Matti Kaisti
mkaist@utu.fi +358 44 533 4238 Vesilinnantie 5 Turku |
medical instrumentation, biosignal analytics, clinical machine learning
I work in biomedical engineering to develop disease monitoring systems. By applying signal processing and AI to novel sensory data, I aim to create clinically validated solutions that integrate technologies across various maturity levels.
I currently teach Analytics of Health Wearables, an advanced engineering course focused on programming and algorithms, and Introduction to Health Technology, an entry-level course."
- Disposable silicon-based all-in-one micro-qPCR for rapid on-site detection of pathogens (2020)
- Nature Communications
- Multi-Wavelength Photoplethysmography Device for the Measurement of Pulse Transit Time in the Skin Microvasculature (2020)
- Computing in Cardiology
- Stretchable Composite Acoustic Transducer for Wearable Monitoring of Vital Signs (2020)
- Advanced Functional Materials
- An Automated Device for Recording Peripheral Arterial Waveform (2019)
- Computing in Cardiology
- Atrial Fibrillation Detection Using MEMS Accelerometer Based Bedsensor (2019)
- Computing in Cardiology
- Cardiac monitoring of dogs via smartphone mechanocardiography: a feasibility study (2019)
- BioMedical Engineering OnLine
- Clinical assessment of a non-invasive wearable MEMS pressure sensor array for monitoring of arterial pulse waveform, heart rate and detection of atrial fibrillation (2019)
- npj Digital Medicine
- Comprehensive Analysis of Cardiogenic Vibrations for Automated Detection of Atrial Fibrillation Using Smartphone Mechanocardiograms (2019)
- IEEE Sensors Journal
- Head Pulsation Signal Analysis for 3-Axis Head-Worn Accelerometers (2019)
- Computing in Cardiology
- Stand-alone Heartbeat Detection in Multidimensional Mechanocardiograms (2019)
- IEEE Sensors Journal



