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hinlab

Hinlab develops FDA-cleared, wearable smart cuffs for continuous, medical-grade vital signs monitoring of adults and children. These lightweight devices automatically track SpO2, pulse rate, and blood pressure, providing high-frequency physiological data to clinicians. The system enables early detection of patient deterioration in hospital wards, clinical trials, and home settings.

Traction 3/10
Palo Alto, United States · HQ
Founded 201914700+ followers
  • Artificial Intelligence
  • Digital Health
  • Hardware
  • Healthcare Technology
  • Internet of Things
  • Medical Devices
Updated 7 months ago

Funding

Funding rounds are not available yet.

Founders

2 founders

Denys-Michel de Larouzière

Co-Founder/CEO

Jean-Marc Dupuis

Co-Founder/COO

Product

Problem

Infrequent vital signs monitoring can lead to delayed detection of patient deterioration, resulting in preventable deaths and increased healthcare costs. Traditional monitoring methods often lack the efficiency and unobtrusiveness needed for continuous and timely data collection.

Solution

Hinlab develops unobtrusive vital signs monitoring devices that leverage IoT connectivity and AI algorithms to provide real-time alerts for patient deterioration. The devices continuously collect physiological data, enabling healthcare professionals to ensure treatment effectiveness and optimize medication dosages. By using early warning algorithms, Hinlab's technology aims to detect deterioration before it occurs, facilitating timely medical intervention. The devices are designed to meet medical specifications while remaining cost-effective, streamlining workflows for healthcare staff.

Target Audience

The primary users are healthcare professionals, including nurses and doctors, in hospitals and clinics who require continuous and efficient patient monitoring solutions.

Features

  • Continuous physiological measurements and diagnostics
  • Real-time alerts for patient deterioration
  • Cloud-based data collection compliant with data privacy standards
  • Early warning algorithms for proactive detection of health issues
  • Wireless connectivity via Internet of Things (IoT)
  • Integration of hardware and software components
  • Application of Artificial Intelligence (AI) for data analysis and prediction
This profile is AI-generated and may contain inaccuracies.