A method for selecting parameters of at least one security or design element to be incorporated in the manufacture of a banknote to facilitate recognition of the banknote thereby increasing the security, characterized by comprising the following steps: a) providing a user with a plurality of banknotes that differ in at least one parameter of at least one security or design element of the banknote; b) for each banknote, defining at least one area of interest that includes the area of the banknote occupied by the at least one security or design element; c) acquiring, by sensor means integrated in an input module, biometric signals for eye tracking , gestural behavior , analysis of facial expression , brain response , heart rate variability and skin conductance , in response to visual, tactile and sound stimulation of the user with the plurality of banknotes; as well as explicit responses to submitted questionnaires; d) conditioning the acquired biometric signals comprising segmenting the acquired biometric signals into predetermined periods of time in a process module , wherein said biometric signals are associated with at least one defined area of interest; e) comparing each of the biometric signal segments with pre-established patterns and identifying certain events as a result of the comparison; f) obtaining at least one biometric variable based on the identified events; g) analyzing the biometric variables in the process module according to previously known results stored in a database using machine learning techniques, and generating partial neurometric indicators associated to each banknote, comprising a user visual interest indicator , an engagement indicator , a workload indicator , an emotional indicator and a security indicator ; h) establishing a global neurometric indicator as a result of a weighting of the partial neurometric indicators; and i) selecting the parameters of the at least one security or design element to be incorporated in the manufacture of the banknote according to the global neurometric indicator established for each banknote. a) providing a user with a plurality of banknotes that differ in at least one parameter of at least one security or design element of the banknote; b) for each banknote, defining at least one area of interest that includes the area of the banknote occupied by the at least one security or design element; c) acquiring, by sensor means integrated in an input module, biometric signals for eye tracking , gestural behavior , analysis of facial expression , brain response , heart rate variability and skin conductance , in response to visual, tactile and sound stimulation of the user with the plurality of banknotes; as well as explicit responses to submitted questionnaires; d) conditioning the acquired biometric signals comprising segmenting the acquired biometric signals into predetermined periods of time in a process module , wherein said biometric signals are associated with at least one defined area of interest; e) comparing each of the biometric signal segments with pre-established patterns and identifying certain events as a result of the comparison; f) obtaining at least one biometric variable based on the identified events; g) analyzing the biometric variables in the process module according to previously known results stored in a database using machine learning techniques, and generating partial neurometric indicators associated to each banknote, comprising a user visual interest indicator , an engagement indicator , a workload indicator , an emotional indicator and a security indicator ; h) establishing a global neurometric indicator as a result of a weighting of the partial neurometric indicators; and i) selecting the parameters of the at least one security or design element to be incorporated in the manufacture of the banknote according to the global neurometric indicator established for each banknote. <EOS>