming the effectiveness of the system.
In this study, a novel system to help estimate eardrum temperature utilizing neural networks as well as data acquired from multiple sensors integrated on a wristwatch-type wearable device is successfully demonstrated. Conventional estimation methods, which use a heat balance model of the body, cannot be applied as it needs parameters, such as the thermal index of the body and the information on clothes, which cannot be measured by the wristwatch-type device. We introduced sensors that measure environmental quantities and vital signals to experimentally acquire sensing data from outdoor locales. To improve the estimation accuracy, time series data were input to a neural network, and the system was optimized by comparing the estimation accuracy while varying the time length and time interval of each sensor. By setting the time interval to 10 s and the time length to 30 as one dataset, the standard deviation of the error between the measured and the estimated eardrum temperatures is 0.046 C, and the ratio of the data where the error between the measured and estimated values was within 0.1 C was 97.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.7
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available