| Presentation | 2022-01-21 Verification of gender identifiability and its sensitivity from heart rate data in Allstar heart rate variability big data analysis Itaru Kaneko, Emi Yuda, |
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| PDF Download Page |  PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | We have verified the analysis of Allstar heart rate big data (big data of heart rate that we are analyzing). This time, we have verified whether the gender can be identified from the heart rate big data. After 10-dimensional statistic extraction for 12,000 heartbeat data, gender identification was performed on them by various discrimination method. Lasso, linear regression, SVM, Random Forest, logistic regression, K-means, Elastic Net were compared. The best Accuracy / r2 score was 0.66 for logistic regression. Although it is possible to identify the gender to some extent by the identification based on these statistics, it was confirmed that the accuracy is not sufficient to identify the gender. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | Allstar heart rate big data / Gender / SVM / Random Forest / privacy |
| Paper # | NLP2021-85,MICT2021-60,MBE2021-46 |
| Date of Issue | 2022-01-14 (NLP, MICT, MBE) |
| Conference Information | |
| Committee | NLP / MICT / MBE / NC |
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| Conference Date | 2022/1/21(3days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Online |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | |
| Chair | Takuji Kosaka(Chukyo Univ.) / Eisuke Hanada(Saga Univ.) / Ryuhei Okuno(Setsunan Univ.) / Rieko Osu(Waseda Univ.) |
| Vice Chair | Akio Tsuneda(Kumamoto Univ.) / Hirokazu Tanaka(Hiroshima City Univ.) / Daisuke Anzai(Nagoya Inst. of Tech.) / Junichi Hori(Niigata Univ.) / Hiroshi Yamakawa(Univ of Tokyo) |
| Secretary | Akio Tsuneda(Kagawa Univ.) / Hirokazu Tanaka(Sojo Univ.) / Daisuke Anzai(Yokohama National Univ.) / Junichi Hori(KISTEC) / Hiroshi Yamakawa(Osaka Electro-Communication Univ) |
| Assistant | Hideyuki Kato(Oita Univ.) / Yuichi Yokoi(Nagasaki Univ.) / Takahiro Ito(Hiroshima City Univ) / Kento Takabayashi(Okayama Pref. Univ.) / Takuya Nishikawa(National Cerebral and Cardiovascular Center Hospital) / Jun Akazawa(Meiji Univ. of Integrative Medicine) / Emi Yuda(Tohoku Univ) / Nobuhiko Wagatsuma(Toho Univ.) / Tomoki Kurikawa(KMU) |
| Paper Information | |
| Registration To | Technical Committee on Nonlinear Problems / Technical Committee on Healthcare and Medical Information Communication Technology / Technical Committee on ME and Bio Cybernetics / Technical Committee on Neurocomputing |
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| Language | JPN |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Verification of gender identifiability and its sensitivity from heart rate data in Allstar heart rate variability big data analysis |
| Sub Title (in English) | |
| Keyword(1) | Allstar heart rate big data |
| Keyword(2) | Gender |
| Keyword(3) | SVM |
| Keyword(4) | Random Forest |
| Keyword(5) | privacy |
| 1st Author's Name | Itaru Kaneko |
| 1st Author's Affiliation | Tohoku University(Tohoku Univ.) |
| 2nd Author's Name | Emi Yuda |
| 2nd Author's Affiliation | Tohoku University(Tohoku Univ.) |
| Date | 2022-01-21 |
| Paper # | NLP2021-85,MICT2021-60,MBE2021-46 |
| Volume (vol) | vol.121 |
| Number (no) | NLP-335,MICT-336,MBE-337 |
| Page | pp.pp.50-53(NLP), pp.50-53(MICT), pp.50-53(MBE), |
| #Pages | 4 |
| Date of Issue | 2022-01-14 (NLP, MICT, MBE) |