Biosignal Extraction and Analysis from Remote Video: Towards Real-world Implementation and Diagnosis Support

Thesis event information

Date and time of the thesis defence

Place of the thesis defence

IT116, Linnanmaa

Topic of the dissertation

Biosignal Extraction and Analysis from Remote Video: Towards Real-world Implementation and Diagnosis Support

Doctoral candidate

Master of Science Constantino Álvarez Casado

Faculty and unit

University of Oulu Graduate School, Faculty of Information Technology and Electrical Engineering, Center for Machine Vision and Signal Analysis (CMVS)

Subject of study

Computer Science and Engineering


Docent Jorma Laaksonen, Aalto University


Associate professor Miguel Bordallo López, University of Oulu

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Remote health monitoring: assistive diagnosis support through video analysis

Healthcare today is grappling with big issues like caring for more elderly people, a shortage of medical staff, and the challenges of providing care in remote and less populated areas. However, there is promising news. Breakthroughs in smart video technology, driven by computer vision and artificial intelligence, are opening up new possibilities to support healthcare professionals.

This research focuses on how we can harness video technology to detect vital health signs in a patient-friendly, non-intrusive way. We are working to improve the reliability and accuracy of two key techniques, remote photoplethysmography (rPPG) and remote ballistography (rBSG). These methods use camera feeds and video connections to help doctors identify signs of stress, depression, and respiratory illnesses, all without physical contact with the patient.

A major aim is to integrate these advanced tools seamlessly into real healthcare environments, taking into account the constraints of network and computing resources. This thesis delves into these challenges, seeking practical ways to make these technologies work effectively.

The ultimate goal is clear: to enhance healthcare accessibility and quality for all. By advancing how we diagnose and monitor health conditions through video technology, we aim to provide doctors with powerful, contactless tools that complement traditional methods and enrich the information available to them.
Last updated: 23.1.2024