Inferring Autonomic Nervous System Stimulation from Hand and Foot Skin Conductance Measurements

Md Rafiul Amin, Rose T. Faghih

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Abstract

    The autonomic nervous system (ANS) stimulates various sweat glands. Changes in skin conductance measurements indicate sudomotor nerve activity (SMNA), and could be used in inferring the underlying ANS stimulation. We model hand and foot skin conductance measurements simultaneously using a state-space model with Gaussian errors and sparse impulsive events as inputs to the model. Using a multi-rate formulation, we recover the timing and amplitudes of SMNA using a generalized cross-validation based sparse recovery approach. We analyze experimental and simulated data to validate the performance of the proposed approach and illustrate that we are able to recover the underlying auditory stimuli.

    Original languageEnglish (US)
    Title of host publicationConference Record of the 52nd Asilomar Conference on Signals, Systems and Computers, ACSSC 2018
    EditorsMichael B. Matthews
    PublisherIEEE Computer Society
    Pages655-660
    Number of pages6
    ISBN (Electronic)9781538692189
    DOIs
    StatePublished - Feb 19 2019
    Event52nd Asilomar Conference on Signals, Systems and Computers, ACSSC 2018 - Pacific Grove, United States
    Duration: Oct 28 2018Oct 31 2018

    Publication series

    NameConference Record - Asilomar Conference on Signals, Systems and Computers
    Volume2018-October
    ISSN (Print)1058-6393

    Conference

    Conference52nd Asilomar Conference on Signals, Systems and Computers, ACSSC 2018
    Country/TerritoryUnited States
    CityPacific Grove
    Period10/28/1810/31/18

    ASJC Scopus subject areas

    • Signal Processing
    • Computer Networks and Communications

    Fingerprint

    Dive into the research topics of 'Inferring Autonomic Nervous System Stimulation from Hand and Foot Skin Conductance Measurements'. Together they form a unique fingerprint.

    Cite this