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@article{201819,
        author = {Mrs.Vidhya A and Dr.M.Rajaram and Mrs C.Preethibha and Dr.V.Shanthi and Gopinath M and Hiruthika V and Nithya B and Subashini K},
        title = {Multimodal Stress Detection Using Bio signals And Wireless Signals},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {12},
        pages = {4878-4884},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=201819},
        abstract = {Stress is a significant cause of numerous physical and psychological disorders, and there is a need to have dependable and constant monitoring systems. The conventional ways of detecting stress primarily use wearable biosensors or questionnaires that either create discomfort or are subjective in nature and do not have real-time flexibility. In this paper, a new multimodal stress detection model will be suggested, which uses physiological biosignals together with non-invasive monitoring of wireless signal distortion. Galvanic Skin Response (GSR) and Photoplethysmography (PPG) sensors are utilized in order to record the changes in heart rate and skin conductance, whereas WiFi-based Received Signal Strength Indicator (RSSI) and Channel State Information (CSI) measurements are utilized in order to detect the micro-movements due to the stress-induced changes in the wireless channel. The obtained signals are preprocessed and feature extracted and normalized, and then multi-modal data fusion methods are used. To classify the stress levels in real time, a Support Vector Machine (SVM) classifier is used to classify the data in real-time into low, medium, and high. The presented system is more robust and more accurate because it ties together contact-based and contactless sensing modalities. The experimental validation has shown a better reliability, less user discomfort, and efficient monitoring that is found within a 5–10-meter range of wireless sensing, which is also applicable in smart healthcare.},
        keywords = {Multimodal Stress Detection, Biosignals, GSR, PPG, RSSI, CSI, Wireless Sensing, Data Fusion, Support Vector Machine, Non-Intrusive Monitoring.},
        month = {May},
        }