Search results
- 1.0583013 - ÚPT 2024 RIV US eng C - Conference Paper (international conference)
Šaclová, L. - Němcová, A. - Šacl, J. - Ronzhina, M. - Smíšek, Radovan - Smítal, L. - Vítek, M.
Autonomic Nervous System Recovery After Various Exercises in Highly Trained Athletes.
2022 Computing in Cardiology (CinC). New York: IEEE, 2022, 2022-eptember (2022), č. článku 265. ISBN 979-8-3503-0097-0. ISSN 2325-8861. E-ISSN 2325-887X.
[Computing in Cardiology 2022 /49./. Tampere (FI), 04.09.2022-07.09.2022]
Institutional support: RVO:68081731
Keywords : autonomic nervous system * heart rate variability * running training session
OECD category: Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
https://ieeexplore.ieee.org/document/10081787 https://cinc.org/archives/2022/pdf/CinC2022-265.pdf
Permanent Link: https://hdl.handle.net/11104/0351422 - 2.0571440 - ÚPT 2024 RIV US eng C - Conference Paper (international conference)
Smíšek, Radovan - Němcová, A. - Smítal, L. - Chlíbková, D. - Králík, M. - Kolářová, J. - Myška, V. - Kolařík, M. - Harvánek, J. - Arm, J. - Baštán, O. - Pospíšil, M. - Šíma, J. - Hubálek, J.
Aerobic Fitness Level Estimation Using Wearables.
2022 Computing in Cardiology (CinC). New York: IEEE, 2022, Roč. 49 (2022), č. článku 302. ISBN 979-8-3503-0097-0. ISSN 2325-8861. E-ISSN 2325-887X.
[Computing in Cardiology 2022 /49./. Tampere (FI), 04.09.2022-07.09.2022]
Institutional support: RVO:68081731
Keywords : Aerobic Fitness Level * Cardiorespiratory fitness
OECD category: Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
https://ieeexplore.ieee.org/document/10081645 https://cinc.org/archives/2022/pdf/CinC2022-302.pdf
Permanent Link: https://hdl.handle.net/11104/0351662 - 3.0555027 - ÚPT 2022 RIV US eng C - Conference Paper (international conference)
Kozumplík, J. - Smítal, L. - Němcová, A. - Ronzhina, M. - Smíšek, Radovan - Maršánová, L. - Králik, M. - Vítek, M.
Respiratory Rate Estimation Using the Photoplethysmogram: Towards the Implementation in Wearables.
2021 Computing in Cardiology (CinC). Vol. 48. New York: IEEE, 2021, č. článku 15. ISBN 978-166547916-5. ISSN 2325-8861. E-ISSN 2325-887X.
[Computing in Cardiology 2021 /48./. Brno (CZ), 12.09.2021-15.09.2021]
Institutional support: RVO:68081731
Keywords : Photoplethysmogram * Respiratory Rate Estimation
OECD category: Medical engineering
https://ieeexplore.ieee.org/document/9662674
Permanent Link: http://hdl.handle.net/11104/0329645 - 4.0494537 - ÚPT 2019 RIV SG eng C - Conference Paper (international conference)
Maršánová, L. - Němcová, A. - Smíšek, Radovan - Goldmann, T. - Vítek, M. - Smítal, L.
Automatic detection of P wave in ECG during ventricular extrasystoles.
IFMBE Proceedings. Vol. 68-2. Singapore: Springer, 2019, s. 381-385. ISBN 978-981-10-9037-0. ISSN 1680-0737.
[World Congress on Medical Physics and Biomedical Engineering. WC 2018. Prague (CZ), 03.06.2018-08.06.2018]
Institutional support: RVO:68081731
Keywords : ECG * electrocardiogram * ventricular extrasystoles P wave * P wave detection * pathological ECG signal
OECD category: Medical engineering
Permanent Link: http://hdl.handle.net/11104/0287673 - 5.0494536 - ÚPT 2019 RIV SG eng C - Conference Paper (international conference)
Němcová, A. - Vítek, M. - Maršánová, L. - Smíšek, Radovan - Smítal, L.
Assessment of ECG signal quality after compression.
IFMBE Proceedings. Vol. 68-2. Singapore: Springer, 2019, s. 169-173. ISBN 978-981-10-9037-0. ISSN 1680-0737.
[World Congress on Medical Physics and Biomedical Engineering. WC 2018. Prague (CZ), 03.06.2018-08.06.2018]
Institutional support: RVO:68081731
Keywords : compression * ECG * electrocardiogram * quality assessment * quality evaluation * SPIHT * CSE database
OECD category: Medical engineering
Permanent Link: http://hdl.handle.net/11104/0287669 - 6.0487043 - ÚPT 2019 RIV FR eng C - Conference Paper (international conference)
Smíšek, Radovan - Hejč, J. - Ronzhina, M. - Němcová, A. - Maršánová, L. - Chmelík, J. - Kolářová, J. - Provazník, I. - Smítal, L. - Vítek, M.
SVM Based ECG Classification Using Rhythm and Morphology Features, Cluster
Analysis and Multilevel Noise Estimation.
Computing in Cardiology 2017. Vol. 44. Rennes: Computing in Cardiology, 2017, s. 1-4. E-ISSN 2325-887X.
[Computing in Cardiology 2017. Rennes (FR), 24.09.2017-27.09.2017]
R&D Projects: GA ČR GAP102/12/2034
Institutional support: RVO:68081731
Keywords : ECG classifications * global feature * cross-validation technique
OECD category: Medical engineering
http://www.cinc.org/archives/2017/
Permanent Link: http://hdl.handle.net/11104/0284366