A Real-Time Heart Rate Detection Algorithm Based on Peripheral Electrical Bioimpedance

Impedance cardiography (ICG) and peripheral bioimpedance may be useful for monitoring several cardiovascular parameters such as cardiac output, stroke volume, blood pressure and heart rate. It is a noninvasive and low-cost method and could be useful for diagnosis and treatment in different clinical situations. This study involved 100 volunteers and their age ranging from 18 to 26 years. The acquired bioimpedance signal was pre-processed and used to estimate the heart rate. Thus, heart rates of each subject were calculated and then compared with actual measurement from FUZZY model MP3 digital blood pressure monitor. The results showed high precision with a 1.38 mean error a high sensitivity of 99.81% and a positive predictivity value of 99.63%, respectively. Compared with six other methods selected from the literature review and which are initially dedicated to ECG signals, the proposed method has been found to be more efficient and more precise with an error in determining the percentile HR = 1.78%.