Mikko
Pänkäälä
Docent, Department of Computing
Yliopistonlehtori, TkT, dosentti
Areas of expertise
Biosignals
health technology
Biography
I'm a University lecturer at the University of Turku. My background is in automotive engineering and I originally came to study electronics to the UTU at 2001. I started my studies related to electronics an communication technology at the IT-Dept. and finished my M.Sc. studies in 2004 and Lich. tech in 2008. After that I worked in a special unit and graduated as a D.Sc in 2014. From the beginning of 2017 I have worked at the Dept. of Future Technologies.
Teaching
Currently I lecture no courses. Previously lectured courses such as Acquisition and Analysis of Biosignals and Embedde IoT Programming. I have also given single lectures related to health technology with other courses.
Research
Currently my focus is on non-invasive cardiac telemonitoring methods based on motion sensors. I have done research on health technology, mainly related to cardiac monitoring since 2011. Previously my research topics were related to the integrated circuits, e.g in my thesis work I investigated a neural network implemented on silicon.
Publications
Stand-alone Heartbeat Detection in Multidimensional Mechanocardiograms (2019)
IEEE Sensors Journal
(Vertaisarvioitu alkuperäisartikkeli tai data-artikkeli tieteellisessä aikakauslehdessä (A1))
Reliability of Self-Applied Smartphone Mechanocardiography for Atrial Fibrillation Detection (2019)
IEEE Access
(Vertaisarvioitu alkuperäisartikkeli tai data-artikkeli tieteellisessä aikakauslehdessä (A1))
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
(Vertaisarvioitu alkuperäisartikkeli tai data-artikkeli tieteellisessä aikakauslehdessä (A1))
A Computational Framework for Data Fusion in MEMS-Based Cardiac and Respiratory Gating (2019)
Sensors
(Vertaisarvioitu alkuperäisartikkeli tai data-artikkeli tieteellisessä aikakauslehdessä (A1))
Comprehensive Analysis of Cardiogenic Vibrations for Automated Detection of Atrial Fibrillation Using Smartphone Mechanocardiograms (2019)
IEEE Sensors Journal
(Vertaisarvioitu alkuperäisartikkeli tai data-artikkeli tieteellisessä aikakauslehdessä (A1))
Atrial Fibrillation Detection Using MEMS Accelerometer Based Bedsensor (2019)
Computing in Cardiology, Computing in Cardiology
(Vertaisarvioitu artikkeli konferenssijulkaisussa (A4))
Multiclass Classifier based Cardiovascular Condition Detection Using Smartphone Mechanocardiography (2018)
Scientific Reports
(Vertaisarvioitu alkuperäisartikkeli tai data-artikkeli tieteellisessä aikakauslehdessä (A1))
Machine Learning Based Classification of Myocardial Infarction Conditions Using Smartphone-derived Seismo- and Gyrocardiography (2018)
Computing in Cardiology, Computing in Cardiology
(Vertaisarvioitu artikkeli konferenssijulkaisussa (A4))
Atrial Fibrillation Detection via Accelerometer and Gyroscope of a Smartphone (2018)
IEEE Journal of Biomedical and Health Informatics
(Vertaisarvioitu alkuperäisartikkeli tai data-artikkeli tieteellisessä aikakauslehdessä (A1))
Mobile Phone Detection of Atrial Fibrillation With Mechanocardiography The MODE-AF Study (Mobile Phone Detection of Atrial Fibrillation) (2018)
Circulation
(Kirjoitus tai data-artikkeli tieteellisessä aikakauslehdessä (B1))