Shuyi Chen

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+).