Olli Lahdenoja
Dr. Sc. (Tech)
olanla@utu.fi Vesilinnantie 5 Turku Office: 454A ORCID identifier: https://orcid.org/0000-0003-2081-600X |
Areas of expertise
Biomedical Engineering; Computer Vision
Biomedical Engineering; Computer Vision
Biography
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.
Research
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)
Teaching
Analog IC design / Mixed-Mode IC design (2005-2010)
Publications 
2 of 6
- Generating Synthetic Mechanocardiograms for Machine Learning Based Peak Detection (2024) Sandelin, Jonas; Elnaggar, Ismail; Lahdenoja, Olli; Kaisti, Matti; Koivisto, Tero
(A1 Refereed original research article in a scientific journal) - Mechanocardiography detects improvement of systolic function caused by resynchronization pacing (2023)
- Physiological Measurement
(A1 Refereed original research article in a scientific journal) - Cardiac Time Intervals Derived from Electrocardiography and Seismocardiography in Different Patient Groups (2022)
- Computing in Cardiology
(A4 Refereed article in a conference publication ) - Mechanocardiography-Based Measurement System Indicating Changes in Heart Failure Patients during Hospital Admission and Discharge (2022)
- Sensors
(A1 Refereed original research article in a scientific journal) - Mechanocardiography in the Detection of Acute ST Elevation Myocardial Infarction: The MECHANO-STEMI Study (2022)
- Sensors
(A1 Refereed original research article in a scientific journal) - Multichannel Bed Based Ballistocardiography Heart Rate Estimation Using Continuous Wavelet Transforms and AutocorrelationAtrial Fibrillation Detection Using MEMS Accelerometer Based Bedsensor2022
- Computing in CardiologyComputing in Cardiology
(A4 Refereed article in a conference publication ) - CardioSignal Smartphone Application Detects Atrial Fibrillation in Heart Failure Population (2021)
- Circulation
(Other publication) - Detecting Aortic Stenosis Using Seismocardiography and Gryocardiography Combined with Convolutional Neural Networks (2021)
- Computing in Cardiology
(A4 Refereed article in a conference publication ) - Classification of Atrial Fibrillation and Acute Decompensated Heart Failure Using Smartphone Mechanocardiography: A Multi-label Learning Approach (2020)
- IEEE Sensors Journal
(A1 Refereed original research article in a scientific journal) - (2019)
(A4 Refereed article in a conference publication )
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