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Article

Wearable Device for Observation of Physical Activity with the Purpose of Patient Monitoring Due to COVID-19

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Biophysics Laboratory, Physics Department, International Hellenic University, 65404 Kavala, Greece
2
Prisma Electronics SA, 45 Agias Kyriakis, Palaio Faliro, Attiki, 17675 Athens, Greece
*
Authors to whom correspondence should be addressed.
Academic Editor: Sheikh Shanawaz Mostafa
Signals 2022, 3(1), 11-28; https://doi.org/10.3390/signals3010002
Received: 3 December 2021 / Revised: 22 December 2021 / Accepted: 27 December 2021 / Published: 6 January 2022
(This article belongs to the Special Issue Deep Learning and Transfer Learning)
In late 2019, a new genre of coronavirus (COVID-19) was first identified in humans in Wuhan, China. In addition to this, COVID-19 spreads through droplets, so quarantine is necessary to halt the spread and to recover physically. This modern urgency creates a critical challenge for the latest technologies to detect and monitor potential patients of this new disease. In this vein, the Internet of Things (IoT) contributes to solving such problems. This paper proposed a wearable device that utilizes real-time monitoring to detect body temperature and ambient conditions. Moreover, the system automatically alerts the concerned person using this device. The alert is transmitted when the body exceeds the allowed temperature threshold. To achieve this, we developed an algorithm that detects physical exercise named “Continuous Displacement Algorithm” based on an accelerometer to see whether a potential temperature rise can be attributed to physical activity. The people responsible for the person in quarantine can then connect via nRF Connect or a similar central application to acquire an accurate picture of the person’s condition. This experiment included an Arduino Nano BLE 33 Sense which contains several other sensors like a 9-axis IMU, several types of temperature, and ambient and other sensors equipped. This device successfully managed to measure wrist temperature at all states, ranging from 32 °C initially to 39 °C, providing better battery autonomy than other similar devices, lasting over 12 h, with fast charging capabilities (500 mA), and utilizing the BLE 5.0 protocol for data wireless data transmission and low power consumption. Furthermore, a 1D Convolutional Neural Network (CNN) was employed to classify whether the user is feverish while considering the physical activity status. The results obtained from the 1D CNN illustrated the manner in which it can be leveraged to acquire insight regarding the health of the users in the setting of the COVID-19 pandemic. View Full-Text
Keywords: COVID-19; body temperature; wearable devices; 9-axis IMU; temperature sensors; indoor condition; activity recognition; BLE; Arduino nano 33 BLE sense COVID-19; body temperature; wearable devices; 9-axis IMU; temperature sensors; indoor condition; activity recognition; BLE; Arduino nano 33 BLE sense
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MDPI and ACS Style

Daskalos, A.-C.; Theodoropoulos, P.; Spandonidis, C.; Vordos, N. Wearable Device for Observation of Physical Activity with the Purpose of Patient Monitoring Due to COVID-19. Signals 2022, 3, 11-28. https://doi.org/10.3390/signals3010002

AMA Style

Daskalos A-C, Theodoropoulos P, Spandonidis C, Vordos N. Wearable Device for Observation of Physical Activity with the Purpose of Patient Monitoring Due to COVID-19. Signals. 2022; 3(1):11-28. https://doi.org/10.3390/signals3010002

Chicago/Turabian Style

Daskalos, Angelos-Christos, Panayiotis Theodoropoulos, Christos Spandonidis, and Nick Vordos. 2022. "Wearable Device for Observation of Physical Activity with the Purpose of Patient Monitoring Due to COVID-19" Signals 3, no. 1: 11-28. https://doi.org/10.3390/signals3010002

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