• digital health •

member of:

  • To assist elders, chronic or short-term patients.
  • Remotely monitor patients’ daily activity.
  • Detect anomalous situations.
  • Trigger warnings and alarms to caregivers.
  • Supply safety, comfort and wellbeing to patients.
  • Capture 24/7 vitals to complete medical records .
  • Assist medical staff with remote supervision.
  • Use of wearables and unobtrusive sensors.
  • Foster early disease detection.
  • Release sanitary and hospital workload.

• how we do it •

smart environments

security and safety

  • When the person leaves home or returns.
  • Real-time location of the person and time spent in a concrete location.
  • Fire, smoke, flood.
  • If other people access home.


  • Notifications 24/7 about anomalous situations.
  • Deviations against daily routines (habits).
  • Air quality (CO2, CO).
  • If the person wakes up and follows a normal pattern.
  • If the person eats warm hot meals.


  • Remote management and automation of heating and air conditioning.
  • Control of blinds and curtains.
  • Schedule automation routines for illumination.
  • Energy consumption and savings.
smart monitoring

ADL monitoring

  • Monitor activities and habits of everyday life.
  • Eating, sleeping, bathing, toileting, socialization…
  • Deviations and trends related to mood and quality of life.

unobtrusive sensing

  • Use of unobtrusive and non-invasive technologies.
  • Infrared, radio frequency, audio, gas sensors.
  • Preserve daily habits and avoid user operation.

physiological sensors

  • Use of medical devices to track biomarkers.
  • Assist medical staff with everyday information.
  • Early symptoms detection for disease diagnosis.

• our platform •

A platform to supply a continuous and sustained care and improvement to patients when combined with the adequate protocols and services.

A platform that can be supplied as an interoperable middleware or as a complete bottom-up solution.

• projects •


Novel unobtrusive physiology and activity monitoring technologies for a better understanding of healthy ageing processes


Creation of trainable knowledge models that benefit from a personalised and precise integration of air quality data acquisition with the real-time evolution of physiological parameters in the development of several breathing disorders


Effects of the daily exposition to some prevalent atmospheric pollutants on patients with COVID-19 and other high-risk respiratory diseases, such as COPD and asthma


Cutting-edge unobtrusive sensing technologies and advanced AI techniques to create a health monitoring system enabling early prediction of Diabetes Mellitus, Congestive Heart Failure and related diseases


Monitoring of Activities of Daily Living (ADL) of elders living alone at home, using gas sensors and applied AI to design identification algorithms through ML techniques

core one

Use of graphene sensor networks in Ambient Assisted Livings environment to detect human activities, and integration into a monitoring system to feed AI and decision support algorithms


Intelligent video-surveillance integrated into a monitoring system to identify daily activity of people and supply advanced security