2020
DOI: 10.1109/access.2020.2981828
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Exploring the Hand and Finger-Issued Behaviors Toward Natural Authentication

Abstract: As wearables, such as smartwatches and data gloves, become ubiquitous in our daily lives, it is possible to capture users' behaviors as they go, and then to authenticate them using biometrics. A variety of behaviors have been exploited to authenticate users in a plethora of scenarios. However, there is still a lack of systematic investigations on what types of behaviors present better performance for authentication, and therefore, limiting our understanding of the custom design of behavioral ''passwords'' to f… Show more

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Cited by 17 publications
(1 citation statement)
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“…In contrast, operating robots using wearable sensing technology is more intuitive, user-friendly, and the algorithm development is relatively simpler, becoming a hot topic of research. Wearable sensing technology typically collects hand information including movement speed, acceleration, degree of bending, and electromyography (EMG) signals [11][12][13][14][15][16][17][18][19][20][21]. Accelerometers are the most common type, capable of capturing the acceleration and velocity of hand movements, but their signals are susceptible to external noise interference.…”
Section: Introductionmentioning
confidence: 99%
“…In contrast, operating robots using wearable sensing technology is more intuitive, user-friendly, and the algorithm development is relatively simpler, becoming a hot topic of research. Wearable sensing technology typically collects hand information including movement speed, acceleration, degree of bending, and electromyography (EMG) signals [11][12][13][14][15][16][17][18][19][20][21]. Accelerometers are the most common type, capable of capturing the acceleration and velocity of hand movements, but their signals are susceptible to external noise interference.…”
Section: Introductionmentioning
confidence: 99%