A Real-Time QRS Detection Method Based on Phase Portraits and Box-Scoring Calculation

In order to detect the QRS complexes locally in the microcontroller-based embedded system, a novel algorithm with lower computation burden is proposed by phase space reconstruction and box-scoring calculation. The method depends on the geometrical property of the ECG signal phase portraits. According to the time-delay method, one segment of the sampled 1-D ECG signal is embedded into a 2-D phase space. The phase space is divided into $2^{M}\times 2^{M}$ grids, and each grid is called a box. The box gridding is implemented by numerically truncating the high $M$ -bits from the digital data. The phase portraits of the sampled ECG signal in the phase space are therefore divided by these boxes. Since the trajectory points corresponding to the R-waves are located relatively far away from the diagonal line, boxes that crossed by the trajectory are flagged and valued according to its distance to the diagonal line. Correspondingly, the box-scoring of the ECG segment is obtained by summarizing the values of the flagged boxes. The location of the R-waves can then be found by finding peak values in the box-scoring time series. The proposed algorithm is suitable for real-time QRS complex detection in microcontroller-based wearable ECG acquisition devices.