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

BMC Research Notes

Research Note

Junichiro Hayano¹  Emi Yuda²  Itaru Kaneko² 

[1] Nagoya City University Graduate School of Medical Sciences, 1 Kawasumi Mizuho-Cho Mizuho-Ku, 467-8601, Nagoya, Japan;Tohoku University Data-driven Science and Artificial Intelligence, Kawauchi 41 Aoba-Ku, 980-8576, Sendai, Japan;

关键词: Heart rate variability (HRV);    Bio-signal processing;    Biological big data analysis;    Gender identification;    Machine learning;   

DOI  :  10.1186/s13104-022-06270-2

 received in 2022-07-04, accepted in 2022-12-24,  发布年份 2022

来源: Springer

【 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.

【 授权许可】

CC BY   
© The Author(s) 2023

【 图 表 】

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