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IoT Lab is a European funded project researching the potential of crowdsourcing as an extension to the traditional IoT testbed infrastructures. The project proposes an innovative co-design, implementation and testing of solutions with the close involvement of the crowd in the process. Through the use of a smart phone application the crowd can participate in experiments by contributing with sensory...
The paper presents design and implementation of an efficient telemedicine system. Main system capabilities are ECG acquisition, automated analysis, transmission to the server, possibility for physician ECG signal review.
In this paper, a mobile telemedicine application implemented for Android based devices is presented. The main application's functionality of ECG transmission is extended by real time ECG analysis, as well as real time analyze of acceleration data captured by embedded acceleration sensor. In this paper are presented efficient algorithms for ECG and acceleration data analysis. The ECG analysis is focused...
In this paper, an implementation of a Resource Directory, a directory storing descriptions of resources available in an Internet of Things system, based on a native XML database is described. Its performance is compared with performance of a Resource Directory with the same functionality, but implemented using a relational, SQL database. The evaluation results show hat the XML based Resource Directory...
The driving concept of device management in M2M systems is establishment of a comprehensive end-to-end resource oriented design. In this paper, OMA-DM protocol for device management of M2M devices in 3GPP LTE networks is proposed and discussed. The OMA-DM represents a stable starting point for device management. Utilization of this protocol in M2M requires efficient message formats and transport replacement...
In this paper, we present a telemedicine application for mobile devices based on Android OS platform. The basic applications functionality of ECG transmition is extended to the real-time ECG analysis and step detection using acceleration sensors integrated in mobile phones. Application is integrated in the existing telemedicine system using predefined interfaces.
In this paper, an efficient heart beat classification algorithm suitable for implementation on mobile devices is presented. A simplified ECG model is used for feature extraction in the time domain. The QRS complex is modeled using straight lines, while P and T waves are modeled using parabolas. The model parameters are estimated by minimizing the root mean square (RMS) of the model error. Heart beats...
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