How can gender be identified from heart rate data? Evaluation using ALLSTAR heart rate variability big data analysis

被引:0
|
作者
Kaneko, Itaru [1 ]
Hayano, Junichiro [2 ]
Yuda, Emi [1 ]
机构
[1] Tohoku Univ Data driven Sci & Artificial Intellige, Kawauchi 41 Aoba Ku, Sendai 9808576, Japan
[2] Nagoya City Univ, Grad Sch Med Sci, 1 Kawasumi Mizuho Cho Mizuho Ku, Nagoya 4678601, Japan
关键词
Heart rate variability (HRV); Bio-signal processing; Biological big data analysis; Gender identification; Machine learning; NORMAL RANGES; AGE;
D O I
10.1186/s13104-022-06270-2
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
ObjectiveA small electrocardiograph and Holter electrocardiograph can record an electrocardiogram for 24 h or more. We examined whether gender could be verified from such an electrocardiogram and, if possible, how accurate it would be.ResultsTen dimensional statistics were extracted from the heart rate data of more than 420,000 people, and gender identification was performed by various major identification methods. Lasso, linear regression, SVM, random forest, logistic regression, k-means, Elastic Net were compared, for Age < 50 and Age >= 50. The best Accuracy was 0.681927 for Random Forest for Age < 50. There are no consistent difference between Age < 50 and Age >= 50. Although the discrimination results based on these statistics are statistically significant, it was confirmed that they are not accurate enough to determine the gender of an individual.
引用
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页数:5
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