Tri-Modal Home Kit (Alzheimer’s & Parkinson’s)

Goal:
Design a unified home monitoring system that captures motion, speech, and eye-tracking data to identify early symptoms of neurodegenerative diseases.

Impact:
Alzheimer’s and Parkinson’s often go undiagnosed for years, until irreversible brain changes occur. Clinical detection relies on expensive imaging and specialist visits unavailable to many. This project aims to democratize neurological screening through a wearable device capable of tracking tremors, gait, voice modulation, and eye behavior — key indicators of disease progression.

General Parts & Functionality:
Combines a motion sensor (IMU), microphone, and IR camera to measure motor control, speech coherence, and pupil dynamics — all processed by a Raspberry Pi Zero for phone-based analysis.

Roles Involved:

• Hardware: Integrate multi-modal sensors into compact wearable units.
• Firmware: Ensure time-synchronized data collection and power efficiency.
• AI/ML: Build cross-sensor learning models for tremor and cognitive detection.
• CAD Design: Prototype comfortable wrist and visor enclosures.
• Research/Biology: Define measurable neurophysiological markers of disease.

Benefits:
Promotes early diagnosis and home monitoring, helping slow disease progression through early intervention and allowing clinicians to track patients remotely.