TY - GEN
T1 - A Pilot mHealth Project for Monitoring Vital Body Signals and Skin Conditions
AU - Tchema, Rodrigue B.
AU - Tzavellas, Georgios
AU - Nestoros, Marios
AU - Polycarpou, Anastasis C.
N1 - Funding Information:
Acknowledgments. The authors would like to thank the University of Nicosia for their financial support of the project.
Publisher Copyright:
© 2022, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.
PY - 2022
Y1 - 2022
N2 - In this paper, we present a pilot project on mobile health (mHealth) which is designed to monitor on a continuous basis the health condition of individuals using a mobile device such as a smartphone or a tablet. The objectives of this pilot project include highly accurate calculation of heart-beat rate using either a smartphone camera or an autonomous, self-powered mini-device which communicates measurement data to the mobile device through Bluetooth or Wi-Fi. In addition, we aim at detecting potentially dangerous skin conditions at an early stage using the smartphone camera and machine learning (ML) or deep learning (DL) algorithms. The trained algorithm will be able to detect malignant cases of skin conditions by searching through various built-in categories of commonly found skin disorders.
AB - In this paper, we present a pilot project on mobile health (mHealth) which is designed to monitor on a continuous basis the health condition of individuals using a mobile device such as a smartphone or a tablet. The objectives of this pilot project include highly accurate calculation of heart-beat rate using either a smartphone camera or an autonomous, self-powered mini-device which communicates measurement data to the mobile device through Bluetooth or Wi-Fi. In addition, we aim at detecting potentially dangerous skin conditions at an early stage using the smartphone camera and machine learning (ML) or deep learning (DL) algorithms. The trained algorithm will be able to detect malignant cases of skin conditions by searching through various built-in categories of commonly found skin disorders.
KW - Deep learning algorithms
KW - Heart-beat rate detection
KW - Skin disorder diagnosis
UR - http://www.scopus.com/inward/record.url?scp=85133010220&partnerID=8YFLogxK
U2 - 10.1007/978-3-031-06368-8_18
DO - 10.1007/978-3-031-06368-8_18
M3 - Conference contribution
AN - SCOPUS:85133010220
SN - 9783031063671
T3 - Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST
SP - 270
EP - 280
BT - Wireless Mobile Communication and Healthcare - 10th EAI International Conference, MobiHealth 2021, Proceedings
A2 - Gao, Xinbo
A2 - Jamalipour, Abbas
A2 - Guo, Lei
PB - Springer Science and Business Media Deutschland GmbH
T2 - 10th EAI International Conference on Wireless Mobile Communication and Healthcare, MobiHealth 2021
Y2 - 13 November 2021 through 14 November 2021
ER -