TY - GEN
T1 - Inferring Autonomic Nervous System Stimulation from Hand and Foot Skin Conductance Measurements
AU - Amin, Md Rafiul
AU - Faghih, Rose T.
N1 - Funding Information:
This work was supported in part by NSF 1755780.
Funding Information:
Md. Rafiul Amin and Rose T. Faghih are with the Computational Medicine Lab in the Department of Electrical and Computer Engineering, University of Houston, Houston, TX, 77204-4005 USA e-mail: [email protected], [email protected] This work was supported in part by NSF 1755780.
Publisher Copyright:
© 2018 IEEE.
PY - 2018/7/2
Y1 - 2018/7/2
N2 - 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.
AB - 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.
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U2 - 10.1109/ACSSC.2018.8645408
DO - 10.1109/ACSSC.2018.8645408
M3 - Conference contribution
AN - SCOPUS:85062942720
T3 - Conference Record - Asilomar Conference on Signals, Systems and Computers
SP - 655
EP - 660
BT - Conference Record of the 52nd Asilomar Conference on Signals, Systems and Computers, ACSSC 2018
A2 - Matthews, Michael B.
PB - IEEE Computer Society
T2 - 52nd Asilomar Conference on Signals, Systems and Computers, ACSSC 2018
Y2 - 28 October 2018 through 31 October 2018
ER -