**Author details**

where *N* is the number of peaks and *dk* is duration between two consecutive peaks. The peaks are detected using a classical peak-detection algorithm that is applied to both the ECG signal

Front 85 93 9.12 Back 88 87 1.43 Left 82 80 2.66 Right 87 80 7.38

**Table 2.** HR calculation for ECG and filtered cardiopulmonary signals and the obtained relative error.

*HR HR Error*

to heart beating will be less affected by the respiration signal on other sides.

100\* | - <sup>|</sup> <sup>=</sup> *ECG VNA ECG*

As shown in Section 5.1, the cardiopulmonary signal detected from the front side of the subject shows clear respiration signal in time-domain while other sides' signals do not. On the other hand, when applying the Bior2.4 family of the discrete wavelet transform to the cardiopul‐ monary signals, the highest accuracy in terms of heartbeat rate is obtained at the back side while the front side shows the lowest accuracy. This is due to the fact that chest displacement due to breathing is higher at the front side than other sides; hence, the chest displacement due

A microwave system used in order to detect the chest wall motion that contains information about respiration and heart beating is described. The system is tested at different operational frequencies: 2.4, 5.8, 10, 16, and 60 GHz on a subject at 1 m from the system while holding the breath for 10 s. Other measurements were performed at 5.8 GHz for different positions for the subject: front, back, left, and right sides. The first measurement is performed on a 27-year-old subject while holding the breath, while the second measurement is performed on a 54-yearold subject while breathing normally. Along with a PC-based ECG, measurements are performed with 0 dBm output power and for a duration of 30 s where the subject breathes normally. The proposed system shows the ability of detecting cardiopulmonary signals for the four sides' positioning: front, back, left, and right. Wavelet transformation is used in processing cardiopulmonary signals in order to extract the heartbeat signal. The 8th-level decomposition of Bior2.4 shows high performance in providing the heartbeat signal in time domain where

**Heartbeat rate for filtered cardiopulmonary signal (bpm)** **Absolute relative error**

**(%)**

*HR* (7)

and the filtered cardiopulmonary signal.

48 Advanced Biosignal Processing and Diagnostic Methods

The relative error of the HR is calculated as

 **Heartbeat rate for ECG signal** 

**Measurement**

**6. Conclusion**

**(bpm)**

**side**

Dany Obeid1\*, Sarah Samad2 , Sawsan Sadek2 , Gheorghe Zaharia1 and Ghaïs El Zein1

\*Address all correspondence to: dany.obeid@gmail.com

1 IETR UMR 6164, INSA Rennes, Rennes, France

2 University Institute of Technology, Lebanese University, Saida, Lebanon
