Quantitative EEG Analysis: Basics

Sinha, Saurabh

doi:10.1007/978-3-319-31230-9_11

Cited by 4 publications

(5 citation statements)

References 17 publications

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“…Prior to, during, and after ganaxolone administration, subjects were monitored for neurophysiologic PD changes using bispectral index (BIS) and quantitative EEG (qEEG) parameters, 20,21 including relative alpha power, alpha/delta ratio, and spectral edge frequency (95%), and the Modified Observer's Assessment of Alertness/Sedation (MOAA/S) scale. qEEG and BIS are important PD variables for capturing the timing and severity of EEG slowing in relation to the doses administered.…”

Section: Pharmacodynamic Evaluationmentioning

confidence: 99%

Intravenous Ganaxolone: Pharmacokinetics, Pharmacodynamics, Safety, and Tolerability in Healthy Adults

Gasior,

Husain,

Barra

et al. 2024

Clinical Pharm in Drug Dev

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Ganaxolone, a neuroactive steroid anticonvulsant that modulates both synaptic and extrasynaptic γ‐aminobutyric acid type A (GABAA) receptors, is in development for treatment of status epilepticus (SE) and rare epileptic disorders, and has been approved in the United States for treatment of seizures associated with cyclin‐dependent kinase‐like 5 deficiency disorder in patients ≥2 years old. This phase 1 study in 36 healthy volunteers evaluated the pharmacokinetics, pharmacodynamics, and safety of intravenous ganaxolone administered as a (i) single bolus, (ii) infusion, and (iii) bolus followed by continuous infusion. After a single bolus over 2 minutes (20 mg) or 5 minutes (10 or 30 mg), ganaxolone was detected in plasma with a median Tmax of 5 minutes, whereas a 60‐minute infusion (10 or 30 mg) or a bolus (6 mg over 5 minutes) followed by infusion (20 mg/h) for 4 hours achieved a median Tmax of approximately 1 and 3 hours, respectively. Cmax was dose and administration‐time dependent, ranging from 73.8 ng/mL (10 mg over 5 minutes) to 1240 ng/mL (30 mg over 5 minutes). Bolus doses above 10 mg of ganaxolone markedly influenced the bispectral index score with a rapid decline; smaller changes occurred on the Modified Observer's Assessment of Alertness/Sedation scale and in quantitative electroencephalogram. Most adverse events were of mild severity, with 2 events of moderate severity; none were reported as serious. No effects on systemic hemodynamics or respiratory functions were reported. Overall, ganaxolone was generally well tolerated at the doses studied and demonstrated pharmacokinetic and pharmacodynamic properties suitable to treat SE.

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Section: Pharmacodynamic Evaluationmentioning

confidence: 99%

Intravenous Ganaxolone: Pharmacokinetics, Pharmacodynamics, Safety, and Tolerability in Healthy Adults

Gasior,

Husain,

Barra

et al. 2024

Clinical Pharm in Drug Dev

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“…Digitization of EEG (or quantitative EEG referred to as qEEG) allows for extensive mathematical signal analysis [85]. Absolute and relative amplitude (µV/time point) as well as absolute and relative power of frequencies (µV2/time point) composing the signal (frequency spectrum obtained by Fast Fourier transform), is the most frequent approach to analyze qEEG.…”

Section: Cns Evaluationmentioning

confidence: 99%

Review of wearable technologies and machine learning methodologies for systematic detection of mild traumatic brain injuries

et al. 2021

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Mild traumatic brain injuries (mTBIs) are the most common type of brain injury. Timely diagnosis of mTBI is crucial in making ‘go/no-go’ decision in order to prevent repeated injury, avoid strenuous activities which may prolong recovery, and assure capabilities of high-level performance of the subject. If undiagnosed, mTBI may lead to various short- and long-term abnormalities, which include, but are not limited to impaired cognitive function, fatigue, depression, irritability, and headaches. Existing screening and diagnostic tools to detect acute and early-stage mTBIs have insufficient sensitivity and specificity. This results in uncertainty in clinical decision-making regarding diagnosis and returning to activity or requiring further medical treatment. Therefore, it is important to identify relevant physiological biomarkers that can be integrated into a mutually complementary set and provide a combination of data modalities for improved on-site diagnostic sensitivity of mTBI. In recent years, the processing power, signal fidelity, and the number of recording channels and modalities of wearable healthcare devices have improved tremendously and generated an enormous amount of data. During the same period, there have been incredible advances in machine learning tools and data processing methodologies. These achievements are enabling clinicians and engineers to develop and implement multiparametric high-precision diagnostic tools for mTBI. In this review, we first assess clinical challenges in the diagnosis of acute mTBI, and then consider recording modalities and hardware implementation of various sensing technologies used to assess physiological biomarkers that may be related to mTBI. Finally, we discuss the state of the art in machine learning-based detection of mTBI and consider how a more diverse list of quantitative physiological biomarker features may improve current data-driven approaches in providing mTBI patients timely diagnosis and treatment.

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“…This system captures the high-speed sequences of cognitive processes that happen in a fraction of a second in a specific order. Thus, automation of such a process can aid in tracking the patient's response towards a particular normal of applied stimulation [ 20 ]. Such a sophisticated QEEG system has been automated and successfully implemented for delayed cerebral ischemia (DCI) analyzing the alpha delta ratio and relative alpha variability [ 21 ].…”

Section: Major Types Of Health Conditions Require Rehabilitationsmentioning

confidence: 99%

Novel Human-Centered Robotics: Towards an Automated Process for Neurorehabilitation

Parre

Sujatha

2021

Neurology Research International

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The global requirement of patient rehabilitation has surged with time due to the growing number of accidents, injuries, age-related issues, and other aspects. Parallelly, the cost of treatment and patient care also increased in a manifold. Moreover, constant monitoring and support for the patients having physical disabilities have become an ongoing challenge to the medical system. Robotics-based neurorehabilitation has reduced the human error while assisting such patients, precisely interpreting the signals, and communicating to the patient. Gradual precise application and improvement of the technology with time yielded a novel direction for patient care and support. The interdisciplinary contribution of many advanced technical branches allowed us to develop robotics-based assistance with high precision for the upper limb and the lower limb impairments. The present review summarizes the generation and background of robotic implementation for patient support, progress, present status, and future requirements.

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Quantitative EEG Analysis: Basics

Cited by 4 publications

References 17 publications

Intravenous Ganaxolone: Pharmacokinetics, Pharmacodynamics, Safety, and Tolerability in Healthy Adults

Intravenous Ganaxolone: Pharmacokinetics, Pharmacodynamics, Safety, and Tolerability in Healthy Adults

Review of wearable technologies and machine learning methodologies for systematic detection of mild traumatic brain injuries

Novel Human-Centered Robotics: Towards an Automated Process for Neurorehabilitation

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