Combining Human Error Verification and Timing Analysis

Rukšėnas, Rimvydas; Curzon, Paul; Blandford, Ann; Back, Jonathan

doi:10.1007/978-3-540-92698-6_2

Cited by 9 publications

(3 citation statements)

References 19 publications

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“…PUMs have been used to model different classes of human operator (expert versus novice) [29] in order to investigate when different types of operators may perform different errors when interacting with an automated teller machine (ATM). Keystrokelevel timing analysis [26], [27] have been added into Curzon et al's [29] framework and used to evaluate timing performance of a human operator interacting with the ATM [30]. Similar to GOMS, KLM timing analyses estimate time with the provision that the sequence of actions required to perform a task is executed without error.…”

Section: A User Models In Human-computer Interactionmentioning

confidence: 99%

A Human Operator Model for Medical Device Interaction Using Behavior-Based Hybrid Automata

Niezen

Eslambolchilar

2016

IEEE Trans. Human-Mach. Syst.

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This paper describes the design and implementation of a control-theoretic model that can be used to model both the discrete and continuous behavior of a human operator. The human operator model can be used to compare different device user interfaces in terms of human performance. The implemented human operator model combines an ON-OFF control model and a behavior-based hybrid automaton with three controllers. The controllers, defined as continuous, discrete, and fine-tuning behavior, simulate the user's conceptual model of the user interface. The device model used is that of a commercial syringe pump with chevron keys, described as a formal specification. Results of the human operator model simulation were generated for 20 different numbers obtained from syringe pump log files. The simulation results were compared over 33 trials to a lab study employing a device based on the formal specification. The result of the simulation shows a significant similarity to the result of the lab study for all the numbers used.

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Section: A User Models In Human-computer Interactionmentioning

confidence: 99%

A Human Operator Model for Medical Device Interaction Using Behavior-Based Hybrid Automata

Niezen

Eslambolchilar

2016

IEEE Trans. Human-Mach. Syst.

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“…These concepts and the classifications above provide support for reasoning about human errors and have been widely used to develop approaches to design and evaluate interactive systems [26]. As pointed out in [20] investigating the association between a phenotype and its potential genotypes is very difficult but is an important step in order to assess the error-proneness of an interactive system.…”

Section: Considering Human Errorsmentioning

confidence: 99%

Accounting for Organisational faults in Task Model Based Systematic Analysis of System Failures and Human Errors

Fayollas,

Martinie,

Palanque

et al. 2015

Schriften Aus Der Fakultät Wirtschaftsinformatik Und Angewandte Informatik Der Otto-Friedrich-Universität Bamberg

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The overall dependability of an interactive system is the one of its weakest component which is usually its user interface. The presented approach integrates techniques from the dependable computing field and elements of usercentred design to provide a wider coverage of possible faults. Risk analysis and fault tolerance techniques are used in combination with task analysis and modelling to describe and analyse the impact of system faults on human activities and the impact of human deviation or errors on system performance and overall mission performance. A technique for systematic analysis of human errors, effects and criticality is proposed (HEECA). It is inspired and adapted from the Failure Mode, Effects and Criticality Analysis (FMECA) technique. The key points of the approach are: a) the HEECA technique combining a systematic analysis of the effects of system faults and of human errors, b) a task modelling notation to describe and to assess the impact of system faults and human errors on operators' activities and system performance. These key points are illustrated on an example extracted from a case study of the space domain. It demonstrates the feasibility of this approach as well as its benefits in terms of identifying opportunities for re-designing the system, re-designing the operations and for modifying operators' training. Lastly, a discussion presents the main challenges for also taking into account organisational faults in an integrated way with the proposed approach.

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“…Given the formality with which these are specified, it is likely they could be incorporated into the formal verification analyses similar to those discussed here. For example, Rukšėnas et al [177] have investigated ways of performing keystroke-level timing analysis (similar to that used by KLM-GOMS [52]) with human behaviors generated using their cognitive-modeling and formal verification infrastructure. Potential exists for further integrating human performance modeling and formal verification analyses where models of trust, situation awareness, and workload could be integrated into formal models or, as with the timing analysis of Rukšėnas et al, the output of formal verifications could be made to work with such models.…”

Section: B Supporting Other Hai Analyses With Formal Verificationmentioning

confidence: 99%

Using Formal Verification to Evaluate Human-Automation Interaction: A Review

Bolton

Bass

Siminiceanu

2013

IEEE Trans. Syst. Man Cybern, Syst.

147

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Failures in complex systems controlled by human operators can be difficult to anticipate because of unexpected interactions between the elements that compose the system, including human-automation interaction (HAI). HAI analyses would benefit from techniques that support investigating the possible combinations of system conditions and HAIs that might result in failures. Formal verification is a powerful technique used to mathematically prove that an appropriately scaled model of a system does or does not exhibit desirable properties. This paper discusses how formal verification has been used to evaluate HAI. It has been used to evaluate human-automation interfaces for usability properties and to find potential mode confusion. It has also been used to evaluate system safety properties in light of formally modeled task analytic human behavior. While capable of providing insights into problems associated with HAI, formal verification does not scale as well as other techniques such as simulation. However, advances in formal verification continue to address this problem, and approaches that allow it to complement more traditional analysis methods can potentially avoid this limitation.

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Combining Human Error Verification and Timing Analysis

Cited by 9 publications

References 19 publications

A Human Operator Model for Medical Device Interaction Using Behavior-Based Hybrid Automata

A Human Operator Model for Medical Device Interaction Using Behavior-Based Hybrid Automata

Accounting for Organisational faults in Task Model Based Systematic Analysis of System Failures and Human Errors

Using Formal Verification to Evaluate Human-Automation Interaction: A Review

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