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Research Output

2019

Deep learning for prediction of cardiac indices from photoplethysmographic waveform: A virtual database approach

Huttunen, J. M. J., Kärkkäinen, L., Honkala, M. & Lindholm, H., Dec 2019, In : INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN BIOMEDICAL ENGINEERING. 17 p., e33303.

Research output: Contribution to journalArticleScientificpeer-review

Estimation of groundwater storage from seismic data using deep learning

Lähivaara, T., Malehmir, A., Pasanen, A., Kärkkäinen, L., Huttunen, J. M. J. & Hesthaven, J. S., 2019, In : Geophysical Prospecting. 67, 8, p. 2115-2126 12 p.

Research output: Contribution to journalArticleScientificpeer-review

1 Citation (Scopus)

Pulse transit time estimation of aortic pulse wave velocity and blood pressure using machine learning and simulated training data

Huttunen, J. M. J., Kärkkäinen, L. & Lindholm, H., 1 Aug 2019, In : PLoS computational biology. 15, 8, p. e1007259

Research output: Contribution to journalArticleScientificpeer-review

Open Access
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2 Citations (Scopus)
91 Downloads (Pure)
2018

Deep convolutional neural networks for estimating porous material parameters with ultrasound tomography

Lähivaara, T., Kärkkäinen, L., Huttunen, J. M. J. & Hesthaven, J. S., 1 Feb 2018, In : Journal of the Acoustical Society of America. 143, 2, p. 1148-1158 11 p.

Research output: Contribution to journalArticleScientificpeer-review

Open Access
File
13 Citations (Scopus)
2 Downloads (Pure)

Differential photoplethysmogram sensor with an optical notch filter shows potential for reducing motion artifact signals

Blomqvist, K. H. & Kärkkäinen, L., 25 May 2018, In : Biomedical Physics and Engineering Express. 4, 4, 8 p., 047004.

Research output: Contribution to journalArticleScientificpeer-review

2 Citations (Scopus)