Olli Lahdenoja
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Atrial fibrillation detection via accelerometer and gyroscope of a smartphone
O Lahdenoja, T Hurnanen, Z Iftikhar, S Nieminen, T Knuutila, A Saraste, ...
IEEE Journal of Biomedical and Health Informatics 22 (1), 108-118, 2017
Reducing the feature vector length in local binary pattern based face recognition
O Lahdenoja, M Laiho, A Paasio
IEEE International Conference on Image Processing 2005 2, II-914, 2005
Multiclass classifier based cardiovascular condition detection using smartphone mechanocardiography
Z Iftikhar, O Lahdenoja, M Jafari Tadi, T Hurnanen, T Vasankari, ...
Scientific reports 8 (1), 9344, 2018
Mobile phone detection of atrial fibrillation with mechanocardiography: the MODE-AF Study (Mobile Phone Detection of Atrial Fibrillation)
J Jaakkola, S Jaakkola, O Lahdenoja, T Hurnanen, T Koivisto, ...
Circulation 137 (14), 1524-1527, 2018
Towards understanding the formation of uniform local binary patterns
O Lahdenoja, J Poikonen, M Laiho
International Scholarly Research Notices 2013 (1), 429347, 2013
Stand-alone heartbeat detection in multidimensional mechanocardiograms
M Kaisti, MJ Tadi, O Lahdenoja, T Hurnanen, A Saraste, M Pänkäälä, ...
IEEE Sensors Journal 19 (1), 234-242, 2018
Heart Rate Variability Estimation with Joint Accelerometer and Gyroscope Sensing
O Lahdenoja, T Hurnanen, MJ Tadi, M Pänkäälä, T Koivisto
Computing in Cardiology (CinC) 2016, 2016
Classification of atrial fibrillation and acute decompensated heart failure using smartphone Mechanocardiography: a multilabel learning approach
S Mehrang, O Lahdenoja, M Kaisti, MJ Tadi, T Hurnanen, A Airola, ...
IEEE Sensors Journal 20 (14), 7957-7968, 2020
Comprehensive analysis of cardiogenic vibrations for automated detection of atrial fibrillation using smartphone mechanocardiograms
MJ Tadi, S Mehrang, M Kaisti, O Lahdenoja, T Hurnanen, J Jaakkola, ...
IEEE Sensors Journal 19 (6), 2230-2242, 2018
A massively parallel algorithm for local binary pattern based face recognition
O Lahdenoja, J Maunu, M Laiho, A Paasio
2006 IEEE International Symposium on Circuits and Systems, 4 pp., 2006
Dedicated hardware for parallel extraction of local binary pattern feature vectors
M Laiho, O Lahdenoja, A Paasio
2005 9th international workshop on cellular neural networks and their …, 2005
Wearable pressure sensor array for health monitoring
M Kaisti, J Leppänen, O Lahdenoja, P Kostiainen, M Pankaaia, ...
2017 Computing in Cardiology (CinC), 1-4, 2017
Local binary pattern feature vector extraction with CNN
O Lahdenoja, M Laiho, A Paasio
2005 9th International Workshop on Cellular Neural Networks and Their …, 2005
Extracting local binary patterns with MIPA4k vision processor
O Lahdenoja, J Poikonen, M Laiho
2010 12th International Workshop on Cellular Nanoscale Networks and their …, 2010
A smartphone-only solution for detecting indications of acute myocardial infarction
O Lahdenoja, T Koivisto, MJ Tadi, Z Iftikhar, T Hurnanen, T Vasankari, ...
2017 IEEE EMBS International Conference on Biomedical & Health Informatics …, 2017
Detection of atrial fibrillation with seismocardiography
M Pänkäälä, T Koivisto, O Lahdenoja, T Kiviniemi, A Saraste, T Vasankari, ...
2016 38th Annual International Conference of the IEEE Engineering in …, 2016
Machine Learning Based Classification of Myocardial Infarction Conditions Using Smartphone-derived Seismo-and Gyrocardiography
S Mehrang, MJ Tadi, M Kaisti, O Lahdenoja, T Vasankari, T Kiviniemi, ...
Computing in Cardiology (CinC), 2018
A massively parallel face recognition system
O Lahdenoja, M Laiho, J Maunu, A Paasio
EURASIP Journal on Embedded Systems 2007, 1-13, 2006
Online seam tracking for laser welding with a vision chip and FPGA enabled camera system
T Säntti, JK Poikonen, O Lahdenoja, M Laiho, A Paasio
2015 IEEE International Symposium on Circuits and Systems (ISCAS), 1985-1988, 2015
Cardiac monitoring of dogs via smartphone mechanocardiography: a feasibility study
O Lahdenoja, T Hurnanen, M Kaisti, J Koskinen, J Tuominen, ...
BioMedical Engineering OnLine 18, 1-14, 2019
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