Personal identification study for touchable devices with ECG

Abstract

Summary Each person has unique bio‐information, and this information rarely would be overlapped to other people. Because of this feature, many researchers have been working on a user's identification. However, the problem is that it is not certain if the feature is exactly matched at any time and in any place for the dynamic signal. It is very hard to match bio‐information whenever it is measured; however, all natural signals have an individual pattern. In this paper, it uses an ECG (electrocardiogram) as bio‐information, and it tries to find each pattern, which will be located within the threshold. With the pattern in the threshold, it detects the user's identification. To analyze the patterns, it analyzes them as measured for 120 seconds. Next, it divides them every 1‐2 seconds to 5 seconds. Then, it could recognize the users' identification with this study, and then, finally, the accuracy is 83.3618%.

A Real-Time Medical Ventilation on Heart Failure Analysis Based on Sleep Apnea Snore and Meta-Analysis

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