The very first step to start psychophysical experiments

Kuroda, Takeshi; Hasuo, Emi

doi:10.1250/ast.35.1

Cited by 19 publications

(13 citation statements)

References 27 publications

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“…Other Timing Methods Another way to investigate processes of prospective timing is to return to Fechner's traditional methods. Kuroda and Hasuo (2014) described ways of using method of limits and of adjustments, in addition of the constant method. For instance, a participant can be presented the standard and comparison intervals, and adjust the comparison interval to make it equal to the standard (method of adjustment).…”

Section: 3mentioning

confidence: 99%

Prospective and Retrospective Timing Processes: Theories, Methods, and Findings

Block¹,

Grondin²,

Zakay³

2018

Timing and Time Perception: Procedures, Measures, &Amp; Applications

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Section: 3mentioning

confidence: 99%

Prospective and Retrospective Timing Processes: Theories, Methods, and Findings

Block¹,

Grondin²,

Zakay³

2018

Timing and Time Perception: Procedures, Measures, &Amp; Applications

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“…The PSE is defined as the mean of the cumulative normal distribution function, indicating the interpolated 50% crossover point. The JND is calculated by multiplying the standard deviation of the fitted cumulative normal distribution with a Zscore of probability of 0.75 (approximately 0.6745), indicating the distance between any two X-axis values where the function crosses 0.50 and 0.75 (or 0.25 and 0.50) [20]. A shift in PSE indicates the time during which people feel perceptual simultaneity has been changed.…”

Section: Plos Onementioning

confidence: 99%

Perceptual simultaneity and its modulation during EMG-triggered motion induction with electrical muscle stimulation

et al. 2020

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When human movement is assisted or controlled with a muscle actuator, such as electrical muscle stimulation, a critical issue is the integration of such induced movement with the person's motion intention and how this movement then affects their motor control. Towards achieving optimal integration and reducing feelings of artificiality and enforcement, we explored perceptual simultaneity through electrical muscle stimulation, which involved changing the interval between intentional and induced movements. We report on two experiments in which we evaluated the ranges between detection and stimulus for perceptual simultaneity achievable with an electromyography-triggered electrical muscle stimulation system. We found that the peak range was approximately 80-160 ms, with the timing of perceptual simultaneity shifting according to different adaptation states. Our results indicate that perceptual simultaneity is controllable using this adaptation strategy.

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“…For JND estimation, we leveraged the method of constant stimuli (Woodworth and Schlosberg, 1954;Kuroda and Hasuo, 2014), considering the human perception in weightlifting as an example.…”

Section: Strategy For Estimating Jndsmentioning

confidence: 99%

Predicting the Working Time of Microtasks Based on Workers' Perception of Prediction Errors

Saito

Chiang

Savage

et al. 2019

HCj

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Crowd workers struggle to earn adequate wages. Given the limited task-related information provided on crowd platforms, workers often fail to estimate how long it would take to complete certain microtasks. Although there exist a few third-party tools and online communities that provide estimates of working times, such information is limited to microtasks that have been previously completed by other workers, and such tasks are usually booked immediately by experienced workers. This paper presents a computational technique for predicting microtask working times (i.e., how much time it takes to complete microtasks) based on past experiences of workers regarding similar tasks. The following two challenges were addressed during development of the proposed predictive model --- (i) collection of sufficient training data labeled with accurate working times, and (ii) evaluation and optimization of the prediction model. The paper first describes how 7,303 microtask submission data records were collected using a web browser extension --- installed by 83 Amazon Mechanical Turk (AMT) workers --- created for characterization of the diversity of worker behavior to facilitate accurate recording of working times. Next, challenges encountered in defining evaluation and/or objective functions have been described based on the tolerance demonstrated by workers with regard to prediction errors. To this end, surveys were conducted in AMT asking workers how they felt regarding prediction errors in working times pertaining to microtasks simulated using an "imaginary" AI system. Based on 91,060 survey responses submitted by 875 workers, objective/evaluation functions were derived for use in the prediction model to reflect whether or not the calculated prediction errors would be tolerated by workers. Evaluation results based on worker perceptions of prediction errors revealed that the proposed model was capable of predicting worker-tolerable working times in 73.6% of all tested microtask cases. Further, the derived objective function contributed to realization of accurate predictions across microtasks with more diverse durations.

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The very first step to start psychophysical experiments

Cited by 19 publications

References 27 publications

Prospective and Retrospective Timing Processes: Theories, Methods, and Findings

Prospective and Retrospective Timing Processes: Theories, Methods, and Findings

Perceptual simultaneity and its modulation during EMG-triggered motion induction with electrical muscle stimulation

Predicting the Working Time of Microtasks Based on Workers' Perception of Prediction Errors

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