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Evaluation on Context Recognition Using Temperature Sensors in the Nostrils
by
Masahiko Tsukamoto
, Ryosuke Kodama
, Tsutomu Terada
in
Activities of Daily Living
/ Chemical technology
/ context recognition
/ Drinking
/ Environment Design
/ Humans
/ nasal cycle
/ Respiratory Rate
/ Temperature
/ temperature sensor
/ TP1-1185
/ User-Computer Interface
/ Walking
/ wearable computing
/ Wearable Electronic Devices
2019
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Evaluation on Context Recognition Using Temperature Sensors in the Nostrils
by
Masahiko Tsukamoto
, Ryosuke Kodama
, Tsutomu Terada
in
Activities of Daily Living
/ Chemical technology
/ context recognition
/ Drinking
/ Environment Design
/ Humans
/ nasal cycle
/ Respiratory Rate
/ Temperature
/ temperature sensor
/ TP1-1185
/ User-Computer Interface
/ Walking
/ wearable computing
/ Wearable Electronic Devices
2019
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Do you wish to request the book?
Evaluation on Context Recognition Using Temperature Sensors in the Nostrils
by
Masahiko Tsukamoto
, Ryosuke Kodama
, Tsutomu Terada
in
Activities of Daily Living
/ Chemical technology
/ context recognition
/ Drinking
/ Environment Design
/ Humans
/ nasal cycle
/ Respiratory Rate
/ Temperature
/ temperature sensor
/ TP1-1185
/ User-Computer Interface
/ Walking
/ wearable computing
/ Wearable Electronic Devices
2019
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Evaluation on Context Recognition Using Temperature Sensors in the Nostrils
Journal Article
Evaluation on Context Recognition Using Temperature Sensors in the Nostrils
2019
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Overview
We can benefit from various services with context recognition using wearable sensors. In this study, we focus on the contexts acquired from sensor data in the nostrils. Nostrils can provide various contexts on breathing, nasal congestion, and higher level contexts including psychological and health states. In this paper, we propose a context recognition method using the information in the nostril. We develop a system to acquire the temperature in the nostrils using small temperature sensors connected to glasses. As a result of the evaluations, the proposed system can detect breathing correctly, workload at an accuracy of 96.4%, six behaviors at an accuracy of 54%, and eight behaviors in daily life at an accuracy of 86%. Moreover, the proposed system can detect nasal congestion, therefore, it can log nasal cycles that are considered to have a relationship with the autonomic nerves and/or biological states.
Publisher
MDPI AG,MDPI
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