Fitts Law Movement Time
Evaluate the Shannon formulation MT = a + b × log2(1 + D/W), using distance and width in the same units and caller-fitted coefficients in milliseconds. Predictions must be nonnegative.
Description
The Shannon form of Fitts’s law relates movement time to distance relative to target width.
The Shannon form of Fitts’s law relates movement time to distance relative to target width. Fitted coefficients supply the empirical timing relationship for the intended task.1
Evaluate the Shannon formulation MT = a + b × log2(1 + D/W), using distance and width in the same units and caller-fitted coefficients in milliseconds. Predictions must be nonnegative.
When to use Fitts Law Movement Time
Use this tool to evaluate the Shannon formulation MT = a + b × log2(1 + D/W), using distance and width in the same units and caller-fitted coefficients in milliseconds. Predictions must be nonnegative.
Prepare the task-specific rates, comparable response-time means, identified spike train, processed ERP or estimated spectra requested. Confirm units, preprocessing, sample pairing and caller-fitted model coefficients.
How to use Fitts Law Movement Time and understand its results
- Prepare the task-specific rates, comparable response-time means, identified spike train, processed ERP or estimated spectra requested. Confirm units, preprocessing, sample pairing and caller-fitted model coefficients.
- Enter distance, width, interceptMs, slopeMsPerBit using the field table and calculation rules, then run the tool.
- Read indexOfDifficultyBits, movementTimeMs. The explanation below defines the units, signs, ordering and any flags or placeholder values.
- If the tool reports an input issue, correct the values and run it again. Apply the stated assumptions when interpreting a successfully returned result.
| Input field | Meaning | Value type; see rules below | Requirement |
|---|---|---|---|
| distance | Movement distance in the same units as width. | number; minimum: 0 | Required |
| width | Target width along the movement axis. | number; strictly above: 0 | Required |
| interceptMs | Fitted intercept a. (ms) | number | Required |
| slopeMsPerBit | Fitted slope b. (ms/bit) | number | Required |
Enter nonnegative distance, positive width in the same units and finite fitted coefficients. Compute difficulty, using an equivalent logarithmic expression if the direct ratio overflows. Reject nonfinite or negative predicted time. Zero distance gives zero difficulty.
difficultyBits=log2(1+distance/width); movementTimeMs=intercept+slope×difficultyBits Units, indexing, boundary conditions and exceptional cases are defined in the calculation rules above.
| Output field | Meaning | Value type |
|---|---|---|
| indexOfDifficultyBits | Shannon index of difficulty. (bit) | number; minimum: 0 |
| movementTimeMs | Predicted movement time. (ms) | number; minimum: 0 |
{
"input": {
"distance": 700,
"width": 100,
"interceptMs": 100,
"slopeMsPerBit": 80
},
"output": {
"indexOfDifficultyBits": 3,
"movementTimeMs": 340
}
}Limitations and assumptions
Target width should follow the movement axis. No geometry, coefficient fitting, accuracy distribution or participant calibration is inferred.
Numeric inputs must be finite. Follow the calculation-specific rules for overflow, underflow and exceptional cases. Missing required fields, extra fields, wrong value types and violations of the calculation rules are input errors.
Alternative or Complementary methods
Use Hick Choice Reaction Time: Evaluate the equally likely choice form RT = a + b × log2(n), using caller-fitted coefficients in milliseconds. Predictions must be nonnegative; this is a model evaluation without participant calibration. For a complementary task, use Weber Fraction: Calculate the dimensionless Weber fraction as measured just-noticeable increment divided by baseline stimulus magnitude. Both magnitudes must use the same linear units; no universal sensory threshold is assumed.
References
-
Fitts Law Movement Time — tool.io
Similar or alternative tools
- Hick Choice Reaction Time
Evaluate the equally likely choice form RT = a + b × log2(n), using caller-fitted coefficients in milliseconds. Predictions must be nonnegative; this is a model evaluation without participant calibration.
- Weber Fraction
Calculate the dimensionless Weber fraction as measured just-noticeable increment divided by baseline stimulus magnitude. Both magnitudes must use the same linear units; no universal sensory threshold is assumed.