Ubiquitous Computing


Course content:
• Ubiquitous computing concepts
• Smart Living
• AAL technologies and IoT
• Vital sign capturing and management
• Health applications

Learning objectives:
Subject-specific competencies:
• interpret ubiquitous computing concepts
• develop ubiquitous computing applications

Methodological competencies:
• design ubiquitous computing applications

Interdisciplinary competencies:
• understand fundamentals ubiquitous computing and applications

Literature and other sources of information:
• Mark Weiser. 1999. The computer for the 21st century. SIGMOBILE Mob. Comput. Commun. Rev. 3, 3 (July 1999), 3–11. DOI:
• G. V. Zhikhareva, M. N. Kramm, O. N. Bodin, R. Seepold, N. Martínez Madrid, "Conversion from electrocardio signals 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.
• M. Gaiduk, T. Penzel, J.A. Ortega, R. Seepold, "Automatic Sleep Stages Classification Using Respiratory, Heart Rate and Movement Signals", Physiological Measurement, 39(12):124008, 2018. DOI: 10.1088/1361-6579/aaf5d4
• W.D. Scherz, D. Fritz, O.R. Velicu, R. Seepold and N. Martínez Madrid, "Heart rate spectrum analysis for sleep quality detection", EURASIP Journal on Embedded Systems 2017
• W.D. Scherz, J.A. Ortega, R. Seepold, M. Conti, "Pattern recognition techniques and classification sets supporting behavioural tagging when using a limited number of body sensors", European Medical and Biological Engineering Conference, Nordic-Baltic Conference on Biomedical Engineering and Medical Physics. IFMBE Proceedings, vol 65. Springer, 2017.

Sprache Englisch
Dozent Ralf Seepold
Fakultät IN
Technisch / Wirtschaftlich Technisch
Studiengänge Automobil­informations­technik (AIT)
Intelligente Mobilitätssysteme (IMS)
Plätze -
Semester WS 2023/24