Abstract
This paper presents the results of using a commercial pulsimeter as an electrocardiogram (ECG) for wireless detection of cardiac alterations and stress levels for home control. For these purposes, signal processing techniques (Continuous Wavelet Transform (CWT) and J48) have been used, respectively. The designed algorithm analyses the ECG signal and is able to detect the heart rate (99.42%), arrhythmia (93.48%) and extrasystoles (99.29%). The detection of stress level is complemented with Skin Conductance Response (SCR), whose success is 94.02%. The heart rate variability does not show added value to the stress detection in this case. With this pulsimeter, it is possible to prevent and detect anomalies for a non-intrusive way associated to a telemedicine system. It is also possible to use it during physical activity due to the fact the CWT minimizes the motion artifacts.
Highlights
There has been an increase in the number of remote health monitoring applications due to the importance of detecting anomalies and illness or diseases [1]
ECG Waveform Packet: one of the functions of the pulsimeter is that of acting as a holter. This frame gives the data of the electrocardiogram
The results show that not all the users have been stressed or annoyed by the different tests
Summary
There has been an increase in the number of remote health monitoring applications due to the importance of detecting anomalies and illness or diseases [1]. Remote monitoring systems are used to detect anomalies, but they are used by chronic patients to control their constants while at home, without the need to be in hospital, improving the patients’ quality of life [2,3]. In this case, the system could act by warning the specialist about any problem detected [4]. The described study uses a commercial ECG with the three following final objectives: Remote monitoring: acquisition of different signals for their posterior treatment
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