NeuroSense
Talon Chaulklin Browning, Reina Howell, Peter Bacalzo, Citlalli Esmeralda Acevedo-Adame
School of Engineering
Faculty Supervisor: Kenya Z. Mejia
Individuals living with anxiety and seizure disorders often experience sudden, unpredictable episodes that can limit independence and create persistent fear in daily life. While many wearable devices monitor heart rate, few incorporate multi-sensor data collection and real-time feedback necessary for early detection and timely intervention. This project addresses that gap through the development of a discreet, wrist-worn wearable capable of continuously monitoring physiological indicators such as heart rate, skin conductance, and abnormal motion patterns.
The device compares collected bio signals against individualized baseline data and predefined thresholds to identify patterns associated with the onset of anxiety or seizure episodes. When irregularities are detected, the system delivers targeted haptic feedback to either calm or stimulate the user, while also sending a notification via Bluetooth communication.
Design decisions were informed by sensor performance data from SparkFun, Adafruit, and Arduino documentation, focusing on accuracy and response times. User survey feedback further highlighted the importance of expanded outreach to individuals with seizure disorders. By integrating multi-sensor acquisition, real-time processing, and haptic intervention into a smartwatch-sized device, this project aims to enhance user safety, awareness, and independence.