Matti
Kaisti
Assistant Professor, Health Technology
Assistant Professor
medical instrumentation, physiological monitoring, biosignal analytics, clinical machine learning
Links
Areas of expertise
sensors
wearables
machine learning
physiology
Teaching
I am currently responsible for teaching Programming and Analytics of Health Wearables, an advanced level engineering course.
Research
I develop new monitoring solutions for disease prevention and management using new sensory solutions and computational techniques. The research aims for clinically validated solutions and combines technologies at the different maturity levels.
Publications
Continuous Radar-based Heart Rate Monitoring using Autocorrelation-based Algorithm in Intensive Care Unit (2025)
IEEE Journal of Biomedical and Health Informatics
(A1 Vertaisarvioitu alkuperäisartikkeli tieteellisessä lehdessä )
Low-Cost Tissue Oximetry Using Discrete Light-Emitting Diodes (2024)
IEEE Instrumentation and Measurement Technology Conference, IEEE International Instrumentation and Measurement Technology Conference
(A4 Vertaisarvioitu artikkeli konferenssijulkaisussa)
Assessment of ECG Signal Quality Index Algorithms Using Synthetic ECG Data (2024)
Computing in Cardiology, Computing in Cardiology
(A4 Vertaisarvioitu artikkeli konferenssijulkaisussa)
Hemodynamic Bedside Monitoring Instrument with Pressure and Optical Sensors : Validation and Modality Comparison (2024)
Advanced Science
(A1 Vertaisarvioitu alkuperäisartikkeli tieteellisessä lehdessä )
Generating Synthetic Mechanocardiograms for Machine Learning-Based Peak Detection (2024)
IEEE Sensors Letters
(A1 Vertaisarvioitu alkuperäisartikkeli tieteellisessä lehdessä )
Smartphone-Based Recognition of Heart Failure by Means of Microelectromechanical Sensors (2024)
JACC: Heart Failure
(A1 Vertaisarvioitu alkuperäisartikkeli tieteellisessä lehdessä )
Toward Automatic Cardiovascular and Respiratory Assessment Using Automatic 6-Minute Walking Test (2024)
IEEE SENSORS, Proceedings of IEEE Sensors
(A4 Vertaisarvioitu artikkeli konferenssijulkaisussa)
Personalization of Affective Models Using Classical Machine Learning : A Feasibility Study (2024)
Applied Sciences
(A1 Vertaisarvioitu alkuperäisartikkeli tieteellisessä lehdessä )
Generating Synthetic Mechanocardiograms for Machine Learning Based Peak Detection (2024)
(A1 Vertaisarvioitu alkuperäisartikkeli tieteellisessä lehdessä )A Modular Framework for the Interpretation of Paper ECGs (2024)
Computing in Cardiology, Computing in Cardiology
(A4 Vertaisarvioitu artikkeli konferenssijulkaisussa)