Name
Abstract | ||
|---|---|---|
Recently, people are increasingly interested in biometrics using wearable device-based biosignals. Biosignals are better than fingerprints, iris, and faces because of less objection, and easy perpetuation and continuation with biosignals. This paper proposes a system for personal identification using ECG which is a biosignal. The proposed system uses ECG signals and extracts features by convergence in the time domain and the frequency domain. The ECG-based method of personal identification analyzes performance change depending on enrolment data, recognition data and the number of feature parameters by 1:N matching to analyze performance. The experiment revealed personal identification performance of 98% in ECG data of 10 persons obtained while they felt comfortable. |
Year | Venue | Field |
|---|---|---|
2016 | MobiSec | Time domain,Convergence (routing),Frequency domain,Wearable computer,Computer science,Continuation,Speech recognition,Biometrics,Biosignal |
DocType | Citations | PageRank |
Conference | 0 | 0.34 |
References | Authors | |
0 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Gyu Ho Choi | 1 | 2 | 0.71 |
| Hae-Min Moon | 2 | 37 | 7.49 |
| Sung Bum Pan | 3 | 162 | 36.88 |