AWEAR offers a continuous‑wear ear‑cuff that captures dry‑electrode EEG signals and processes them on‑device to deliver real‑time stress, focus, and emotion metrics via a mobile app. The platform combines cloud‑based machine‑learning analytics with AI‑generated coaching to provide neurofeedback and automated emotional logs for professionals and wellness users. The device is FDA‑compliant, encrypted and designed for all‑day comfort.
Funding
Funding not disclosed
Founders
Product
Problem
Many professionals and health‑conscious individuals lack a convenient way to continuously monitor their mental state, resulting in delayed awareness of stress spikes, focus lapses, and emotional dysregulation. Existing solutions are either clinical‑grade EEG systems that are bulky and require specialist setup, or generic wellness apps that rely on self‑reporting and lack objective physiological data.
Solution
AWEAR delivers an all‑day wearable ear‑cuff that integrates a miniature dry‑electrode EEG sensor with on‑device signal preprocessing and cloud‑based machine‑learning analytics. The system translates raw brainwave patterns into real‑time metrics for stress, focus, and emotional valence, which are displayed on a companion mobile app. Users receive immediate neurofeedback, an automatically generated emotional log that aligns physiological events with daily activities, and personalized coaching tips generated by AI models trained on large psychophysiology datasets. The device’s sleek, customizable form factor makes continuous wear comfortable, enabling proactive self‑regulation without disrupting daily routines.
Target Audience
The primary customers are high‑performance professionals, wellness‑focused consumers, and corporate wellness programs that seek objective, continuous mental‑state monitoring and actionable feedback.
Features
- Compact ear‑cuff housing a low‑power ASIC and dry‑electrode EEG sensor for continuous, artifact‑robust brainwave acquisition
- Edge preprocessing pipeline that filters, segments, and extracts spectral features before secure transmission to the cloud
- Proprietary machine‑learning models that map EEG features to quantitative stress, focus, and emotion scores in real time
- Mobile app dashboard with live metric visualizations, trend graphs, and push notifications for moment‑to‑moment neurofeedback
- Automated emotional log that timestamps physiological events and correlates them with calendar entries, location data, and activity tags
- AI‑driven personalized coaching engine that delivers habit‑building recommendations, breathing exercises, and focus techniques tailored to the user’s profile
- Interchangeable finishes and color options for style customization while maintaining FDA‑compliant biocompatible materials
- End‑to‑end encryption and role‑based access controls to ensure data privacy and compliance with health‑information regulations