Humeds
Developer of a portable, hand-held device and supporting software for short-duration, medical‑grade 3‑lead ECG acquisition. The system integrates dry‑electrode sensing, on‑device signal conditioning, mobile app connectivity, cloud processing and machine‑learning algorithms for automated arrhythmia detection and remote clinician/patient communication. The product and platform are described as clinically validated and intended for patient self‑monitoring, clinician review and population screening use cases.
Industries
Nr. of Employees
small (1-50)
Humeds
Products
Portable 3‑lead ECG device
Hand‑held, battery‑powered device that records a 3‑lead ECG via dry electrodes and transmits recordings to a mobile app for cloud processing and clinical review.
Portable 3‑lead ECG device
Hand‑held, battery‑powered device that records a 3‑lead ECG via dry electrodes and transmits recordings to a mobile app for cloud processing and clinical review.
Services
Practitioner monitoring platform
Cloud/web platform for clinicians to register consenting patients, view and analyse multiple ECG recordings, visualise signals and communicate with patients.
Consumer mobile app and cloud analytics (Basic and Premium tiers)
Mobile application that connects to the device, uploads recordings to the cloud for automated analysis, offers long‑term storage and configurable sharing; additional analytics and storage offered via a premium subscription.
Practitioner monitoring platform
Cloud/web platform for clinicians to register consenting patients, view and analyse multiple ECG recordings, visualise signals and communicate with patients.
Consumer mobile app and cloud analytics (Basic and Premium tiers)
Mobile application that connects to the device, uploads recordings to the cloud for automated analysis, offers long‑term storage and configurable sharing; additional analytics and storage offered via a premium subscription.
Expertise Areas
- Remote ECG monitoring and telecardiology
- Arrhythmia detection and screening
- Mobile health application development
- Machine learning for clinical signal analysis
Key Technologies
- 3‑lead electrocardiography
- Dry electrode sensing
- Signal filtering and preprocessing
- Machine learning / AI for ECG classification