Olli Lahdenoja
Dr. Sc. (Tech)
olanla@utu.fi Vesilinnantie 5 Turku Office: 454A ORCID identifier: https://orcid.org/0000-0003-2081-600X |
Biomedical Engineering; Computer Vision
Olli Lahdenoja received the M.Sc. and D.Sc. (Tech) degrees from the University of Turku, Finland, in 2003 and 2015, respectively, where he is currently a Senior Researcher in the Health Technology group, Department of Computing, Faculty of Technology. His research interests include biomedical signal processing, biomedical engineering and computer vision. He has also worked at several research projects related to a concrete implementation of embedded systems related to these areas. He has published several international peer-reviewed journal and conference articles. He is currently working part-time at Precordior Ltd.
Biomedical engineering:
- Seismocardiography (SCG)
- Gyrocardiography (GCG)
- Ballistocardiography (BCG)
- Electrocardiography (ECG)
- Clinical trials: atrial fibrillation (AF), heart failure (HF), coronary artery disease (CAD)
Computer vision:
- Local binary patterns (LBP)
- Face recognition
- Real-time machine vision (including industrial)
Dr. Sc. Thesis: "Local Binary Patterns in Focal-Plane Processing - Analysis and Applications" (2015)
Analog IC design / Mixed-Mode IC design (2005-2010)
- Cardiac monitoring of dogs via smartphone mechanocardiography: a feasibility study (2019)
- BioMedical Engineering OnLine
(A1 Refereed original research article in a scientific journal) - Comprehensive Analysis of Cardiogenic Vibrations for Automated Detection of Atrial Fibrillation Using Smartphone Mechanocardiograms (2019)
- IEEE Sensors Journal
(A1 Refereed original research article in a scientific journal) - Embedded processing methods for on-line visual analysis of laser welding (2019)
- Journal of Real-Time Image Processing
(A1 Refereed original research article in a scientific journal) - Head Pulsation Signal Analysis for 3-Axis Head-Worn Accelerometers (2019)
- Computing in Cardiology
(A4 Refereed article in a conference publication ) - Reliability of Self-Applied Smartphone Mechanocardiography for Atrial Fibrillation Detection (2019)
- IEEE Access
(A1 Refereed original research article in a scientific journal) - Stand-alone Heartbeat Detection in Multidimensional Mechanocardiograms (2019)
- IEEE Sensors Journal
(A1 Refereed original research article in a scientific journal) - Atrial Fibrillation Detection via Accelerometer and Gyroscope of a Smartphone (2018)
- IEEE Journal of Biomedical and Health Informatics
(A1 Refereed original research article in a scientific journal) - Machine Learning Based Classification of Myocardial Infarction Conditions Using Smartphone-derived Seismo- and Gyrocardiography (2018)
- Computing in Cardiology
(A4 Refereed article in a conference publication ) - MOBILE PHONE DETECTION OF ATRIAL FIBRILLATION: THE MODE-AF STUDY (2018)
- Journal of the American College of Cardiology
(Other publication) - Mobile Phone Detection of Atrial Fibrillation With Mechanocardiography The MODE-AF Study (Mobile Phone Detection of Atrial Fibrillation) (2018)
- Circulation
(B1 Non-refereed article in a scientific journal)



