By Alberto Greco, Gaetano Valenza, Enzo Pasquale Scilingo
This booklet explores Autonomic apprehensive method (ANS) dynamics as investigated via Electrodermal task (EDA) processing. It offers groundbreaking study within the technical box of biomedical engineering, particularly biomedical sign processing, in addition to scientific fields of psychometrics, affective computing, and mental evaluation. This quantity describes probably the most whole, potent, and custom-made methodologies for extracting info from a non-stationary, nonlinear EDA sign on the way to symbolize the affective and emotional country of a human topic. those methodologies are underscored through dialogue of real-world purposes in temper evaluate. The textual content additionally examines the physiological bases of emotion reputation via noninvasive tracking of the autonomic worried approach. this can be an excellent ebook for biomedical engineers, physiologists, neuroscientists, engineers, utilized mathmeticians, psychiatric and mental clinicians, and graduate scholars in those fields.
This ebook additionally:
Expertly introduces a unique technique for EDA research in keeping with convex optimization and sparsity, an issue of swiftly expanding curiosity
Authoritatively offers groundbreaking learn completed utilizing EDA as an exemplary biomarker of ANS dynamics
Deftly explores EDA's strength as a resource of trustworthy and potent markers for the review of emotional responses in fit matters, in addition to for the popularity of pathological temper states in bipolar patients
Read Online or Download Advances in Electrodermal Activity Processing with Applications for Mental Health: From Heuristic Methods to Convex Optimization PDF
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Additional info for Advances in Electrodermal Activity Processing with Applications for Mental Health: From Heuristic Methods to Convex Optimization
Each method returns an output that can be an index or the central state, but we have to measure which method estimates the central state at best. A possible evaluation process uses an experimental paradigm in order to create two central states that are known to be different. Thus, the method can be evaluated investigating the ability to detect this difference. This is achieved using a statistical approach on the features extracted that quantify the central activation. In this book, we first present a conventional modeling approach, the Continuous Deconvolution Analysis (CDA) , and a recently proposed model proposed by Greco et al.
Nowadays, a remarkable theory of emotion belongs to the neurobiologist Joseph LeDoux, who believed that the perception of an affective stimulus activates two neural information paths that are independent but interconnected: an unconscious path activating the peripheral reactions, and a conscious one producing the experience cognitive awareness of emotion . According to LeDoux, one of the neural centers related to the unconscious way is the amygdala. This region makes a first process, of the stimulus perception, even with absence of awareness.
In the context of mathematical optimization, the most important consequence of convexity is that necessary conditions for local optimality are also sufficient for global optimality. Moreover, important categories of convex optimization problems can be solved efficiently (this is rarely the case for general nonconvex problems). A special subclass of convex optimization problems is represented by leastsquare problems where the goal is the unconstrained minimization of a quadratic objective function kAx bk22 .