Title :
Biometric Statistical Study of One-Lead ECG Features and Body Mass Index (BMI)
Author :
Shen, T.W. ; Tompkins, W.J.
Author_Institution :
Dept. of Biomed. Eng., Wisconsin Univ., Madison, WI
Abstract :
We have studied the electrocardiogram (ECG) as a potential biometric for human identity verification. This research investigates the relationship between ECG biometric features and body mass index (BMI) using correlation analysis and linear regression methods. Using our ECG database of 168 normal healthy people (113 females and 55 males), we studied normalized features extracted from a one-lead, resting, palm ECG. The results showed that normalized ECG biometric features explain 25.3% of the variability of the BMI. ECG features of males better correlate with the BMI model than those of females. Furthermore, we calculated correlation coefficients and R-square changes to analyze the correlations between extracted features and the BMI and to indicate the most significant feature as a predictor of BMI among all ECG biometric features
Keywords :
biometrics (access control); electrocardiography; feature extraction; medical signal processing; regression analysis; R-square; biometric; biometric statistical study; body mass index; correlation analysis; correlation coefficients; electrocardiogram; features extraction; human identity verification; linear regression methods; normal healthy people; one-lead ECG features; Biological system modeling; Biomedical engineering; Biometrics; Electrocardiography; Electrodes; Feature extraction; Geometry; Humans; Linear regression; Spatial databases; Biometrics; Body Mass Index (BMI); Correlation; ECG features; Electrocardiogram (ECG); Human identity verification; Linear regression;
Conference_Titel :
Engineering in Medicine and Biology Society, 2005. IEEE-EMBS 2005. 27th Annual International Conference of the
Conference_Location :
Shanghai
Print_ISBN :
0-7803-8741-4
DOI :
10.1109/IEMBS.2005.1616629
