Neuro Help
Developer of a home-based, AI-powered wearable EEG monitoring system that combines multi-sensor hardware, real-time signal processing, and cloud-based analytics to detect and predict seizures and support remote neurological care. The organization conducts clinical validation studies with medical centers and emphasizes overnight, long-term monitoring, low false alarm rates, and user-friendly self-installation.
Industries
Nr. of Employees
small (1-50)
Products
Wearable AI-powered EEG monitoring system
A home-use headband combining eight dry-contact EEG electrodes with integrated heart rate, motion, and temperature sensors plus AI models for seizure detection and prediction and cloud-based analytics.
EpiNess™
A revolutionary home EEG monitoring device that combines advanced EEG monitoring with AI-powered engineering to provide a comprehensive solution for neurological care.
Wearable AI-powered EEG monitoring system
A home-use headband combining eight dry-contact EEG electrodes with integrated heart rate, motion, and temperature sensors plus AI models for seizure detection and prediction and cloud-based analytics.
EpiNess™
A revolutionary home EEG monitoring device that combines advanced EEG monitoring with AI-powered engineering to provide a comprehensive solution for neurological care.
Services
Design and execution support for clinical studies evaluating wearable EEG hardware and seizure detection/prediction algorithms in partnership with medical centers.
Cloud-synced mobile application and clinician dashboard providing real-time alerts, longitudinal EEG reports, and data visualization for remote care.
Design and execution support for clinical studies evaluating wearable EEG hardware and seizure detection/prediction algorithms in partnership with medical centers.
Cloud-synced mobile application and clinician dashboard providing real-time alerts, longitudinal EEG reports, and data visualization for remote care.
Expertise Areas
- Wearable neurotechnology
- EEG signal analysis
- Seizure detection and prediction
- Machine learning for biosignals
Key Technologies
- Wearable EEG (dry electrodes)
- Multimodal physiological sensing (HR, motion, temperature)
- Real-time signal processing
- Machine learning / predictive analytics
News & Updates
Clinical validation of wearable device and detection algorithm including 30 patients (study start reported).
Software evaluation using clinical EEG data including 100 patients (study start reported).
Discussion of the shift toward home EEG monitoring and validation of lightweight headbands for sleep and epilepsy care.
Overview of the role of wearable devices in epilepsy monitoring, night-use monitoring risks, and demand for continuous remote monitoring.
Peer-reviewed research demonstrating that a selected subset of eight electrodes can approach full clinical EEG performance, guiding wearable design choices.
Company post describing participation in a remembrance initiative and organizational values.
Clinical validation of wearable device and detection algorithm including 30 patients (study start reported).
Software evaluation using clinical EEG data including 100 patients (study start reported).
Discussion of the shift toward home EEG monitoring and validation of lightweight headbands for sleep and epilepsy care.
Overview of the role of wearable devices in epilepsy monitoring, night-use monitoring risks, and demand for continuous remote monitoring.
Peer-reviewed research demonstrating that a selected subset of eight electrodes can approach full clinical EEG performance, guiding wearable design choices.
Company post describing participation in a remembrance initiative and organizational values.