Predicting Success Rates in Steering Through Linear and Circular Paths by the Servo-Gaussian Model

Yamanaka, Shota; Usuba, Hiroki; Takahashi, Haruki; Miyashita, Homei

doi:10.1080/10447318.2023.2212221

Cited by 1 publication

(2 citation statements)

References 90 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…where A is the path length, W is the width, and a and b are regression constants. This model holds both for error-free [3], [38] and error-inclusive MT data [17], [41]. Previous studies have shown the validity of the model for various conditions such as using touchpads and trackballs [2] and moving towards various directions [29], [45].…”

Section: Time-prediction Model For Path-steering Tasksmentioning

confidence: 66%

See 1 more Smart Citation

Sample-size and Repetition Effects on the Prediction Accuracy of Time and Error-rate Models in Steering Tasks

Yamanaka

2024

Journal of Information Processing

Self Cite

View full text Add to dashboard Cite

A previous study on target pointing has shown that the accuracy of performance models improves as the number of participants and clicks increases, but the task was limited to artificially simplified one-dimensional movements. Practical user interfaces often require more complex operations, and thus we examine the effects of the number of participants and task repetitions on the fit of existing models for path-steering tasks. Empirical results showed that the model for predicting movement times consistently fitted the data with high accuracy, even when the numbers of participants and repetitions were small. However, the model for predicting error rates was less accurate in terms of R 2 , MAE, and RMSE. Therefore, the benefit of recruiting numerous participants is relatively greater for the error-rate prediction model, which supports the previous study on target-pointing tasks.

show abstract

Section: Time-prediction Model For Path-steering Tasksmentioning

confidence: 66%

“…In contrast, for the Keep rule, particularly for narrow path conditions, it is possible that some participants failed all ten trials and thus ER was 100%, resulting in no error-free MTs. Because the steering law holds for error-inclusive MT data [17], [41], we apply all ten trials' MTs to the steering law.…”

Section: Design and Proceduresmentioning

confidence: 99%

Sample-size and Repetition Effects on the Prediction Accuracy of Time and Error-rate Models in Steering Tasks

Yamanaka

2024

Journal of Information Processing

Self Cite

View full text Add to dashboard Cite

show abstract

Predicting Success Rates in Steering Through Linear and Circular Paths by the Servo-Gaussian Model

Cited by 1 publication

References 90 publications

Sample-size and Repetition Effects on the Prediction Accuracy of Time and Error-rate Models in Steering Tasks

Sample-size and Repetition Effects on the Prediction Accuracy of Time and Error-rate Models in Steering Tasks

Contact Info

Product

Resources

About