Gaetano Valenza, Enzo Pasquale Scilingo's Autonomic Nervous System Dynamics for Mood and PDF

By Gaetano Valenza, Enzo Pasquale Scilingo

ISBN-10: 3319026380

ISBN-13: 9783319026381

ISBN-10: 3319026399

ISBN-13: 9783319026398

This monograph reviews on advances within the size and examine of autonomic fearful method (ANS) dynamics as a resource of trustworthy and powerful markers for temper nation acceptance and evaluate of emotional responses. Its basic impression could be in affective computing and the applying of emotion-recognition structures. Applicative reports of biosignals reminiscent of: electrocardiograms; electrodermal responses; respiratory task; gaze issues; and pupil-size version are lined intimately, and experimental effects clarify find out how to represent the elicited affective degrees and temper states pragmatically and properly utilizing the data therefore extracted from the ANS. Nonlinear sign processing recommendations play a very important position in figuring out the ANS body structure underlying superficially visible alterations and supply very important quantifiers of cardiovascular regulate dynamics. those have prognostic worth in either fit matters and sufferers with temper problems. additionally, Autonomic anxious method Dynamics for temper and Emotional-State popularity proposes a unique probabilistic strategy in line with the point-process idea on the way to version and signify the instant ANS nonlinear dynamics supplying a starting place from which laptop “understanding” of emotional reaction should be superior. utilizing arithmetic and sign processing, this paintings additionally contributes to pragmatic concerns resembling emotional and mood-state modeling, elicitation, and non-invasive ANS tracking. in the course of the textual content a serious evaluation at the present state of the art is pronounced, resulting in the outline of committed experimental protocols, novel and trustworthy temper types, and novel wearable platforms capable of practice ANS tracking in a naturalistic atmosphere. Biomedical engineers will locate this booklet of curiosity, particularly these considering nonlinear research, as will researchers and commercial technicians constructing wearable platforms and sensors for ANS monitoring.

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Additional info for Autonomic Nervous System Dynamics for Mood and Emotional-State Recognition: Significant Advances in Data Acquisition, Signal Processing and Classification

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L. 67 Hz to 40 Hz Analog-to-digital conversion 16 bits Sampling rate 250 Hz Respiration signal Measurement principle Piezoresistive method Range of electrical resistance 20 k Bandwidth DC to 10 Hz Resolution 12 bits Sampling rate 25 Hz to 10 M Fig. 1 Photometric Normalization Technique The purpose of the illumination normalization is to reduce or eliminate some variations in the captured eyes due to different conditions of illumination. It normalizes and enhances the eye image to improve the recognition performance of the system.

The proposed sampling rate is set to 250 Hz for all signals. 05–35 Hz) connected with pregelled Ag/AgCl electrodes placed following Einthoven triangle configuration. In the procedures reported in this book, ECG signal was used to extract the HRV [98], which reflects the sympathetic-parasympathetic balance. 05 ÷ 10 Hz. This piezoresistive sensor changed its electrical resistance if stretched or shortened, and it was sensitive to the thoracic circumference variations occurring during respiration [233].

13 Hz). 3 Portable and Novel Wearable Systems for ANS Monitoring 37 Fig. 12 Electric circuit used for the impedance characterization of the textile electrode (from [22]) RT is the charge–transfer resistance and Re is the spreading resistance. 3) where A is the electrode area and k [ s−1/2 cm2 ] is constant. The low frequency of EDRs implies, according to previous works [228], that both Warburg and interface capacitance terms are important for this characterization. All the experiments were carried out at 25◦ C and pressure of 1 atm.

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Autonomic Nervous System Dynamics for Mood and Emotional-State Recognition: Significant Advances in Data Acquisition, Signal Processing and Classification by Gaetano Valenza, Enzo Pasquale Scilingo

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