Remote Vitals Tracking and Stress Detection from Facial Video
Key Expertise
Experience
8+ years
Timezone
CET (UTC +1)
Skills
AI / ML
Languages
Databases
Infrastructure
Frameworks
Overview
The project involved leading the scientific research and development of a camera-based health monitoring solution for remote vital signs tracking and stress detection. The system was designed to extract physiological signals directly from facial video and support health and wellness applications through non-contact monitoring. The work combined medical research, signal processing, healthcare analytics, and machine learning to build scalable algorithms for real-world device environments.
Achievements
Led the scientific direction of remote vitals and stress detection research for medical and wellness applications. Built robust algorithmic approaches for extracting and analyzing physiological indicators from video streams. Supported scalable AI deployment across multiple device types and research settings while collaborating with universities, clinics and scientific organizations.
Responsibilities
- Designed and led scientific research initiatives for camera-based vital signs monitoring and stress detection.
- Developed algorithms for biomedical signal extraction, time series analysis, anomaly detection, and pattern recognition, clinical data analysis.
- Worked with EHR, biomarkers, lifestyle data, biometrics, and physiological monitoring data to support research hypotheses.
- Conducted statistical analysis, medical data interpretation, and research validation for healthcare use cases.
- Collaborated with university research teams and scientific organizations on medical R&D activities.
- Mentoring and managing the interns
- Produced scientific reports, stakeholder materials, and research documentation.
Technologies Used
Key Expertise
Experience
8+ years
Timezone
CET (UTC +1)
Skills
AI / ML
Languages
Databases
Infrastructure
Frameworks
This project was delivered by
Oleksandra K.
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