A Wearable Skin Temperature Monitoring System for Early Detection of Infections
IEEE Sensors Journal
; 2021.
Article
in English
| Scopus | ID: covidwho-1574574
ABSTRACT
This paper describes a wearable, open-source wrist temperature monitoring system that enables the reliable identification of slowly-varying skin temperature patterns that may be indicative of infections. The hardware platform uses a Bluetooth Low Energy (BLE) wireless interface and includes three skin temperature sensors, a thermally-isolated ambient temperature sensor, an inertial measurement unit (IMU), and a Galvanic skin response (GSR) sensor. A template-matching algorithm is used to detect weak but long-lived anomalous temperature patterns that deviate from the normal circadian rhythm are thus may be driven by infections. Experimental and simulation results confirm that small temperature anomalies (peak value <0.4°C) extending over 2-3 weeks can be detected with a total error rate <10%. IEEE
anomaly detection; COVID-19; early detection; Monitoring; Sensors; Skin; skin temperature; Temperature distribution; Temperature measurement; Temperature sensors; template-matching; wearable; Electrophysiology; Open systems; Template matching; Wearable sensors; Hardware platform; Monitoring system; Open-source; Skin temperatures; Temperature monitoring; Temperature patterns
Full text:
Available
Collection:
Databases of international organizations
Database:
Scopus
Language:
English
Journal:
IEEE Sensors Journal
Year:
2021
Document Type:
Article
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