Fitt's Law Replication

by Vivek R. Shivaprabhu

Paul M. Fitts modeled human psychomotor behavior by describing the phenomena of variability of a response as a function of response duration using information theory concepts. He introduced an index of difficulty of a movement which relates average values for amplitude, duration and variability of successive movements [1]. He proposed a speed-accuracy trade-off using a principle of motor control where activities done quicker can be less accurate than those activities done slower.

For a brief explanation of Fitts' Law see below.
For a more detailed explanation and sample experimental results, click here.
Please select values for the following parameters and click Begin.

Number of Targets 16
Target Sizes (Radius) 30
Distances 250


ISO 9241-9 establishes uniform guidelines and testing procedures for evaluating computer pointing devices. The metric for comparison is Throughput, in bits per second (bits/s), which includes both the speed and accuracy of users' performance. The equation for throughput is Fitts’ Index of Performance except using an effective index of difficulty (ID). Specifically,

     Throughput = ID / MT      (1)

where MT is the mean movement time, in seconds, for all trials within the same condition, and

     ID = log2(D / W + 1)      (2)

ID, in bits, is calculated from D, the distance to the target, and W, the effective width of the target. W is calculated as

     W = 4.133 × SD            (3)

where SD is the standard deviation of the end-point positions using observed end-point scatter data. Using effective width allows throughput to incorporate the spatial variability in human performance. It includes both speed and accuracy [1].


  1. MacKenzie, I.S., Fitts’ law as a research and design tool in human-computer interaction. Human-Computer Interaction 7, 91–139 (1992).
  2. Soukoreff, R. W., & MacKenzie, I. S. (2004). Towards a standard for pointing device evaluation: Perspectives on 27 years of Fitts' law research in HCI. International Journal of Human-Computer Studies, 61, 751-789.