Abstract
This chapter presents analysis of emerging mHealth applications as well as the exploration of novel trends supporting healthcare intelligent environments assisted by mobile devices. The case of study is mHealth and remote vital sign monitoring. Particularly, we present a methodology for recollecting, processing and real-time monitoring heart activity with the main purpose to interpret electrocardiogram ECG signals, detect and manage situations of risk and provide the interaction between medical practitioner and patient into smart healthcare environment. The proposed architecture and approach provide continuous detection and interpretation of the patient’s QRS complex. The challenge is to adapt some approaches for data gathering, processing, compression, storage, analysis, and visualization to capabilities of mobile devices. The designed system for monitoring vital signals has been tested using standard MIT-BIH Arrhythmia Database achieving satisfactory ECG interpretation accuracy with relative error in range from 4 % to 10 % for signal sampling frequency of 360 and 128 samples per second respectively. It is important to note that the proposed prototype does not substitute diagnosis by physician. Our intention is to propose methodologies that serve as guide for development of complex health assistance tool expanding coverage of medical services.
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Starostenko, O., Alarcon-Aquino, V., Rodriguez-Asomoza, J., Sergiyenko, O., Tyrsa, V. (2015). Remote Health/Vital Sign Monitoring. In: Adibi, S. (eds) Mobile Health. Springer Series in Bio-/Neuroinformatics, vol 5. Springer, Cham. https://doi.org/10.1007/978-3-319-12817-7_10
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DOI: https://doi.org/10.1007/978-3-319-12817-7_10
Publisher Name: Springer, Cham
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