A Wearable Brain Machine Interface Architecture for Regulation of Energy in Hypercortisolism

Hamid Fekri Azgomi, Rose T. Faghih

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

Abstract

Hypercortisolism is associated with tiredness and fatigue during the day and disturbed sleep at night. Our goal is to employ a wearable brain machine interface architecture to regulate one's energy in hypercortisolism. First, we present a state-space model to infer a hidden cognitive energy-related state from one's Cortisol secretion patterns. Particularly, we consider circadian upper and lower bound envelope curves on Cortisol levels, and timings of hypothalamic pulsatile activity underlying Cortisol secretion as observations. We then use Bayesian filtering to estimate the hidden cognitive energy-related state. Finally, we close the loop using a knowledge-based control approach. In a simulation study based on experimental data, we illustrate the feasibility of designing a wearable brain machine interface architecture for energy regulation in hypercortisolism. In this architecture, we infer one's cognitive energy-related state seamlessly rather than monitoring the brain activity directly and close the loop using fuzzy control. This simulation study is a first step towards the ultimate goal of managing hypercortisolism in real-world situations.

Original languageEnglish (US)
Title of host publicationConference Record - 53rd Asilomar Conference on Circuits, Systems and Computers, ACSSC 2019
EditorsMichael B. Matthews
PublisherIEEE Computer Society
Pages254-258
Number of pages5
ISBN (Electronic)9781728143002
DOIs
StatePublished - Nov 2019
Event53rd Asilomar Conference on Circuits, Systems and Computers, ACSSC 2019 - Pacific Grove, United States
Duration: Nov 3 2019Nov 6 2019

Publication series

NameConference Record - Asilomar Conference on Signals, Systems and Computers
Volume2019-November
ISSN (Print)1058-6393

Conference

Conference53rd Asilomar Conference on Circuits, Systems and Computers, ACSSC 2019
Country/TerritoryUnited States
CityPacific Grove
Period11/3/1911/6/19

ASJC Scopus subject areas

  • Signal Processing
  • Computer Networks and Communications

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