Startup Ideas AI

This project proposes an AI-driven solution that leverages machine learning to identify early markers of silent neurological disorders such as Parkinson’s disease or Alzheimer’s based on subtle speech, handwriting, or gait abnormalities. The system would collect multimodal data (voice recordings, writing samples, motion sensor inputs), extract features, and use classification algorithms (like SVM or deep learning models) to detect early-stage symptoms.

The model’s uniqueness lies in combining non-invasive data sources and passive monitoring, enabling timely detection before clinical symptoms become prominent. The potential for college-level patentability lies in the novel integration of data modalities and real-time mobile deployment.

Ideal for research, clinical trials, and integration with telehealth platforms.