Publication Type : Conference Proceedings
Publisher : IEEE
Source : 2025 5th International Conference on Artificial Intelligence and Signal Processing (AISP)
Url : https://doi.org/10.1109/aisp68263.2025.11396267
Campus : Amaravati
School : School of Engineering
Department : Electronics and Communication
Year : 2025
Abstract : Parkinson’s Disease (PD) presents challenges in early detection and monitoring. This paper proposes a deployable IoT–Cloud–Dashboard system integrating voice-based machine learning diagnostics with real-time visualization and clinical alerting. The pipeline includes voice data preprocessing, Random Forest classification, and performance evaluation using accuracy, classification reports, and confusion matrices. Feature importance and SHAP analyses enhance interpretability. A conceptual monitoring module tracks clinical score progression and flags threshold breaches. Results highlight the system’s potential for scalable, non-invasive PD diagnostics and continuous patient monitoring.
Cite this Research Publication : Kamala Duru, Venkata Jahnavi Kosuri, Harika Gadiparthi, Sai Yogita CH, Vineela Chandra Dodda, Lakshmi Kuruguntla, Monitoring Parkinson’s Disease in the IoT-Cloud Framework Using Voice Data with a Random Forest Classifier, 2025 5th International Conference on Artificial Intelligence and Signal Processing (AISP), IEEE, 2025, https://doi.org/10.1109/aisp68263.2025.11396267