Low complexity QRS detectors for performance and energy aware applications

Telemedicine or mHealth systems can improve the quality of life of patients who need to be monitored continuously. Not only will it allow them to stay at their own home with a higher level of mobility but also maintaining or even improving the accuracy of the diagnostic. Remote monitoring can enable information about the health status of all patients to be passed to the medical staff continuously for prolonged periods of time. Some of the vital physiological parameters for diagnostic are heart rate and heart rate variability. The calculation of these parameters relies on an accurate heartbeats detector (QRS complexes detector). In this work, two QRS detectors are proposed. They have been designed taking into account not only the accuracy, but also the computational complexity and the power consumption they require to analyze the electrocardiographic signal (ECG) in order to implement them on wearable platforms with different levels of constrained resources (integer numbers or floating point arithmetic). The complexity, power consumption and accuracy parameters of both algorithms are also analyzed.