The Human–Biometric-Sensor Interaction Evaluation Method: Biometric Performance and Usability Measurements

Kukula, Eric P.; Sutton, Mathias J.; Elliott, Stephen J.

doi:10.1109/tim.2009.2037878

Cited by 55 publications

(31 citation statements)

References 6 publications

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“…[ 1,2 ] The development of sensor technology has made it possible to detect responses even without physical contact and devices of this kind, the so-called "proximity sensors", have been integrated in robotics, mechatronics, wearable electronics, and optoelectronics. [ 3,4 ] Though these sensor materials generally are based on many mechanisms such as electromagnetic induction, infrared emission, ultrasonic wave detection etc., capacitance or resistance measurements still offer an easier way.…”

Section: Introductionmentioning

confidence: 99%

Transparent and Flexible Cellulose Nanocrystal/Reduced Graphene Oxide Film for Proximity Sensing

Sadasivuni

Kafy

Zhai

et al. 2014

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The rapid development of touch screens as well as photoelectric sensors has stimulated the fabrication of reliable, convenient, and human-friendly devices. Other than sensors that detect physical touch or are based on pressure sensing, proximity sensors offer controlled sensibility without physical contact. In this work we present a transparent and eco-friendly sensor made through layer-by-layer spraying of modified graphene oxide filled cellulose nanocrystals on lithographic patterns of interdigitated electrodes on polymer substrates, which help to realize the precise location of approaching objects. Stable and reproducible signals generated by keeping the finger in close proximity to the sensor can be controlled by humidity, temperature, and the distance and number of sprayed layers. The chemical modification and reduction of the graphene oxide/cellulose crystal composite and its excellent nanostructure enable the development of proximity sensors with faster response and higher sensitivity, the integration of which resolves nearly all of the technological issues imposed on optoelectronic sensing devices.

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Section: Introductionmentioning

confidence: 99%

Transparent and Flexible Cellulose Nanocrystal/Reduced Graphene Oxide Film for Proximity Sensing

Sadasivuni

Kafy

Zhai

et al. 2014

Small

186

132

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“…FAR, FRR, and FTA are frequently mentioned in the literature as factors affecting both user perceptions of system performance and overall user satisfaction with the system (Braz & Robert, 2006;ElAbed, Gio, Hemery, & Rosenberger, 2012;Kukula, Sutton, & Elliott, 2010). There is, however, no known literature suggesting links between these system characteristics and user privacy perceptions.…”

Section: Employee Distrustmentioning

confidence: 99%

A multicultural study of biometric privacy concerns in a fire ground accountability crisis response system

Carpenter

Maasberg

Hicks

et al. 2016

International Journal of Information Management

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“…These metrics have been successfully used for the assessment of fingerprint systems and have shown that clear distinctions of systems-related and user-related errors can be made within the analysis of system performance [6], [15]. …”

Section: The Human-biometric Sensor Interactionmentioning

confidence: 99%

“…In an attempt to assess, understand and react to biometric systems usability issues, the HBSI model was developed [6] to present a user-centric assessment of performance, enabling usage errors to be decomposed and attributed to a multitude of factors including incorrect user interaction, performance modification due to ergonomics and user interface, and error in sampling/poor quality of sample, alongside conventional measurements of algorithmic performance. Adopting this model it is possible for developers, integrators and end-users to pinpoint exactly where usage error occurs.…”

Section: Introductionmentioning

confidence: 99%

An assessment of the usability of biometric signature systems using the human-biometric sensor interaction model

Guest

Brockly

Elliott

et al. 2016

IJCAT

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(2016) An assessment of the usability of biometric signature systems using the human-biometric sensor interaction model'.International AbstractSignature biometrics is a widely used form of user authentication. As a behavioural biometric, samples have inherent inconsistencies which must be accounted for within an automated system. Performance deterioration of a tuned biometric software system may be caused by an interaction error with a biometric capture device, however, using conventional error metrics, system and user interaction errors are combined, thereby masking the contribution by each element. In this paper we explore the application of the Human-Biometric Sensor Interaction (HBSI) model to signature as an exemplar of a behavioural biometric. Using observational data collected from a range of subjects, our study shows that usability issues can be identified specific to individual capture device technologies. While most interactions are successful, a range of common interaction errors need to be mitigated by design to reduce overall error rates.

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The Human–Biometric-Sensor Interaction Evaluation Method: Biometric Performance and Usability Measurements

Cited by 55 publications

References 6 publications

Transparent and Flexible Cellulose Nanocrystal/Reduced Graphene Oxide Film for Proximity Sensing

Transparent and Flexible Cellulose Nanocrystal/Reduced Graphene Oxide Film for Proximity Sensing

A multicultural study of biometric privacy concerns in a fire ground accountability crisis response system

An assessment of the usability of biometric signature systems using the human-biometric sensor interaction model

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