Matti Kaisti
Assistant Professor
mkaist@utu.fi +358 44 533 4238 Vesilinnantie 5 Turku |
sensors, wearables, machine learning, physiology
medical instrumentation, physiological monitoring, biosignal analytics, clinical machine learning
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.
I am currently responsible for teaching Programming and Analytics of Health Wearables, an advanced level engineering course.
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- Bed sensor ballistocardiogram for non-invasive detection of atrial fibrillation: a comprehensive clinical study (2025)
- Physiological Measurement
- Continuous Radar-based Heart Rate Monitoring using Autocorrelation-based Algorithm in Intensive Care Unit (2025)
- IEEE Journal of Biomedical and Health Informatics
- Validation of an MEMS-Based Pressure Sensor System for Atrial Fibrillation Detection from Wrist and Finger (2025)
- IEEE Sensors Journal
- A Modular Framework for the Interpretation of Paper ECGs (2024)
- Computing in Cardiology
- Assessment of ECG Signal Quality Index Algorithms Using Synthetic ECG Data (2024)
- Computing in Cardiology
- Empirical investigation of multi-source cross-validation in clinical ECG classification (2024)
- Computers in Biology and Medicine
- Evaluating Piezoelectric Ballistocardiography for Post-Surgical Heart Rate Monitoring (2024)
- Computing in Cardiology
- Generating Synthetic Mechanocardiograms for Machine Learning Based Peak Detection (2024)
- IEEE Sensors Letters
- Hemodynamic Bedside Monitoring Instrument with Pressure and Optical Sensors : Validation and Modality Comparison (2024)
- Advanced Science
- Investigating the impact of contact pressure on photoplethysmograms (2024)
- Biomedical Engineering Advances
- Low-Cost Tissue Oximetry Using Discrete Light-Emitting Diodes (2024)
- IEEE International Instrumentation and Measurement Technology Conference
- Non-Invasive Hemodynamic Monitoring System Integrating Spectrometry, Photoplethysmography, and Arterial Pressure Measurement Capabilities (2024)
- Advanced Science
- Parallel, Continuous Monitoring and Quantification of Programmed Cell Death in Plant Tissue (2024)
- Advanced Science
- Personalization of Affective Models Using Classical Machine Learning : A Feasibility Study (2024)
- Applied Sciences
- Smartphone-Based Recognition of Heart Failure by Means of Microelectromechanical Sensors (2024)
- JACC: Heart Failure
- Toward Automatic Cardiovascular and Respiratory Assessment Using Automatic 6-Minute Walking Test (2024)
- Proceedings of IEEE Sensors
- Wearable edge machine learning with synthetic photoplethysmograms (2024)
- Expert Systems with Applications
- Advances in non-invasive blood pressure measurement techniques (2023)
- IEEE Reviews in Biomedical Engineering
- Continuous Blood Pressure Monitoring Using Nonpulsatile Photoplethysmographic Components for Low-Frequency Vascular Unloading (2023)
- IEEE Transactions on Instrumentation and Measurement
- Development and clinical validation of a miniaturized finger probe for bedside hemodynamic monitoring (2023)
- iScience
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