rhBNN+ Comprehensive Detections and Analyses of the Human Body Temperatures and Sounds by the Same Smart Mask

rhBNN+ Comprehensive Detections and Analyses of the Human Body Temperatures and Sounds by the Same Smart Mask

Scholars have recently used various methods to study the human body’s characteristics, propose improvements, and rely on medical data. This research introduces a new real−time data collection and analysis system comprising two components: a smart mask for data collection and a processing unit for an...

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Bibliographic Details
Main Authors: Bingcan Liao, Pin Sun, Shuyi Chen, Rihong Huang, Junyu Yang, Guofeng Li, Chengzhi Lv, Nan Zhu, Shui Guan, Hailong Liu, Rong Liu, Ali Mansouri, Changkai Sun
Format: Article
Language:English
Published: MDPI AG 2023-08-01
Series:Computer Sciences & Mathematics Forum
Subjects:
rhBNN+
smart mask
human body temperatures
human body sounds
support vector machine
Online Access:https://www.mdpi.com/2813-0324/8/1/54
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Summary:Scholars have recently used various methods to study the human body’s characteristics, propose improvements, and rely on medical data. This research introduces a new real−time data collection and analysis system comprising two components: a smart mask for data collection and a processing unit for analysis and storage. The medical mask incorporates four sensors: three heat sensors to measure the nose tip and exhaled air temperature from the nostrils and mouth, along with a microphone for audio data. Collected data is instantly transmitted to the processing unit. Temperature readings are labeled and stored for analysis, while audio data is classified into breathing, coughing, and speaking categories using the Support Vector Machine (SVM) algorithm. The SVM’s performance is further optimized using the Lion Algorithm. Evaluation results indicate satisfactory accuracy for temperature data collected from the mask. The SVM achieved 84.3% accuracy for sound data classification, while the Lion algorithm−optimized SVM achieved an even higher accuracy of 93.6%. Future work aims to establish a reliable data collection tool that will serve as the foundation for developing an intelligent human body analysis model called the real human body neural network (rhBNN+).
ISSN:2813-0324

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