Types

• Law

Own Slots
	Slot Name	Value
	reference	The information capacity of the human motor system in controlling the amplitude of movement, Towards a standard for pointing device evaluation: Perspectives on 27 years of Fitts’ law research in HCI
	related knowledge	Закон Хика
	supported by
	tag	Size, Error rate, Performance time, Layout
	text (english)	On the inapplicability of the Fitts’ Law to the elderly users The upper limb movement is fundamental human body movement to interact with computers. The purpose of the study is to examine the upper limb motor behavior of the elder persons and the applicability of Fitts’ law (Fitts, 1954). Fitts’ law is one of the most important and widely recognized empirical findings in the field of human-computer interaction, and it predicts the movement time thusly: , where MT is movement time, a and b are constants, A is distance to the target, W is width of the target, and a logarithmic element is the index of difficulty (ID). Many scientists have confirmed the law for a large variety of task conditions (Kerr, 1973; Jagacinski and Monk, 1985; Kantowitz and Elvers, 1988) and for humans as well as for animals (Brooks, 1979). Many researchers have reported usually very high R2 statistics (coefficient of determination) in Fitts’ law model (MacKenzie and Buxton, 1992; Hinckley et al., 2002; Card et al., 1983). Movement Time and Reaction Time of the Elderly In relation to HCI researchers, the law applies as a predictive model to pointing and dragging with the mouse, trackball, stylus, joystick, and touchscreen. The Fitts’ law can be used to predict time for both simple actions, e.g. moving a cursor with the mouse to select a menu option and complex tasks. The law can be applied, for example, to calculate the time required to type a word using a stylus on a soft-keyboard by summing the Fitts’ movement times of a series of letter-to-letter stylus movements over the keyboard (Soukoreff and MacKenzie, 1995). However, despite the popularity of Fitts’ law and a large number of publications on this matter, it seems that the problem of its applicability to such group as elder people has been neglected (Soukoreff and MacKenzie, 2004, p. 778). There are recognized assumptions for Fitts’ law including non-constrained and non-breaking movement, potential biases connected with habitual and serial tasks, target shapes, as well as with devices used for moving and pointing (MacKenzie, 1991). The Fitts’ law provides a very good fit to the empirical data, but no satisfactory psychomotor theory exists that explains the law (Soukoreff and MacKenzie, 2004). *** As rapid aimed movements are required to interact with most modern software interfaces, Fitts’ law [4] remains one of the most important and recognized empirical findings in the field. The common expression of the law [13, p.755], following from Shannon’s 17th Theorem is: (1) MT represents movement time required to reach a target of size (width) W at distance A, and the two constants (a, b) are generally found using regression analysis. The logarithm part is called the index of difficulty (ID): (2) Thus, Fitts’ law establishes relationship between movement time, distance and accuracy, via effective target size [13, p.756], and is known as robust and highly adaptive model. In HCI, the law is used both as predictive model, in particular for interface design, and for evaluation and comparison of various conditions and interface devices, such as mouse, trackball, touch screen, etc. [12, p.281], via derivative measure of throughput [13, p. 759]. Fitts’ law generally provides a very good fit to empirical data, but no satisfactory psychomotor theory exists to explain the law [12, p. 286]. Also, some researchers reported cases when Fitts’ law did not correspond well to the MT data for some special user groups or in special circumstances, such as for individuals with cerebral palsy [5].
	text (russian)	MT = a + b * ID = a + b * log2(A/W+1) где MT – время движения, необходимое для достижения цели размера (шириной) W на расстоянии A. Две константы, a и b, как правило, находятся при помощи регрессионного анализа, а логарифмическая часть называется индексом сложности ID. Закон Фиттса соответствует номинальной точности 96%.

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