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 Time Intervals Derived from Electrocardiography and Seismocardiography in Different Patient Groups (2022)
- Computing in Cardiology
(Refereed article in conference proceedings (A4)) - Mechanocardiography-Based Measurement System Indicating Changes in Heart Failure Patients during Hospital Admission and Discharge (2022)
- Sensors
(Refereed journal article or data article (A1)) - Mechanocardiography in the Detection of Acute ST Elevation Myocardial Infarction: The MECHANO-STEMI Study (2022)
- Sensors
(Refereed journal article or data article (A1)) - Multichannel Bed Based Ballistocardiography Heart Rate Estimation Using Continuous Wavelet Transforms and Autocorrelation (2022)
- Computing in Cardiology
(Refereed article in conference proceedings (A4)) - CardioSignal Smartphone Application Detects Atrial Fibrillation in Heart Failure Population (2021)
- Circulation
(Other (O2)) - Detecting Aortic Stenosis Using Seismocardiography and Gryocardiography Combined with Convolutional Neural Networks (2021)
- Computing in Cardiology
(Refereed article in conference proceedings (A4)) - Classification of Atrial Fibrillation and Acute Decompensated Heart Failure Using Smartphone Mechanocardiography: A Multi-label Learning Approach (2020)
- IEEE Sensors Journal
(Refereed journal article or data article (A1)) - Atrial Fibrillation Detection Using MEMS Accelerometer Based Bedsensor (2019)
- Computing in Cardiology
(Refereed article in conference proceedings (A4)) - Cardiac monitoring of dogs via smartphone mechanocardiography: a feasibility study (2019)
- BioMedical Engineering OnLine
(Refereed journal article or data article (A1)) - Comprehensive Analysis of Cardiogenic Vibrations for Automated Detection of Atrial Fibrillation Using Smartphone Mechanocardiograms (2019)
- IEEE Sensors Journal
(Refereed journal article or data article (A1)) - Embedded processing methods for on-line visual analysis of laser welding (2019)
- Journal of Real-Time Image Processing
(Refereed journal article or data article (A1)) - Head Pulsation Signal Analysis for 3-Axis Head-Worn Accelerometers (2019)
- Computing in Cardiology
(Refereed article in conference proceedings (A4)) - Reliability of Self-Applied Smartphone Mechanocardiography for Atrial Fibrillation Detection (2019)
- IEEE Access
(Refereed journal article or data article (A1)) - Stand-alone Heartbeat Detection in Multidimensional Mechanocardiograms (2019)
- IEEE Sensors Journal
(Refereed journal article or data article (A1)) - Atrial Fibrillation Detection via Accelerometer and Gyroscope of a Smartphone (2018)
- IEEE Journal of Biomedical and Health Informatics
(Refereed journal article or data article (A1)) - Machine Learning Based Classification of Myocardial Infarction Conditions Using Smartphone-derived Seismo- and Gyrocardiography (2018)
- Computing in Cardiology
(Refereed article in conference proceedings (A4)) - MOBILE PHONE DETECTION OF ATRIAL FIBRILLATION: THE MODE-AF STUDY (2018)
- Journal of the American College of Cardiology
(Other (O2)) - Mobile Phone Detection of Atrial Fibrillation With Mechanocardiography The MODE-AF Study (Mobile Phone Detection of Atrial Fibrillation) (2018)
- Circulation
(Article or data-article in scientific journal (B1)) - Multiclass Classifier based Cardiovascular Condition Detection Using Smartphone Mechanocardiography (2018)
- Scientific Reports
(Refereed journal article or data article (A1)) - A Smartphone-only Solution for Detecting Indications of Acute Myocardial Infarction (2017) Biomedical & Health Informatics (BHI), 2017 IEEE EMBS International Conference on Lähdenoja O, Koivisto T, Tadi MJ, Iftikhar Z, Hurnanen T, Vasankari T, Kiviniemi T, Airaksinen J, Pänkäälä M
(Refereed article in conference proceedings (A4))