NEUROSKY HOME USE DEVICE FOR NEUROFEEDBACK

NeuroSky technology allows for low-cost EEG-linked research and products by using inexpensive dry sensors; older EEGs require the application of a conductive gel between the sensors and the head. The systems also include built-in electrical “noise” reduction software/hardware, and utilize embedded (chip level) solutions for signal processing and output. The major advantage of the dry sensor is the time it takes to set up. Traditional gel bases EEGs can take up to 30 minutes to start acquiring data while the NeuroSky headsets are ready to go in seconds. The disadvantage to the dry sensor electrodes is an increase in the impedance contact the sensor has with the scalp. This can cause low amplitude signals to not be fully represented in the acquired data.

The headset gets employed with ThinkGear ASIC Module (TGAM) chip that preprocesses the data within the headset itself. The eSense Meters (Attention and Meditation) are calculated on the ThinkGear chip.

NeuroSky developed a ThinkGear measurement technology to calculate the Power Spectrum Density (PSD) using 512 samples per second sampling frequency and eSense Attention meter algorithm to indicate the intensity of attention, which occurs during intense concentration. The device amplifies and digitalizes the voltage difference (to achieve better common mode rejection) between a single dry sensor on the forehead and a reference on the ear. The brain signal is filtered by analog and digital, low and high pass filters in the 1-50 Hz range. Each second, the signal is analyzed in the time domain to detect and correct noise, a standard FFT is performed, and finally, the signal is rechecked for noise and artifacts in the frequency domain to get brainwave strengths and eSense Attention and Mediation values. eSense algorithm is dynamically learning, so ThinkGear sensors are able to operate on a wide range of individuals, and on a wide range of personal and environmental conditions NeuroSky’s EEG biosensor digitizes and amplifies raw analog brain signals to deliver concise inputs to games, toys, and devices running health and wellness, educational and research applications.

ThinkGear: ThinkGear is the equipment which is the contemporary interior of every NeuroSky product that allows a device to integrate with the user’s brainwaves. It consists of the sensor which touches the forehead of the user, the reference and junction points presented in the ear clip, and the onboard chip that operates all of the data. Both the dominant brainwaves and the eSense Meters (Attention and Meditation) are calculated on the ThinkGear chip.

eSense: eSense is a NeuroSky’s quick fix algorithm for distinguishing mental states. To compute eSense, the NeuroSky ThinkGear technology fleshes out the raw brainwave signal and removes the atmosphere noise and muscle movement. The eSense algorithm is then appealed to the remaining signal, resulting in the elucidated eSense meter values.

eSense Meter: Technical Description: For each different type of eSense, i.e., the Attention and Meditation meter value are described on eSense respective scale of 1 to 100. A value across 40 to 60 at any given moment in time is considered “neutral” and is similar in notion to “baselines. A value across 60 to 80 is considered “slightly elevated”, and may be interpreted as levels of eSense values may be higher than normal for a given person. Values across 80 to 100 are considered “elevated”, denoting they are strongly expressive of heightened levels of that eSense. Similarly, on the other end, a value across 20 to 40 indicates “reduced” levels of the eSense, while a value across 1 to 20 indicates “strongly lowered” levels of the eSense.

Attention eSense
The eSense Meter algorithm specifies the strength of a user’s level of mental “attention” or “focus”, which occurs during extreme concentration and directed (but stable) mental activity. The meter value ranges from 0 to 100. The attention level increases when a user focuses on a single thought or an external object, and decreases when distracted. Users can observe their ability to concentrate using the algorithm. In educational settings, attention to lesson plans can be tracked to measure their effectiveness in engaging students. In gaming, attention has been used to create “push” control over virtual objects. Lack of concentration, wandering thoughts, Distractions, or anxiety may decrease the Attention meter level.

Meditation eSense
The eSense Meditation meter specifies the user’s level of mental “relaxation” or “calmness”. The value ranges from 0 to 100, and increases when users relax the mind and decreases when they are uneasy or stressed. The Meditation Meter quantifies the ability to find an inner state of mindfulness, and can thus help users learn how to self- correct and find inner balance to overcome the stresses of everyday life. The algorithm is also used in a variety of game-design controls. The account that Meditation is a meter of a person’s mental states, not physical states so just relaxing of all body muscles may not quickly result in an enhanced Meditation level. Nevertheless, for most people in most everyday situations, relaxing the body frequently helps the mind to relax as well. Meditation is associated to decrease activity by the active mental processes in the brain. It has been an observed that closing the eyes is often an effective method for increasing the Meditation meter level. Distractions, anxiety, sensory stimuli and wandering thoughts may lower the Meditation meter levels.

Blink Detection
The Blink Detection algorithm signals a user’s blinks. A higher number indicates a “stronger” blink, while a smaller number indicates a “lighter” or “weaker” blink. The frequency of blinking is often correlated with nervousness or fatigue. Eye blinks are akin to a standard on/off binary system and therefore are valuable for controls that require definitive responses. For instance, in communication applications, one blink means no, two mean yes — giving individuals with a special needs a simple way to communicate.

Mental Effort
The Mental Effort algorithm measures the mental workload while performing a task. The harder a user’s brain works on a task, the higher the value. The algorithm works well with both physical (e.g., drawing) and mental (e.g., reciting) tasks, and can be used for continuous real-time tracking and between-trial comparisons to measure the effects of multi-tasking, workload variability, and more. The algorithm can be used to track the effects of diverse cognitive loads on the ability to learn and provide feedback for user self-improvement.

Familiarity
The Familiarity algorithm tracks learning processes to measure the relative level of understanding, learning, or comfort with a task. It is a measure of the subconscious learning of procedural (motor) and mental tasks. In some cases, it reflects how well a user is doing with the task. By observing trends, users can better understand and assess their learning process. It can be applied to tasks that are physical in nature (e.g., drawing) or mental (e.g., recitation), and enable data-tracking assessments to gauge learning status.

Appreciation
The Appreciation algorithm provides real-time measurement of the level of enjoyment or appreciation a subject feels towards an external audiovisual stimulus. The algorithm allows moment-by-moment detection of emotions. In marketing applications, it can be used to track and understand a user’s level of appreciation, providing insights and strategic direction for marketing efforts.

Emotional Spectrum
Emotional spectrum measures the intensity (low-high) and pleasantness (pleasant/unpleasant) of emotional activity. Pleasant/Unpleasant identifies whether a user is having a pleasant or unpleasant emotion. Pleasant emotions could be happy, serene, relaxed, etc. Unpleasant emotions could be anger, disgust, depressed, etc. Intensity measures how strong a user’s emotions are in real time. The emotion could be happy, angry, calm, or any other emotion. There are four eTensity levels: Very Weak – Weak – Strong – Very Strong.

Cognitive Preparedness
Cognitive Preparedness measures the brain’s capacity for optimal cognitive performance on a relatively complex task or in other words, the brain’s capacity for higher level cognitive functions.

Creativity
Creativity measures the brainwave activities underlying creative cognition. The higher the Creativity value, the stronger the brainwave activities promoting innovative and creative thinking.

Alertness
Alertness measures user’s alertness or vigilance level at the moment. High alertness value indicates you are at a state of focus while low value represents a relaxing state of mind.