A Cortisol-Based Energy Decoder for Investigation of Fatigue in Hypercortisolism

Wickramasuriya, Dilranjan S.; Faghih, Rose T.

doi:10.1109/embc.2019.8857658

Cited by 20 publications

(39 citation statements)

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“…The human brain detects and mediates the physiologic response to environmental stimuli including cognitive stress tasks [10]. Traditional approaches in monitoring the brain activity directly, e.g.…”

Section: Introductionmentioning

confidence: 99%

Closed-Loop Cognitive Stress Regulation Using Fuzzy Control in Wearable-Machine Interface Architectures

2021

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Keeping cognitive stress at a healthy range can improve the overall quality of life: helping subjects to decrease their high levels of arousal, which will make them relaxed, and elevate their low levels of arousal, which could increase their engagement. With recent advances in wearable technologies, collected skin conductance data provides us with valuable information regarding ones' cognitive stressrelated state. In this research, we aim to create a simulation environment to control a cognitive stress-related state in a closed-loop manner. Toward this goal, by analyzing the collected skin conductance data from different subjects, we model skin conductance response events as a function of simulated environmental stimuli associated with cognitive stress and relaxation. Then, we estimate the hidden stress-related state by employing Bayesian filtering. Finally, we design a fuzzy control structure to close the loop in the simulation environment. Particularly, we design two classes of controllers: (1) an inhibitory controller for reducing cognitive stress and (2) an excitatory controller for increasing cognitive stress. We extend our previous work by implementing the proposed approach on multiple subjects' profiles. Final results confirm that our simulated skin conductance responses are in agreement with experimental data. In a simulation study based on experimental data, we illustrate the feasibility of designing both excitatory and inhibitory closedloop wearable-machine interface architectures to regulate the estimated cognitive stress state. Due to the increased ubiquity of wearable devices capable of measuring cognitive stress-related variables, the proposed architecture is an initial step to treating cognitive disorders using non-invasive brain state decoding.

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Section: Introductionmentioning

confidence: 99%

Closed-Loop Cognitive Stress Regulation Using Fuzzy Control in Wearable-Machine Interface Architectures

2021

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“…The cortisol hormone is the main stress hormone in an individual's body which is secreted in a pulsatile process (Azgomi and Faghih, 2019 ; Taghvafard et al, 2019 ; Wickramasuriya and Faghih, 2019b ; Smyth et al, 2020 ). Cortisol secretion patterns, which are mainly controlled by the hypothalamus, are critical in assessing various functionalities such as regulating blood pressure and adjusting blood glucose levels.…”

Section: Introductionmentioning

confidence: 99%

“…Cortisol secretion patterns, which are mainly controlled by the hypothalamus, are critical in assessing various functionalities such as regulating blood pressure and adjusting blood glucose levels. So, investigating changes in cortisol secretion would shed some light on one's internal energy state variations (Faghih, 2018 ; Wickramasuriya and Faghih, 2019b ; Smyth et al, 2020 ). Adrenocorticotrophic hormone (ACTH) (i.e., a tropic hormone) causes the adrenal cortex to release cortisol in a pulsatile manner (Hakamata et al, 2017 ; Pednekar et al, 2019 , 2020 ).…”

Section: Introductionmentioning

confidence: 99%

“…The clinical observations in Cushing's syndrome patients clearly demonstrate a role for the HPA axis in the regulation of energy balance (Björntorp and Rosmond, 2000 ; Nieuwenhuizen and Rutters, 2008 ; Wickramasuriya and Faghih, 2019b ). While there exist multiple factors to understand one's energy variations, there is not any specific method to directly infer internal energy state.…”

Section: Introductionmentioning

confidence: 99%

“…As someone's energy variations are influenced by changes in their cortisol levels, the objective of this research is to regulate the energy state by monitoring the cortisol secretion patterns. To model the internal energy state and relate it to the cortisol variations, we utilize the state-space model presented in Wickramasuriya and Faghih ( 2019b ). To close the loop, we simulate hypothetical medication dynamics and develop a control system.…”

Section: Introductionmentioning

confidence: 99%

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Closed-Loop Fuzzy Energy Regulation in Patients With Hypercortisolism via Inhibitory and Excitatory Intermittent Actuation

2021

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Hypercortisolism or Cushing's disease, which corresponds to the excessive levels of cortisol hormone, 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 levels in hypercortisolism. In the present simulation study, we generate multi-day cortisol profile data for ten subjects both in healthy and disease conditions. To relate an internal hidden cognitive energy state to one's cortisol secretion patterns, we employ a state-space model. Particularly, we consider circadian upper and lower bound envelopes on cortisol levels, and timings of hypothalamic pulsatile activity underlying cortisol secretions as continuous and binary observations, respectively. To estimate the hidden cognitive energy-related state, we use Bayesian filtering. In our proposed architecture, we infer one's cognitive energy-related state using wearable devices rather than monitoring the brain activity directly and close the loop utilizing fuzzy control. To model actuation in the real-time closed-loop architecture, we simulate two types of medications that result in increasing and decreasing the energy levels in the body. Finally, we close the loop using a knowledge-based control approach. The results on ten simulated profiles verify how the proposed architecture is able to track the energy state and regulate it using hypothetical medications. 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. This simulation study is a first step toward the ultimate goal of managing hypercortisolism in real-world situations.

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Introduction

Wickramasuriya,

Faghih

2023

Bayesian Filter Design for Computational Medicine

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The human body is an intricate network of multiple functioning sub-systems. Many unobserved processes quietly keep running within the body even while we remain largely unconscious of them. For decades, scientists have sought to understand how different physiological systems work and how they can be mathematically modeled. Mathematical models of biological systems provide key scientific insights and also help guide the development of technologies for treating disorders when proper functioning no longer occurs. One of the challenges encountered with physiological systems is that, in a number of instances, the quantities we are interested in are difficult to observe directly or remain completely inaccessible. This could be either because they are located deep within the body or simply because they are more abstract (e.g., emotion). Consider the heart, for instance. The left ventricle pumps out blood through the aorta to the rest of the body. Blood pressure inside the aorta (known as central aortic pressure) has been considered a useful predictor of the future risk of developing cardiovascular disease, perhaps even more useful than the conventional blood pressure measurements taken from the upper arm (McEniery et al. (Eur Heart J 35(26):1719–1725, 2014)). However, measuring blood pressure inside the aorta is difficult. Consequently, researchers have had to rely on developing mathematical models with which to estimate central aortic pressure using other peripheral measurements (e.g., Ghasemi et al. (J Dyn Syst Measur Control 139(6):061003, 2017)). The same could be said regarding the recovery of CRH (corticotropin-releasing hormone) secretion timings within the hypothalamus—a largely inaccessible structure deep within the brain—using cortisol measurements in the blood based on mathematical relationships (Faghih (System identification of cortisol secretion: Characterizing pulsatile dynamics, Ph.D. dissertation, Massachusetts Institute of Technology, 2014)). Emotions could also be placed in this same category. They are difficult to measure because of their inherently abstract nature. Emotions, however, do cause changes in heart rate, sweating, and blood pressure that can be measured and with which someone’s feelings can be estimated. What we have described so far, in a sense, captures the big picture underlying this book. We have physiological quantities that are difficult to observe directly, we have measurements that are easier to acquire, and we have the ability to build mathematical models to estimate those inaccessible quantities.

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A Cortisol-Based Energy Decoder for Investigation of Fatigue in Hypercortisolism

Cited by 20 publications

References 16 publications

Closed-Loop Cognitive Stress Regulation Using Fuzzy Control in Wearable-Machine Interface Architectures

Closed-Loop Cognitive Stress Regulation Using Fuzzy Control in Wearable-Machine Interface Architectures

Closed-Loop Fuzzy Energy Regulation in Patients With Hypercortisolism via Inhibitory and Excitatory Intermittent Actuation

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