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

2021 ◽  
Vol 15 ◽  
Author(s):  
Hamid Fekri Azgomi ◽  
Jin-Oh Hahn ◽  
Rose T. Faghih

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.

2019 ◽  
Author(s):  
A. Abbasi ◽  
L. Estebanez ◽  
D. Goueytes ◽  
H. Lassagne ◽  
D. E. Shulz ◽  
...  

SummaryNew and improved neuroprosthetics offer great hope for motor-impaired human patients to regain autonomy. One obstacle facing current technologies is that fine motor control requires near-instantaneous somatosensory feedback. The way forward is to artificially recreate the rich, distributed feedback generated by natural movements. Here, we hypothesize that incoming sensory feedback needs to follow biomimetic rules in order to be efficiently integrated by motor circuits. We have developed a rodent closed-loop brain-machine interface where head-fixed mice were trained to control a virtual cursor by modulating the activity of motor cortex neurons. Artificial feedback consisting of precise optogenetic stimulation patterns in the primary somatosensory cortex coupled to the motor cortical activity was provided online to the animal. We found that learning occurred only when the feedback had a topographically biomimetic structure. Shuffling the spatiotemporal organization of the feedback prevented learning the task. These results suggest that the patterns of inputs that are structured by the body map present in the primary somatosensory cortex of all mammals are essential for sensorimotor processing and constitute a backbone that needs to be considered when optimizing artificial sensory feedback for fine neuroprosthetic control.


Author(s):  
Qiaosheng Zhang ◽  
Sile Hu ◽  
Robert Talay ◽  
Zhengdong Xiao ◽  
David Rosenberg ◽  
...  

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-15
Author(s):  
Moshu Qian ◽  
Guanghua Zhong ◽  
Xinggang Yan ◽  
Heyuan Wang ◽  
Yang Cui

In this study, a closed-loop brain stimulation control system scheme for epilepsy seizure abatement is designed by brain-machine interface (BMI) technique. In the controller design process, the practical parametric uncertainties involving cerebral blood flow, glucose metabolism, blood oxygen level dependence, and electromagnetic disturbances in signal control are considered. An appropriate transformation is introduced to express the system in regular form for design and analysis. Then, sufficient conditions are developed such that the sliding motion is asymptotically stable. Combining Caputo fractional order definition and neural network (NN), a finite time fractional order sliding mode (FFOSM) controller is designed to guarantee reachability of the sliding mode. The stability and reachability analysis of the closed-loop tracking control system gives the guideline of parameter selection, and simulation results based on comprehensive comparisons are carried out to demonstrate the effectiveness of proposed approach.


2019 ◽  
Vol 116 (52) ◽  
pp. 26274-26279 ◽  
Author(s):  
Richard A. Andersen ◽  
Tyson Aflalo ◽  
Spencer Kellis

A dramatic example of translational monkey research is the development of neural prosthetics for assisting paralyzed patients. A neuroprosthesis consists of implanted electrodes that can record the intended movement of a paralyzed part of the body, a computer algorithm that decodes the intended movement, and an assistive device such as a robot limb or computer that is controlled by these intended movement signals. This type of neuroprosthetic system is also referred to as a brain–machine interface (BMI) since it interfaces the brain with an external machine. In this review, we will concentrate on BMIs in which microelectrode recording arrays are implanted in the posterior parietal cortex (PPC), a high-level cortical area in both humans and monkeys that represents intentions to move. This review will first discuss the basic science research performed in healthy monkeys that established PPC as a good source of intention signals. Next, it will describe the first PPC implants in human patients with tetraplegia from spinal cord injury. From these patients the goals of movements could be quickly decoded, and the rich number of action variables found in PPC indicates that it is an appropriate BMI site for a very wide range of neuroprosthetic applications. We will discuss research on learning to use BMIs in monkeys and humans and the advances that are still needed, requiring both monkey and human research to enable BMIs to be readily available in the clinic.


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