EmgAuth: An EMG-based Smartphone Unlocking System Using Siamese Network

Fan, Boyu; Li, Xuefeng; Su, Xiang; Hui, Pan; Niu, Jianwei

doi:10.1109/percom45495.2020.9127387

Cited by 24 publications

(22 citation statements)

References 35 publications

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“…In contrast, the EMG-based authentication systems are more suitable because they are not influenced by the surrounding noise or the health of the user. Therefore, authentication studies using EMG signals have been actively conducted in the recent years [11][12][13][14].…”

Section: Introductionmentioning

confidence: 99%

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

et al. 2021

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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.

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Section: Introductionmentioning

confidence: 99%

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

et al. 2021

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“…This paper is an extended version of [10] with a more detailed literature study, an upgraded Android-implemented prototype system, a bigger dataset and a deeper analysis to investigate the effect of rotation-independency and nonsitting scenarios. The contributions of this paper are summarized as follows:…”

Section: Introductionmentioning

confidence: 99%

EmgAuth: Unlocking Smartphones with EMG Signals

Fan¹,

Xiang²,

Niu³

et al. 2021

Preprint

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Screen lock is a critical security feature for smartphones to prevent unauthorized access. Although various screen unlocking technologies, including fingerprint and facial recognition, have been widely adopted, they still have some limitations. For example, fingerprints can be stolen by special material stickers and facial recognition systems can be cheated by 3D-printed head models. In this paper, we propose EmgAuth, a novel electromyography(EMG)-based smartphone unlocking system based on the Siamese network. EmgAuth enables users to unlock their smartphones by leveraging the EMG data of the smartphone users collected from Myo armbands. When training the Siamese network, we design a special data augmentation technique to make the system resilient to the rotation of the armband, which makes EmgAuth free of calibration. We conduct extensive experiments including 53 participants and the evaluation results verify that EmgAuth can effectively authenticate users with an average true acceptance rate of 91.81% while keeping the average false acceptance rate of 7.43%. In addition, we also demonstrate that EmgAuth can work well for smartphones with different screen sizes and for different scenarios when users are placing smartphones at different locations and with different orientations. EmgAuth shows great promise to serve as a good supplement for existing screen unlocking systems to improve the safety of smartphones.

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“…On the other hand, electrode displacement has been successful as an augmentation method for the problem of user authentication based on sEMG. The authors of [ 17 ] apply a circular rotation of the eight electrodes of the Myo armband, thus expanding the original data up to 8×. In this case, the electrode displacement augmentation improves the performance of the model because the enhanced dataset still belongs to one person, while a specific hand gesture is not required for the successful authentication.…”

Section: Introductionmentioning

confidence: 99%

Data Augmentation of Surface Electromyography for Hand Gesture Recognition

Tsinganos

Cornelis

et al. 2020

Sensors

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The range of applications of electromyography-based gesture recognition has increased over the last years. A common problem regularly encountered in literature is the inadequate data availability. Data augmentation, which aims at generating new synthetic data from the existing ones, is the most common approach to deal with this data shortage in other research domains. In the case of surface electromyography (sEMG) signals, there is limited research in augmentation methods and quite regularly the results differ between available studies. In this work, we provide a detailed evaluation of existing (i.e., additive noise, overlapping windows) and novel (i.e., magnitude warping, wavelet decomposition, synthetic sEMG models) strategies of data augmentation for electromyography signals. A set of metrics (i.e., classification accuracy, silhouette score, and Davies–Bouldin index) and visualizations help with the assessment and provides insights about their performance. Methods like signal magnitude warping and wavelet decomposition yield considerable increase (up to 16%) in classification accuracy across two benchmark datasets. Particularly, a significant improvement of 1% in the classification accuracy of the state-of-the-art model in hand gesture recognition is achieved.

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EmgAuth: An EMG-based Smartphone Unlocking System Using Siamese Network

Cited by 24 publications

References 35 publications

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

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

EmgAuth: Unlocking Smartphones with EMG Signals

Data Augmentation of Surface Electromyography for Hand Gesture Recognition

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