Development of Miniaturized Wearable Wristband Type Surface EMG Measurement System for Biometric Authentication

Siho Shin,Mingu Kang,Jaehyo Jung,Youn Tae Kim

doi:10.3390/electronics10080923

Abstract

Personal authentication systems employing biometrics are attracting increasing attention owing to their relatively high security compared to existing authentication systems. In this study, a wearable electromyogram (EMG) system that can be worn on the forearm was developed to detect EMG signals and, subsequently, apply them for personal authentication. In previous studies, wet electrodes were attached to the skin for measuring biosignals. Wet electrodes contain adhesives and conductive gels, leading to problems such as skin rash and signal-quality deterioration in long-term measurements. The miniaturized wearable EMG system developed in this study comprised flexible dry electrodes attached to the watch strap, enabling EMG measurements without additional electrodes. In addition, for accurately classifying and applying the measured signal to the personal authentication system, an optimal algorithm for classifying the EMG signals based on a multi-class support vector machine (SVM) model was implemented. The model using cubic SVM achieved the highest personal authentication rate of 87.1%. We confirmed the possibility of implementing a wearable authentication system by measuring the EMG signal and artificial intelligence analysis algorithm presented in this study.

Highlights

Biometric recognition is a technology that recognizes an individual based on the unique characteristics of their body
In previous studies that attempted to perform authentication using a surface electromyogram, similar to the system that we proposed, special hand gestures performed by a user were analyzed and classified with an support vector machine (SVM) to recognize the host data [16]
The module was manufactured as a minimized wearable device with a size of 15 × 25 × 2 mm3 that can be worn on the forearm; it uses one channel consisting of two dry electrodes

Summary

Introduction

Biometric recognition is a technology that recognizes an individual based on the unique characteristics of their body. This technology authenticates the host by analyzing a person’s physical characteristics and determining whether they match the host data stored in the database. The most promising biometric technology is the use of unique signals, such as electrocardiogram (ECG) and electromyogram (EMG) signals [7,8]. This method analyzes the morphological characteristics of ECG and EMG signals and has a considerable potential for development in the field of biometrics technology because it enables real-time authentication and prevents hacking

Methods

Results

Discussion

Conclusion