A Smart-Fabric Wearable System for Continuous Physiological Monitoring and Human Activity Recognition
M. Rajani, Naveen Ghorpade, Ajay Sudhir BaleIntroduction:
Continuous monitoring of physiological parameters and physical activities plays an important role in modern healthcare, remote patient monitoring, rehabilitation, and elderly care. Advances in wearable technologies and smart textiles have enabled the integration of sensing, communication, and data processing capabilities into wearable platforms.
Methods:
This work presents a Smart-Fabric-based Body Area Sensor Network (BASN) architecture for continuous physiological monitoring and human activity recognition. The proposed framework integrates textile-compatible sensing modules, including heart-rate monitoring, respiration sensing, blood oxygen saturation (SpO2) monitoring, body-temperature sensing, and inertial measurement units (IMUs). An ESP32-based embedded platform is employed for signal acquisition, preprocessing, and wireless data transmission through Bluetooth Low Energy (BLE). Activity recognition is evaluated using machine-learning classifiers, including Random Forest, SVM, and XGBoost.
Results:
The proposed BASN framework integrates physiological sensing, activity monitoring, embedded processing, wireless communication, and cloud-based monitoring within a unified wearable architecture. Activity recognition was evaluated using the publicly available UCI Human Activity Recognition (HAR) dataset, which contains 10,299 samples from six daily activities. Experimental evaluation demonstrated classification accuracies of 92.87%, 95.05%, and 93.55% with Random Forest, SVM, and XGBoost, respectively.
Discussion:
The proposed architecture provides a scalable framework for combining multimodal physiological sensing and activity recognition within a wearable healthcare platform. The integration of sensing, communication, and data analytics supports continuous monitoring and remote healthcare applications.
Conclusion:
The presented Smart-Fabric BASN demonstrates the feasibility of integrating physiological monitoring, activity recognition, wireless communication, and cloud connectivity into a unified wearable system. The proposed framework can support future developments in remote healthcare, rehabilitation monitoring, elderly care, and personalized health-management applications.