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H

HUINNO

Huinno combines wearable ECG monitoring devices with AI-based analytics to detect and prevent chronic cardiac conditions such as arrhythmia, stroke, and hypertension. Their technology enhances patient care by providing real-time data analysis and diagnostic support for healthcare professionals.

Founded 201446700+ followers
Updated 4 months ago

Funding

$36.6M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.

Funding rounds are not available yet.

Founders

Product

Problem

Diagnosing and managing chronic cardiac conditions like arrhythmia, stroke, and hypertension often require frequent and convenient ECG monitoring, which can be challenging with traditional clinic-based equipment. Analyzing the large volumes of ECG data generated also poses a significant burden on healthcare professionals.

Solution

Huinno offers a wearable ECG monitoring solution combined with AI-powered analytics to facilitate the detection and prevention of chronic cardiac conditions. The MEMO solution includes a wearable patch for convenient ECG monitoring, a medical staff application for device and patient management, and a cloud-based system for remote monitoring and AI-assisted analysis. The platform aims to improve the efficiency of cardiac monitoring and provide diagnostic support to healthcare professionals through automated analysis of ECG data.

Target Audience

The primary target audience includes healthcare professionals, such as cardiologists and general practitioners, as well as hospitals and clinics seeking to improve cardiac monitoring and diagnostic efficiency.

Features

  • MEMO Patch 2: A wearable ECG patch for continuous heart rhythm monitoring.
  • Medical Staff App: A mobile application for healthcare providers to manage devices and patient data.
  • MEMO Care: A patient management system for tracking and reviewing ECG data.
  • MEMO Report: Automated generation of ECG reports with AI-based analysis.
  • AI-powered arrhythmia detection algorithm, validated in the PhysioNet AI Challenge.
  • Cloud-based remote monitoring capabilities for continuous data access and analysis.
This profile is AI-generated and may contain inaccuracies.