• The ENORA Unobtrusive Sleep Monitoring and Assessment AI-driven platform, with its user-friendly interface and advanced visualization techniques, transforms raw data into a narrative of nightly rest.
  • A pre-trained machine learning model that has been tuned for sleep stages classification employing wearable originated data.
  • The HECA, a dedicated medical CA, is designed to assist the user through medical queries and provide him/her with reliable and accurate responses. Utilizing sophisticated Natural Language Processing…
  • A computer vision application that has been trained to recognise the mood of the user given their facial expression. The model has been developed to run as a background service of other mobile…
  • Make predictions about a future health status of PMSS (Parkinson’s Disease, Multiple Sclerosis and Stroke) patients, given a history of tracked predictor variables.
  • Developed to detect activities of daily living (ADLs) using acceleration data obtained from wearable inertial sensors.