User Classification and Authentication for Mobile Device Based on Gesture Recognition

Nixon, Kent W.; Chen, Yiran; Mao, Zhi-Hong; Li, Kang

doi:10.1007/978-1-4614-7597-2_8

Cited by 4 publications

(3 citation statements)

References 2 publications

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“…Most experiments recruited less than 50 subjects (Buschek et al, 2015;Kambourakis et al, 2014;Y. Meng et al, 2014), with some less than 5 subjects (Nixon et al, 2014;Rao et al, 2014). We were only able to find three experiments, (Gascon et al, 2014;Serwadda et al, 2013;, which used a large number of subjects (315, 190 and 152 subjects, respectively).…”

Section: Subject Sizementioning

confidence: 92%

“…The touch size value captured from a subject is determined by the subject's fingertip size. For example, the authors of (Nixon et al, 2014) observed that an adult male subject usually produces a larger touch size value than a child or an adult female subject. This means that it is hard for people with different fingertip sizes to mimic each other.…”

Section: Spatial Feature (Sp)mentioning

confidence: 99%

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A survey on touch dynamics authentication in mobile devices

Teh

Zhang

Teoh

et al. 2016

Computers & Security

130

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There have been research activities in the area of keystroke dynamics biometrics on physical keyboards (desktop computers or conventional mobile phones) undertaken in the past three decades. However, in terms of touch dynamics biometrics on virtual keyboards (modern touchscreen mobile devices), there has been little published work. Particularly, there is a lack of an extensive survey and evaluation of the methodologies adopted in the area. Owing to the widespread use of touchscreen mobile devices, it is necessary for us to examine the techniques and their effectiveness in the domain of touch dynamics biometrics. The aim of this paper is to provide some insights and comparative analysis of the current state-of-the-art in the topic area, including data acquisition protocols, feature data representations, decision making techniques, as well as experimental settings and evaluations. With such a survey, we can gain a better understanding of the current state-of-the-art, thus identifying challenging issues and knowledge gaps for further research.

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Section: Subject Sizementioning

confidence: 92%

Section: Spatial Feature (Sp)mentioning

confidence: 99%

A survey on touch dynamics authentication in mobile devices

Teh

Zhang

Teoh

et al. 2016

Computers & Security

130

View full text Add to dashboard Cite

show abstract

“…A related set of approaches does not try to prevent unauthorized access, but rather take an auditing approach. For example, learning the wrist motions of different people can create an audit trail [165], which can then be used to identify tampering for later remediation.…”

Section: Tampering Authentication and Active Non-compliancementioning

confidence: 99%

A Review of Medication Adherence Monitoring Technologies

Aldeer

Javanmard

Martin

2018

ASI

113

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Medication non-adherence is a prevalent, complex problem. Failure to follow medication schedules may lead to major health complications, including death. Proper medication adherence is thus required in order to gain the greatest possible drug benefit during a patient's treatment. Interventions have been proven to improve medication adherence if deviations are detected. This review focuses on recent advances in the field of technology-based medication adherence approaches and pays particular attention to their technical monitoring aspects. The taxonomy space of this review spans multiple techniques including sensor systems, proximity sensing, vision systems, and combinations of these. As each technique has unique advantages and limitations, this work describes their trade-offs in accuracy, energy consumption, acceptability and user's comfort, and user authentication.

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Monitoring Technologies for Quantifying Medication Adherence

et al. 2022

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Medication non-adherence is a prevalent, complex problem. Failure to follow medication schedules may lead to major health complications, which could reduce quality of life. Proper medication adherence is thus required in order to gain the greatest possible drug benefit during a patient’s treatment. Interventions have been proven to improve medication adherence if deviations are detected. This review focuses on recent advances in the field of technology-based medication adherence approaches and pays particular attention to their technical monitoring aspects. The taxonomy space of this review spans multiple techniques including sensor systems, proximity sensing, vision systems, and combinations of these. As each technique has unique advantages and limitations, this work describes their trade-offs in accuracy, energy consumption, acceptability and user’s comfort, and user authentication.

show abstract

User Classification and Authentication for Mobile Device Based on Gesture Recognition

Cited by 4 publications

References 2 publications

A survey on touch dynamics authentication in mobile devices

A survey on touch dynamics authentication in mobile devices

A Review of Medication Adherence Monitoring Technologies

Monitoring Technologies for Quantifying Medication Adherence

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