BrainTrip Cognitive Index (BCI)

A scalable, neurological tool to measure mental function

The BCI is an objective measure of cognitive abilities based on fully automatic neuroscientific brain-wave analysis. It assists in detecting mental decline and can be used as a rapid screening test for early dementia detection.



Cognitive Index (BCI)

In the current system of referrals and clinical trials used to diagnose dementia, elderly individuals lose 1-2 years of prospective treatment, as that is how long it takes for symptoms to develop in most people. As a contrast, our solution is based on a 15-minute EEG test with an accuracy of 85%. The diagnostic algorithm that BrainTrip has developed is

than any other method currently used in dementia diagnosis.


N O N -I N V A S I V E

In addition to clinical observation, general practitioners and neurologists might advise the use of other methods for dementia diagnosis, such as structural imaging (CT and MRI), cerebrospinal fluid analysis, genetic testing, and functional neuroimaging (PET, FDG-PET, and SPECT), all of which are invasive and not patient-friendly. As a contrast, BrainTrip's EEG-based approach to early dementia diagnosis is completely

and safe. By opting for a saline-based over gel-based solution, we make sure that our hardware is as comfortable as possible.  

CT scanners can cost the medical facility up to $2.5 million, while Tesla 3 MRI machines are typically purchased for $3 million. The cost of this type of technology makes public hospitals more inclined to recommend cheaper forms of diagnosis, while private clinics charge tens of thousands of dollars for such high-end biological testing. This undoubtedly makes BrainTrip's EEG-based  testing  for  dementia  the most

way of diagnosing dementia at the moment.





BrainTrip is the brainchild of lifelong brain enthusiasts with backgrounds in cognitive science, neuroscience, and medicine. We teamed up with electrical engineers, designers, and medical experts to create an affordable, easy to use, and mobile EEG-based (electroencephalogram) method of dementia diagnosis. Coupled with our years-long experience in clinical work, our research expertise in dementia-related diseases allowed us to get close insights into the shortcomings of currently available technology for dementia diagnosis. For that reason, we developed the first scalable biological screening test for dementia.


While most people associate dementia with forgetfulness, the disease covers a much wider diapason of neurodegenerative symptoms, such as fear for safety, paranoia, and extreme emotional wavering. It is a devastating disease that robs people of their personality and memories, affects relationships with their loved ones, and represents a big socioeconomic burden for the society as a whole. Our vision is to change that by offering early diagnosis to individuals at a risk age. This can hopefully buy people up to 2 or more years of healthy life, as they can start taking medication earlier in order to palliate the symptoms, engage in cognitive training, and plan ahead for the future (finances, inheritance, home management, etc).  




Most people seem to be familiar with the primary issue faced by individuals with dementia, which happens to be memory loss. That said, the disease also represents an overall decline in cognitive abilities and as such eventually affects the person's capacity to distinguish long-term from short-term memories, reasonably react to simple everyday challenges, as well as maintain stable emotional relationships with their inner circle or form new ones. In comparison to their average healthy peers, individuals with some form of dementia are typically considered to be at a higher risk of (A) injury within and outside of the home, (B) facing a quicker exacerbation of other age-related health issues due to their tendency to forget to take medication, and (C) making rash financial decisions as a result of fear and paranoia that can arise from dementia. This is precisely why an early diagnosis of dementia can improve the lives of those affected by it, as they can get informed on how to best tackle the challenges imposed by the disease.




The electroencephalogram (EEG) is a record of the oscillations of brain electric potential recorded from electrodes on the human scalp. The scalp EEG is an important clinical tool for following and treating certain illnesses. Brain tumors, strokes, epilepsies, infectious diseases, mental disorders, severe head injury, drug overdose, sleep and metabolic disorders, and ultimately brain death are some of the medical conditions that may show up in the spontaneous EEG [1, 2]. Evoked and event-related potentials measured on the scalp may be used in the diagnosis and treatment of central nervous system diseases as well as illuminating cognitive processes, but often EEG abnormalities seen with naked eye observation of spontaneous EEG are slight and non-specific [3].


Alzheimer's disease and other dementias typically cause substantial slowing of normal EEG rhythms. Traditional naked eye inspected EEG has been of little use in dementia because EEG changes are often only evident late in the illness when other clinical signs are obvious. New efforts to apply EEG to early detection of Alzheimer's disease are under study [3].


EEG has been used as a productive neuroscientific “window on the mind” for the last 100 years. With the application of new signal processing techniques and quantitative assessment EEG oscillatory dynamics, we strive to elevate the tool much beyond its past “naked eye inspection” roots. At BrainTrip we’ve developed a robust way to automatically extract EEG features that correspond to neurodegenerative processes in the brain. Our EEG Cognitive Index (ECI) algorithm was developed from the ground up based on fundamental neurophysiological insights into how neurodegeneration changes EEG signals. The ECI provides objective assessment of general cognitive (mental) function. It can also be used as a rapid screening test for early dementia detection as this disease naturally affects patient’s cognitive abilities.

We’ve tested the ECI algorithm in two separate scientific studies [4, 5].

In the first study (N=57) we tested the ability of our algorithm to differentiate between clinically confirmed probable early stage Alzheimer’s disease and healthy matched controls. The ECI performed with an accuracy of 85% (specificity=82%, sensitivity=73%).

In the second study (N=443) we tested the ECI’s ability to tract seniors’ mental abilities. Our EEG metric achieved a highly statistically significant correlation with a standard test of mental abilities – the MoCA (Montreal Cognitive Abilities test).

[1] Kellaway P, 1 979, An orderly approach to visual analysis: the parameters of the normal EEG in adults and children. In: DW Klass and DD Daly (Eds.), Current Practice of Clinical Electroencephalography, New York: Raven Press, pp. 69-1 47.

[2] Niedermeyer E and Lopes da Silva FH (Eds.), 1999, Electroencephalography. Basic Principles, Clinical Applications, and Related Fields, 4th Edition, London: Williams and Wilkins.

[3] Paul Nunez, Electric fields of the Brain

[4] Jurij Dreo, Bruna Pikš, Andreja Emeršič, David Sakić et al., The EEG Dementia Index (EDI): a promising low-cost biomarker of early stage Alzheimer's type dementia [Unpublished]

[5] Jurij Dreo et al., Associations between simple EEG spectral measures and cognitive function in older adults, Nanosymposium, Society for Neuroscience, Washington DC, 2017

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BrainTrip Limited
Edge Water Business Complex
Elia Zammit Street
St Julian's, STJ 3150, Malta
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