Abstract
The decision-making model with basic fuzzy rule modus ponens is suggested in this paper to control the hand prosthesis. The hand movements are described by angles of finger and wrist flexion. Electromyogram (EMG) of hand muscles was used as a source of the input data. Software was developed to implement the decision-making model with fuzzy rule modus ponens. In particular, the software receives EMG data, executes calculations and visualises the output data. The key advantage of the model is smoothness of output data changes; this way a maximum approach to natural hand movements is reached.
Highlights
BASIC CONCEPTS AND DEFINITIONSA logical and linguistic description of the relationship of the input and the output control parameters is formed to construct a decision making model (DM)
The decision-making model with basic fuzzy rule modus ponens is suggested in this paper to control the hand prosthesis
Electromyogram (EMG) of hand muscles was used as a source of the input data
Summary
A logical and linguistic description of the relationship of the input and the output control parameters is formed to construct a decision making model (DM). Deductive rule modus ponens has a great significance, which is presented below: P1: if A is a B is b ; P2: A is a true;. The fuzzy inference of System 2 is presented as a maximin composition and as an interpretation of a conditional statement in the form of Mamdani’s implication operation. Exact nonfuzzy value b0 of output parameter B is defined on the basis of the analysis of membership function μ*B (b). The usage of the middle maximum method is problematic at the defuzzification stage, since function B does not have the quasi-concavity property
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