check out the video:  emwave

30 day risk free offer…maybe we need to buy it and take apart the sensors….we could do better!

and the EEG measurement device [Link] – it seems impressive. not sure how accurate it is.

subconscious is probably a poor term to use…non-conscious is better. We could also think about how to use our technology for marketing purposes.

another thought to stir in the pot.

d

This link is a

Quantitative EEG and Neurotherapy Fact Sheet

The idea is to reduce slow (theta/delta – .5 – 8 Hz) wave EEG during active states and increase beta (20-30 Hz) in frontal electrodes

The brainMaster Atlantis has 4 channels to record EEG. It is $2700.

4 channels of EEG and 4 channels of AUX signals for additional biofeedback modalities. Features built in EEG driven photic stim and USB interface.

• EEG inputs sampled with 24 bits.
• Maximum EEG sampling rate (1 channel) 8192 samples/second. Presently emulating 2.5W.
• Continual impedance checking
• EEG/ Biofeedback Systems with USB Interface (no batteries, no power cord).
• Total Immersion feature (photic, vibrotactile, auditory) internal autonomous functions presently functioning with 2.5W.

An anecdote using this equipment to reduce slow-wave theta follows:

The other 3 children used one active sensor Neurofeedback of the Brainmaster 4X4 instrument.  The set up was a reference electrode on one ear (usually the left ear) and a ground electrode on the opposite ear ( obviously the right ear in this case).  The active electrode was placed at FZ in the 10-20 system of placement of electrodes.  They were to increase the amplitude of the activity at this electrode (i.e. beta of 15-18 hertz) and their feedback was to watch a pink bar go above the threshold line as much as possible.  At the same time they were to inhibit the amplitude of 4-8 hertz (theta) and of high beta ( 20-30 hertz).  They could also see the blue bar (theta) and yellow bar (high beta) stay below the threshold line.   The thresholds were set by myself after a few seconds of data collection which determined their threshold levels.  All were able to train and reported feeling calmer and more energy at the end of 5-7 minutes of training.   All of these experiments were done in front of their classmates with questions and answers being conducted as they trained.  Not the usually training conditions and yet they achieved the goal.

There is a conference that may be helpful in designing some interface that is also simple, but easy to use with iphone

See this http://aapb.org/

and check out:
ISNR.org; – Helping the Brain help us…I like this motto

You can also train to procude more coherence across sites…See HERE

maybe a visual display

• Analog Gain: 200,000
• Noise At Front End: Less than 0.3 micro-volts
• Analog Bandwidth: 0.2 Hz to 3,000 Hz
• Analog to Digital Conversion: 6 Channels, 12 Bit Accuracy
• Battery Powered: 2 AA Batteries (included)
• Isolation: 2,500 Volts
• PC connection:  RS232 serial port connection, or serial to USB for WinXP
• DIMENSIONS: 190mm x 100mm x 40mm
• WEIGHT: 13.5 oz.

then there is the Proteus sound and mind machine!

Our representatives are here to assist you with pure brainwave customer service

Interestingly, they provide a set of open programming APIs that allow independent developers to more easily create software that interacts with the data coming out of the device.  So, although they haven’t created any interesting applications of the device, it’s possible that someone else will.

They seem to be positioning themselves to tap into the burgeoning physical computing scene, by simplifying use of the device in projects involving the Arduino and similar microcontroller devices.

Someone from my grad school has already started working on it.

See also Emotive Epoc for similar device.

1. Improve sleep/wake/circadian rhythms

2. Improve recall of dreams

3. Understand the mechanisms of memory recall

4. Address the subtle levels of energy that manifest in the dream state

5. increase ability for lucid dreaming

There are multiple brain-machine interfaces that could be created based on products such as:

a digital sun

a lucid dream induction device

integrating multiple sensory modalities for alarm

http://www.heartmath.com/

People use this to maintain control over stress response.

At least since the industrial revolution with its suggestive images of efficient robots performing mundane factory tasks without the melodrama of our dirty humanity, the popular conception of artificial intelligence and robotics has been one of cold, dispassionate creatures, made of either metal, or of thousands of lines of tightly structured computer code.  But the future of artificial intelligence is starting to look quite a bit wetter.

Computer artificial intelligence research and the design of “intelligent agents” have traditionally been heavily influenced by developments in neuroscientists’ understanding of brain processes, whether in terms of actual wiring of neural circuits, or on the more abstract symbolic level of cognitive processes.  Yet, despite what the computer scientists claim, we have still yet to see an artificially intelligent agent that does even the most mundane of tasks well, besides tasks of the most repetitive, inhuman sort.

But rather than crudely simulate the design of the human brain in intelligent agents, why not use the real thing?  Research done by Dr. Thomas DeMarse at the University of Florida recently grew brain tissue in a dish that learned to control a flight simulator program.

The intent of the research was to better understand the ways in which neurons communicate with one another.  In order to probe neuronal signaling pathways, the researchers grew the brain tissue on top of grid of electrodes that not only provided a sensory array with which to observe the electrical signals present within the brain tissue, but also allowed them to inject their own electrical signals into the brain tissue as a way of probing neuronal activity and providing feedback.

Dr. DeMarse did almost exactly what artificial intelligence programmers do, but using actual brain tissue instead of computer algorithms.  We are at a stage of understanding in both brain science and technology where such hybrid researches are becoming possible.

Will it one day be more efficient to use living tissue to perform complex computations?  Why use flawed, primitive computer models of the human mind when you can use the real thing?  If the cost of growing such natural sources of artificial intelligence were brought down, this could be a phenomenal area for growth (pun intended).