CAU proudly celebrates a significant milestone in interdisciplinary innovation. Prof. Niladri Maiti, Dean of the School of Dentistry, has co-authored a pivotal chapter published in ScienceDirect (2026) titled:
“Machine Learning-Based Gait Freezing Detection and Classification in Parkinson’s Patients Using Biometric Insights” featured in Recent Advances in Computational Intelligence Applications for Biometrics and Biomedical Devices.
“Machine Learning-Based Gait Freezing Detection and Classification in Parkinson’s Patients Using Biometric Insights” featured in Recent Advances in Computational Intelligence Applications for Biometrics and Biomedical Devices.
This research introduces an advanced AI-driven system designed to detect and classify freezing of gait (FoG)—a common and debilitating symptom in Parkinson’s disease. Leveraging wearable sensor data, the team developed machine learning models capable of analyzing gait patterns and identifying FoG episodes in real time. Techniques such as Support Vector Machines (SVM), Random Forest, and Convolutional Neural Networks (CNN) demonstrated high accuracy in recognizing gait irregularities, enabling more timely clinical responses and paving the way for personalized treatment strategies.
Key Contributions of the Study
- Development of machine learning models tailored for gait pattern recognition in Parkinson’s patients
- Feature selection and data reduction techniques to enhance classification accuracy and computational efficiency
- Exploration of real-time monitoring solutions, including wearable devices and mobile health technologies, for continuous patient support
This achievement underscores CAU’s dedication to cutting-edge research, cross-disciplinary collaboration, and the advancement of biomedical technologies that improve patient outcomes. Through innovations like this, CAU continues to contribute meaningfully to the future of AI-driven healthcare.
