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Antti Vehkaoja
Antti Vehkaoja
Tampere University
Verified email at tuni.fi
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Wireless, multipurpose in-home health monitoring platform: two case trials
S Junnila, H Kailanto, J Merilahti, AM Vainio, A Vehkaoja, M Zakrzewski, ...
IEEE Transactions on Information Technology in Biomedicine 14 (2), 447-455, 2009
1252009
Comparison of HRV parameters derived from photoplethysmography and electrocardiography signals
V Jeyhani, S Mahdiani, M Peltokangas, A Vehkaoja
2015 37th annual international conference of the ieee engineering in …, 2015
1102015
Is 50 Hz high enough ECG sampling frequency for accurate HRV analysis?
S Mahdiani, V Jeyhani, M Peltokangas, A Vehkaoja
2015 37th Annual International Conference of the IEEE Engineering in …, 2015
752015
Photoplethysmography and its detailed pulse waveform analysis for arterial stiffness
M Huotari, A Vehkaoja, K Määttä, J Kostamovaara
Journal of Structural Mechanics 44 (4), 345-362, 2011
542011
Wireless head cap for EOG and facial EMG measurements
AT Vehkaoja, JA Verho, MM Puurtinen, NM Nojd, JO Lekkala, JA Hyttinen
2005 IEEE Engineering in Medicine and Biology 27th Annual Conference, 5865-5868, 2006
532006
Noncontact respiration monitoring during sleep with microwave Doppler radar
M Zakrzewski, A Vehkaoja, AS Joutsen, KT Palovuori, JJ Vanhala
IEEE Sensors Journal 15 (10), 5683-5693, 2015
502015
Night-time EKG and HRV monitoring with bed sheet integrated textile electrodes
M Peltokangas, J Verho, A Vehkaoja
IEEE Transactions on Information Technology in Biomedicine 16 (5), 935-942, 2012
472012
Monitoring of heart rate and inter-beat intervals with wrist plethysmography in patients with atrial fibrillation
J Harju, A Tarniceriu, J Parak, A Vehkaoja, A Yli-Hankala, I Korhonen
Physiological measurement 39 (6), 065007, 2018
422018
Correlation approach for the detection of the heartbeat intervals using force sensors placed under the bed posts
A Vehkaoja, S Rajala, P Kumpulainen, J Lekkala
Journal of medical engineering & technology 37 (5), 327-333, 2013
362013
Age dependence of arterial pulse wave parameters extracted from dynamic blood pressure and blood volume pulse waves
M Peltokangas, A Vehkaoja, J Verho, VM Mattila, P Romsi, J Lekkala, ...
IEEE journal of biomedical and health informatics 21 (1), 142-149, 2015
312015
Wearable wireless biopotential measurement device
A Vehkaoja, J Lekkala
The 26th Annual International Conference of the IEEE Engineering in Medicine …, 2004
282004
Acquiring respiration rate from photoplethysmographic signal by recursive bayesian tracking of intrinsic modes in time-frequency spectra
M Pirhonen, M Peltokangas, A Vehkaoja
Sensors 18 (6), 1693, 2018
242018
Parameters extracted from arterial pulse waves as markers of atherosclerotic changes: performance and repeatability
M Peltokangas, AA Telembeci, J Verho, VM Mattila, P Romsi, A Vehkaoja, ...
IEEE journal of biomedical and health informatics 22 (3), 750-757, 2017
242017
Comparison of simple algorithms for estimating respiration rate from electrical impedance pneumography signals in wearable devices
V Jeyhani, T Vuorinen, M Mäntysalo, A Vehkaoja
Health and Technology 7 (1), 21-31, 2017
242017
PVDF microforce sensor for the measurement of Z-directional strength in paper fiber bonds
P Saketi, SK Latifi, J Hirvonen, S Rajala, A Vehkaoja, T Salpavaara, ...
Sensors and Actuators A: Physical 222, 194-203, 2015
232015
Comparison of non-invasive blood pressure monitoring using modified arterial applanation tonometry with intra-arterial measurement
J Harju, A Vehkaoja, P Kumpulainen, S Campadello, V Lindroos, ...
Journal of clinical monitoring and computing 32 (1), 13-22, 2018
222018
Monitoring arterial pulse waves with synchronous body sensor network
M Peltokangas, A Vehkaoja, J Verho, M Huotari, J Röning, J Lekkala
IEEE Journal of Biomedical and Health Informatics 18 (6), 1781-1787, 2014
222014
Utilization of wireless sensor network for health monitoring in home environment
M Zakrzewski, S Junnila, A Vehkaoja, H Kailanto, AM Vainio, I Defee, ...
2009 IEEE International Symposium on Industrial Embedded Systems, 132-135, 2009
222009
Parkinson’s disease detection from 20-step walking tests using inertial sensors of a smartphone: Machine learning approach based on an observational case-control study
M Juutinen, C Wang, J Zhu, J Haladjian, J Ruokolainen, J Puustinen, ...
Plos one 15 (7), e0236258, 2020
162020
A fully printed ultra-thin charge amplifier for on-skin biosignal measurements
MM Laurila, H Matsui, R Shiwaku, M Peltokangas, J Verho, KL Montero, ...
IEEE Journal of the Electron Devices Society 7, 566-574, 2019
162019
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