LIT_2020_0 - Ubiquitous Computing - THE LÖSUNG. - HTWG Konstanz - Prof. Dr. Ralf Seepold - Ubiquitous Computing - THE LÖSUNG. - HTWG Konstanz

2020

G. V. Zhikhareva, M. N. Kramm, O. N. Bodin, R. Seepold, N. Martínez Madrid, A. I. Chernikov, Y. A. Kupriyanova, and N. A. Zhuravleva, "Conversion from electrocardiosignals to equivalent electrical sources on heart surface," BMC Bioinformatics, vol. 21, no. 2, p. 87, 2020/03/11 2020, doi: 10.1186/s12859-020-3354-8.
W. D. Scherz, R. Seepold, N. Martínez Madrid, P. Crippa, and J. A. Ortega, "RR interval analysis for the distinction between stress, physical activity and no activity using a portable ECG," in 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), 20-24 July 2020 2020, pp. 4522-4526, doi: 10.1109/EMBC44109.2020.9175458.
M. Gaiduk, R. Seepold, N. Martínez Madrid, S. Orcioni, and M. Conti, "Recognizing Breathing Rate and Movement While Sleeping in Home Environment," Cham, 2020: Springer International Publishing, in Applications in Electronics Pervading Industry, Environment and Society, pp. 333-339, doi: 10.1007/978-3-030-37277-4_38.
M. Gaiduk, S. Orcioni, M. Conti, R. Seepold, T. Penzel, N. Martínez Madrid, and J. A. Ortega, "Embedded system for non-obtrusive sleep apnea detection," in 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), 20-24 July 2020 2020, pp. 2776-2779, doi: 10.1109/EMBC44109.2020.9176075.
M. Conti, C. Aironi, S. Orcioni, R. Seepold, M. Gaiduk, and N. Martínez Madrid, "Heart rate detection with accelerometric sensors under the mattress," in 2020 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), 20-24 July 2020 2020, pp. 4063-4066, doi: 10.1109/EMBC44109.2020.9175735.
V. Corcoba Magaña, W. D. Scherz, R. Seepold, N. Martínez Madrid, X. García Pañeda, and R. Garcia, "The Effects of the Driver’s Mental State and Passenger Compartment Conditions on Driving Performance and Driving Stress," Sensors, vol. 20, no. 18, 2020, doi: 10.3390/s20185274.
M. Gaiduk, R. Seepold, and T. Penzel, "Kontaktloses System zur Erkennung von Apnoe," Somnologie, 2020/10/01 2020, doi: 10.1007/s11818-020-00267-4.
R. Seepold, M. Conti, N. Martínez Madrid, C. Aironi, S. Orcioni, and M. Gaiduk, "Die Ballistokardiographie misst die Herzfrequenz anhand der mechanischen Körperschwingungen aus der Herzbewegung.," Somnologie, 2020/10/01 2020, doi: 10.1007/s11818-020-00267-4.
R. Seepold, K. Stuburić, M. Gaiduk, N. Martínez Madrid, and T. Penzel, "Aufwandsbegrenztes maschinelles Lernen zur Bestimmung von Schlafstadien," Somnologie, 2020/10/01 2020, doi: 10.1007/s11818-020-00267-4.
K. Stuburić, M. Gaiduk, and R. Seepold, "A deep learning approach to detect sleep stages," Procedia Computer Science, vol. 176, pp. 2764-2772, 2020/01/01/ 2020, doi: https://doi.org/10.1016/j.procs.2020.09.280 .
Y. Shkilniuk, Á. S. Alarcón, M. Gaiduk, R. Seepold, and N. Martínez Madrid, "Analysis of Survey Tools for Recommender Systems in the Selection of Ambient Assisted Living Technologies," Procedia Computer Science, vol. 176, pp. 2332-2340, 2020/01/01/ 2020, doi: https://doi.org/10.1016/j.procs.2020.09.294 .
W. D. Scherz, V. C. Magaña, R. Seepold, N. Martínez Madrid, and J. A. Ortega, "Can Virtual Reality be used as a significant stressor for studies using ECG?," Procedia Computer Science, vol. 176, pp. 3255-3262, 2020/01/01/ 2020, doi: https://doi.org/10.1016/j.procs.2020.09.123 .
M. Gaiduk, D. Wehrle, R. Seepold, and J. A. Ortega, "Non-obtrusive system for overnight respiration and heartbeat tracking," Procedia Computer Science, vol. 176, pp. 2746-2755, 2020/01/01/ 2020, doi: https://doi.org/10.1016/j.procs.2020.09.282 .
W. D. Scherz, J. Baun, R. Seepold, N. Martínez Madrid, and J. A. Ortega, "A portable ECG for recording and flexible development of algorithms and stress detection," Procedia Computer Science, vol. 176, pp. 2886-2893, 2020/01/01/ 2020, doi: https://doi.org/10.1016/j.procs.2020.09.265 .
M. Gaiduk, R. Seepold, J. A. Ortega, and N. Martínez Madrid, "Comparison of sleep characteristics measurements: a case study with a population aged 65 and above," Procedia Computer Science, vol. 176, pp. 2341-2349, 2020/01/01/ 2020, doi: https://doi.org/10.1016/j.procs.2020.09.297 .
G. Biagetti, P. Crippa, L. Falaschetti, E. Focante, N. Martínez Madrid, R. Seepold, and C. Turchetti, "Machine Learning and Data Fusion Techniques Applied to Physical Activity Classification Using Photoplethysmographic and Accelerometric Signals," Procedia Computer Science, vol. 176, pp. 3103-3111, 2020/01/01/ 2020, doi: https://doi.org/10.1016/j.procs.2020.09.178.