An empirical model of aimed movement time stating that the time to move rapidly to a target (movement time MT) is approximately a linear function of an index of difficulty ID = log2(2D/W), where D is distance to target center and W is target width along the movement axis; commonly written MT = a + b · log2(2D/W) with constants a,b fit to data.

Principle

Aimed movement time increases with the logarithm of the ratio of movement distance to target size, reflecting a speed–accuracy tradeoff: farther or smaller targets require slower, more precise control and therefore longer movement times.

Demonstration

Illustrative scenario → A user points with a mouse to targets at varying distances and widths. Recognition → Measured movement times plotted against ID fall roughly on a straight line. Action → Fit MT = a + b·log2(2D/W) to obtain a and b for that device and user. Consequence → The model predicts that increasing button size or reducing distance reduces selection time and guides layout decisions for interactive surfaces.

Misapplication

Applying Fitts’s formula unchanged to continuous tracking, to tasks dominated by visual search or decision time, or assuming the coefficients a and b are identical across input devices, control-display gains, or users without recalibration.

Consequence

Correct use quantifies motor contribution to interaction latency and supports ergonomic and interface layout choices (target size, spacing, control‑display mapping); misuse leads to poor predictions when perceptual, cognitive or device dynamics dominate time to selection.

Reversal

For very small W or very short D (near targets), other effects (reaction time floor, device jitter, quantization) dominate; for multi‑segment movements, constrained paths, or highly trained ballistic actions, the simple log model may not hold and more complex or piecewise models are needed.

Boundary

Clearly within: rapid, discrete pointing movements to stationary targets where accuracy along the motion axis is the principal constraint. Boundary case: targets with similar visual distractors requiring additional search. Clearly outside: continuous tracking tasks, tasks where decision time (Hick) or perceptual search dominates, or selections mediated by non‑pointing modalities without spatial distance metrics.

Semantic Tension

Fitts’s Law ↔ Hick’s Law — Fitts quantifies the motor speed–accuracy component of interaction time while Hick quantifies the cognitive choice component; both constrain user performance and must be combined when tasks require both decision and movement.

Synthesis

Fitts’s Law isolates the motoric speed–accuracy cost of aiming and provides a practical, device‑dependent predictor for target design, but real interfaces require integrating perceptual, cognitive and device dynamics alongside the model’s parameters.