Abstract
This work presents the design and development of an online daily-life activity measurement system. This system has been conceptualized to be used along with other vital parameter sensor-systems, e.g. blood-pressure and electrocardiogram (ECG), to provide the necessary context information for the evaluation of the health status of cardiovascular risk patients who are not hospitalized, but must be permanently monitored during their daily routines. The activity and energy expenditure are captured and estimated from accelerometers, which are placed on different points of the body. The activity, the ECG and the blood pressure are sent to a base station (smart phone or a PDA) and from there to a data base, to which the physicians have access. Thus it is possible to continuously analyze the vital data of a cardiovascular patient taking into consideration the activity or physical strain.
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References
Context aware cardiac long-term monitoring (CALM) project at http://www.itiv.org/calm
Ottenbacher J, Jatobá L, Großmann U, Stork W, Müller-Glaser K. (2006) ECG Electrodes for a Context Aware Cardiac Permanent Monitoring System. IFMBE, World Congress on Med. Phys. & Biomed. Eng., Seoul, South Korea
Ottenbacher J, Jatobá L, Großmann U, Stork W, Müller-Glaser K (2006) Mobiles dauerhaftes EKG Monitoring. BMT 2006, ETH Zürich, Switzerland
Jatobá L, Großmann U, Ottenbacher J, Stork W, Müller-Glaser K (2006) Physical-Activity as Context-Information for Long-term Monitoring of Cardiovascular Diseases. IFMBE, World Congress on Med. Phys. & Biomed. Eng., Seoul, South Korea
Jatobá L, Großmann U, Ottenbacher J, Stork W, Müller-Glaser K (2006) Using Adaptive Neuro-Fuzzy Inference System for Online Classification of Movement Patterns. BMT 2006, ETH Zürich, Switzerland
Jang J, Sun C., Mizutani, E (1997) Neuro-Fuzzy and Soft Computing. A Computational Approach to Learning and Machine Intelligence. Prentice Hall
Jatobá L, Großmann U, Ottenbacher J, Stork W, Müller-Glaser K (2007) Development of a Self-Constructing Neuro-Fuzzy Inference System for Online Classification of Physical Movements, Healthcom 2007, Taipei, Taiwan “in press
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© 2007 Springer-Verlag Berlin Heidelberg
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Jatobá, L.C. et al. (2007). Obtaining Energy Expenditure and Physical Activity from Acceleration Signals for Context-aware Evaluation of Cardiovascular Parameters. In: Müller-Karger, C., Wong, S., La Cruz, A. (eds) IV Latin American Congress on Biomedical Engineering 2007, Bioengineering Solutions for Latin America Health. IFMBE Proceedings, vol 18. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74471-9_111
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DOI: https://doi.org/10.1007/978-3-540-74471-9_111
Publisher Name: Springer, Berlin, Heidelberg
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