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The world of biometric security has been dominated by technologies such as fingerprint and voice recognition. Recent advancements made in neurotechnology, has shown promise in providing an upgrade to the current state of biometric security.
June 26, 2022
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Recent advancements in eye tracking technology have expanded the field to include applications in many different areas, both as a tool for research and as a source of real-time data for interaction. Eye tracking has expanded well beyond the original research in vision and attention.
As a result, the field now includes very disparate use cases. Systems are designed to fit certain applications and are often much less suited for others.
Electroencephalography (EEG)-based neurotechnology not only offers us new alternatives to interact with our environment directly via our brain, but also promises to improve our human functions. In this post, we will discuss how to exploit these technologies as a rehabilitative tool for people with nervous system damage, and how to facilitate human enhancement for the general population.
We are all somewhat biased due to our past experiences and the upbringing and education we have been given. It remains more or less unconscious in our minds, defining our beliefs, influencing our attitudes, and shaping our behavior. It is the reason why we associate the color black with elegance and red with passion. However, it is also the reason why technology is still more associated with boys than girls, or why, in part, we still suffer from racism.
Geolocalization is key to multiple applications and services. Indoor Positioning Systems (IPS) are key to extend these services indoors where GPS systems are not reliable. IPS are integrated and can be deployed in homes and buildings, and can interact with smart devices to provide them with spatial context. In this post we will explain how IPS work, what types of IPS technology exist, its features and its main applications to track people, from hospitals to market research.
Neurofeedback is a human enhancement technique aimed at providing cognitive improvements in psychological variables such as memory, attention, processing speed or executive functions. We describe herein neurofeedback and biofeedback techniques, the science behind one of the most validated protocols, the new trends in modern approaches, influenced by the advances in brain-computer interfaces, and some use cases and scientific results.
When choosing an electroencephalogram (EEG) device it is important to find the best possible performance by balancing device features and value. Once all the signal related features (those which apply to both sensor and amplifier stages) have been addressed, we will discuss other important characteristics such as connectivity, power, autonomy, data format, etc.
Eye tracking has become an invaluable tool for understanding attention, visual behavior and human behavior in a number of diverse fields, from psychology, neurophysiology, user experience, market research/neuromarketing, etc. The technology can also be used for medical analysis and screening, and it provides a new method of interaction.
Historically, eye tracking systems were invasive and immobile, and therefore useful only in very limited experiments. While there are still some limitations
The market for neurotechnology devices is growing, with many new tools available. Finding the right EEG headset can be a challenge. There are many features that will influence this decision, but a very important one is whether the EEG has a fixed or variable sensor layout. Variable layouts will give you flexibility at the cost of usability, and fixed layouts the opposite. We explain here the pros and cons of each version.
EEG systems capture information about many different aspects of our cognition, behavior, and emotions. The technology not only helps to study the brain, but also has applications in health, in affective and emotional EEG monitoring, and in human improvement. However, EEG data is not easy to interpret: it has a lot of noise, varies significantly between individuals and, even for the same person, changes substantially over time.
One of the main concerns when dealing with electroencephalographic signals (EEG) is assuring that we record clean data with a high signal to noise ratio. The EEG signal amplitude is in the microvolts range and it is easily contaminated with noise, known as “artifacts”, which need to be filtered from the neural processes to keep the valuable information we need for our applications. We review in this post different EEG artifacts and the main tools and techniques to remove them.
Implicit measures became very popular years ago by the academics, and many researchers employed them to analyze biases in racial groups, gender, sexuality, age, and religion, as well as to assess self-esteem in clinical psychology. Today, other applications in market research have emerged to gather information on implicit preferences of products, brands, politicians, and celebrities, and to reveal which attributes are more inherently associated with these concepts.
When choosing an electroencephalogram (EEG) device within the constraints of a project requirements, it is important to find the maximum performance possible by balancing features and value. This article will build on top of the previous one (EEG sensor layer) by addressing important EEG amplifier features like sampling rate, bandwidth, noise level, CMRR, etc.
Quantitative electroencephalogram (QEEG) is the mathematical analysis of the brain’s electrical activity, mainly power spectral analyses, to obtain metrics that may be associated with behavioral-cognitive function.
When choosing an electroencephalogram (EEG) device within the constraints of a project requirements, it is important to find the maximum performance possible by balancing features and value. This article focuses on the EEG sensor layer features, including the type of sensor (dry/wet), shielding, and electrode placement, in order to give guidelines to help in the selection process.
Dry-EEG systems can open the door for the application of neuroscience in real-world settings, and the market to a new generation of products and services based on neurotechnology. However, there are many open questions related to their reliability, accuracy and signal quality. This post will give the reader solid arguments for selecting a technology that fits the application requirements.
