Backed by research.
Designed for physicians.

The world's LARGEST standardized neuroscientific database.

BrainView System


BrainView technology is a scientific breakthrough in brain health management and diagnostic.
BrainView allows medical professionals, to see more and know more than ever before.

BrainView helps clinicians with objective data on a patient's core brain functions like: memory, attention, information processing, and executive function.
BrainView can identify symptoms of cognitive disfunction such as fatigue, memory loss or brain fog, in some cases several years before they erupt.

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BrainView Research


The BrainView system enables a physician to collect the patient's neuro-physiological biomarkers, which profile the patient's neurological function. The system allows the physician to gain additional clinical information vital to making a well-informed patient-care decision.

BrainView is backed by more than 30 years of globally celebrated, peer-reviewed scientific research.
At BrainView, we stay at the forefront of brain health research, collaborating with experts in neurology, cognitive science, and computer science to develop boundary-pushing methods for brain signal analysis.
Since the earliest evoked responses were reported in 1939, there are now over 160,000 published studies on the PubMed.gov database.

Our latest R&D efforts have been on developing an Artificial Intelligence (AI) biomarker for ADHD, TBI, PTSD and Alzheimer's disease diagnosis. We're currently conducting several IRB approved studies, using Evoke to measure EEG & ERP biomarkers. BrainView Machine-Learning models are based on more than 200,000 EEG reports database.

BrainView uses artificial intelligence algorithms to cluster test performance in accuracy, speed and image properties. Evaluations are based on comparison with an accurate dataset.
  • Driving innovation and inspiration
  • Improved outcomes and collaboration
  • Backed by research. Designed for physicians and other healthcare providers
  • De-identified and ready for use in big data research applications.
  • 200,000+ unique patient datasets
  • 5+ billion data points

A Revolutionary New Tool for Mapping Brain Health


BrainView envisions a world in where brain healthcare is intelligent, data-driven and available to everyone.

BrainView technology is revolutionize the healthcare system by more offering tools to more efficiently achieving an accurate diagnosis of neurological disorders. BrainView integrates big-data repositories and deep-learning algorithms. To measure how effectively different parts of the brain are connecting and communicating. This leads to improving the quality of life for patients suffering from various symptoms and disorders.

BrainView machine-learning (ML) and Artificial intelligence (AI)

BrainView offers a revolutionary new way of understanding how the brain's neural networks are activated and informed about brain function. BrainView does so by leverage machine-learning, advanced algorithms, and large-population database.

BrainView creates a high-resolution, three-dimensional representation of functional neural pathways from post-hoc neural patterns of time, location, amplitude, and frequency data points in the brain related to specific functions evoked by repeatable tasks.

BrainView is able to offer healthcare providers a unique perspective on brain function, one that is not available via traditional diagnostic methods. This is possible by comparing a patient's test results to their previous healthy baseline - or to a Reference Brain Network Model generated from an extensive population database. This is beneficial for both initial evaluation, as well as follow-up evaluation for disease progression.
BrainView Provides:
  • snapshot mapping of brain network function in comparison to a healthy/normative group;
  • the ability to compare multiple tests over time;
  • objective information to assist with better-informed medical decisions.

Our evidence-based insights expand our knowledge of the body's most important organ, offering medical professionals the opportunity to improve informed decision making about patient care, and speeding the development of more effective drugs and treatment protocols in the future.

Earlier detection and improved assessment of cognition is critical to achieve or improve more effective clinical trial recruitment, drug efficacy measurement, differential diagnosis, and clinical care. Our neuro-analytic platform unlocks the full potential of EEG by harnessing advanced deep-learning techniques to decode highly complex brain activity signals into objective measurements of cognition with superior diagnostic accuracy.

Big data for big science


At BrainView, we are dedicated to addressing the world's most critical brain health issues. That means partnering with industry and academic researchers alike to accelerate the translational research that will help patients achieve better health outcomes.

Become one of our data partners and help tackle your big science questions. Whether you are working on training machine-learning algorithms for improved diagnostics, or advancing the frontier of functional brain mapping, let us provide the rich and robust data you need.

The BrainView Health System takes qEEG technology that has been used for decades in a laboratory setting and brings it into the physician's office. With easy data collection right in your practice, BrainView delivers well-established, reliable, and stable brain health biomarkers that can aid in diagnosis of cognitive disorders. We didn't create the science, we perfected it for clinical use.

Quantitative analysis of the artifact-free EEG (qEEG)


Quantitative analysis of the artifact-free EEG (qEEG) data allows characterization of the signal into features used to describe brain activity, including measures of power, symmetry, coherence, phase, phase synchrony, complexity and others. Advances in signal processing have enriched these measures beyond those conventionally described, and approximately 10,000 features are derived from each EEG recording. The scientific literature demonstrates that the EEG of "normally functioning" individuals systematically changes over the life span and can be described by equations as a function of age. Deviations from the age expected normal values can be used to statistically describe abnormal signals in an individual, expressed as z-scores, removing the effect of age. Also, important to highlight is that EEG has very high time resolution (milliseconds) and can capture physiological changes much better than other brain imaging tools (e.g., MRI or PET), making it uniquely suited to reflect the types of changes in brain activity that occur in mild traumatic brain injury (mTBI).

Alzheimer's disease diagnosis


In collaboration with several prestigious institutions, BrainView is developing diagnostic tools for more accurate and objective diagnosis, as well as tracking of neurodegenerative disease, starting with Alzheimer's Disease (AD).

Our latest R&D efforts have been on developing an Artificial Intelligence (AI) biomarker for Alzheimer's disease diagnosis. Using BrainView to measure EEG & ERP biomarkers for patients with cognitive impairment. Together, along with our database of 200,000+ unique patient EEG reports, are used to train our Machine-Learning models.

The ultimate goal? Develop an AI algorithm capable of diagnosing AD based on EEG/ERP data alone, with sensitivity and specificity levels near 95%. Impressive? We think so.

Traumatic brain injury (TBI) diagnosis


Advanced signal processing captures changes in brain activity distinctive of TBI including measures that reflect disruption in neuronal transmission (connectivity), disorganization of neural networks & changes in neurotransmitters.

BrainView's database contains more than 12,000 evaluations from mTBI patients and normal subjects. 10,000 features that characterize the EEG signal are then extracted from each record and age-regressed relative to age expected normal values. These features are then used to power proprietary, A.I. derived clinically accurate algorithms to create objective biomarkers of brain injury.
With EEG features as core inputs to machine learning classifier building methods, distinctive profiles of TBI are identified.

After an informed data reduction, selected EEG features are used as candidate inputs to A.I./machine learning based techniques (such as, genetic algorithms and Logistic Regression) for the derivation of the classifier algorithms. These sophisticated A.I. methodologies describe distinctive profiles or patterns of brain electrical activity used to determine the likelihood of structural brain injury (with sensitivity of 95% to the smallest amount of reliably detectable, and using the same EEG data, two separate algorithms for identifying the likelihood of concussion).

The algorithms provide a multivariate interpretation of the EEG data, which can be thought of as multivariate descriptors (unique profiles), and can be used to objectively identify the likelihood of a structural brain injury or (with separate algorithms) the likelihood of brain function impairment (concussion). These algorithms have been demonstrated in independent clinical validation studies to have high accuracy. This capability does not require a neurologist or electroencephalographer to read the brain waves and allows comparison to large populations of patients with closed head injury.

BrainView for Drug Development Challenge


Drug development is a challenging and lengthy process. CNS drugs exhibit the lowest approval success rates due to multiple challenges, including lack of efficacy in early and advanced stages of development, Poor target selection / engagement, poor translation from pre-clinical models and disease heterogeneity. By adding new objective endpoints, assisting in understanding drug mechanism, identifying placebo effects and mapping cognitive functions, BrainView may contribute in improving the process of CNS research and drug development. In addition, BrainView can serve as a screening tool, identifying subtypes and predicting treatment protocol success and failure.

For various reasons, research has not delivered truly innovative drugs for the treatment of CNS disorders in the past decades. This is due to an insufficient understanding of the pathophysiology of the disorders, and limited predictive validity of preclinical behavioral and pharmacological models. In addition, a lack of reliable biomarkers to quantify treatment effects and excessive reliance on subjective measures of diagnosis and disease progression. There is an urgent need for an innovative diagnostic response and predictive biomarkers, in order improve drug development for CNS related disorders.

Pharma solutions
BrainView offers an innovative comprehensive solution of leading-edge EEG/ERP based assessment technologies for pharmaceutical and academic clinical trials which includes the following products:
  • Consistent EEG/ERP acquisition platform
  • BrainView analysis
  • Brain analytics - based on our 200,000+ datasets data lake (healthy and patients).
  • Services are HIPAA and 21 CFR Part 11 compliant including data management via a cloud-based portal system
BrainView's support includes the following features when applicable: Installation, training, certification, clinical protocol and IRB support, FDA cleared EEG multi-channel device, secure and compliant data management tools, real time analysis and ongoing data quality monitoring.

Biomarkers to aid for earlier detection of memory loss and dementia.