Sixtus Okwuoha. A short summary of this paper. Download Download PDF. Translate PDF. Acknowledgement The satisfaction that accompanies the successful completion of any task would be incomplete without the mention of persons whose ceaseless cooperation made it made it possible, whose constant guidance and encouragement crown all efforts with success.
I am much grateful to my project supervisor Mrs. Ijeoma Emeagi. My sincere gratitude goes to my parents; Mr. Maurice Okwuoha and Mrs. Benadetth Okwuoha for their financial and moral support in my Academics and Social well-being in this institution. Although the dot's gyrations are directed by a computer, the machine was only carrying out the orders of the test subject.
Though computers can solve extraordinarily complex problems with incredible speed, the information they digest is fed to them by such slow, cumbersome tools as typewriter keyboards or punched tapes.
The key to his scheme: the electroencephalograph, a device used by medical researchers to pick up electrical currents from various parts of the brain. If we could learn to identify brain waves generated by specific thoughts or commands, we might be able to teach the same skill to a computer.
The machine might even be able to react to those commands by, say, moving a dot across a TV screen. So far the S. I, computer has been taught to recognize seven different commands—up, down, left, right, slow, fast and stop. This is true even when they are interacting with machines.
The ability to attribute mental states to others from their behavior and to use that knowledge to guide our own actions and predict those of others is known as theory of mind or mind-reading. A computer may wait indefinitely for input from a user who is no longer there, or decide to do irrelevant tasks while a user is frantically working towards an imminent deadline.
As a result, existing computer technologies often frustrate the user, have little persuasive power and cannot initiate interactions with the user. Even if they do take the initiative, like the now retired Microsoft Paperclip, they are often misguided and irrelevant, and simply frustrate the user.
Erik What is Mind-reading computer? A computational model of mind-reading Drawing inspiration from psychology, computer vision and machine learning, the team in the Computer Laboratory at the University of Cambridge has developed mind-reading machines — computers that implement a computational model of mind-reading to infer mental states of people from their facial signals. The goal is to enhance human-computer interaction through empathic responses, to improve the productivity of the user and to enable applications to initiate interactions with and on behalf of the user, without waiting for explicit input from that user.
It determine the oxygen level and the blood flows around the subjects brain, and determine that the users thought by his facial expression. In a complex marriage of medical and computer technology, Lawrence Pinneo, a neurophysiologist and electronics engineer at the Stanford Research Institute in Menlo Park, Calif. Experiments have shown that a test subject can manipulate the position of a dot on a television screen simply by thinking or willing what the movement of the dot should be.
According to Peter , A key element in Pinneo's scheme of thought translation is a device which could bridge the gap between the electrical signals generated by the human brain and the signal inputs that a computer needs for analysis.
For this function he chose an electroencephalograph, a device used by medical researchers to measure and records the electrical activity of the brain. Utilizing the signals provided by the electroencephalograph, the computer is programmed by means of sophisticated software techniques to recognize and identify brain-wave patterns generated by specific thoughts or commands.
So far the SRI computer is capable of recognizing seven different commands—up, down, left, right, slow, fast, and stop.
Brain waves, however, like speech patterns, vary in some detail from person to person, often fooling the computer.
To circumvent this problem, the computer's memory stores a library of command patterns against which the thoughts of a given test subject are compared.
At this embryonic stage in its development, Pinneo's system is already capable of identifying the thought commands of 25 different people with an accuracy of 60 percent. Pinneo is convinced that with further research these results can be vastly improved. Speculating upon future developments, Pinneo suggests that eventually technology may well be sufficiently advanced to reverse the thought process and feed information from a computer into the human brain.
A computational model of mindreading Drawing inspiration from psychology, computer vision and machine learning, the team in the Computer Laboratory at the University of Cambridge has developed mind-reading machines — computers that implement a computational model of mind-reading to infer mental states of people from their facial signals.
Prior knowledge of how particular mental states are expressed in the face is combined with analysis of facial expressions and head gestures occurring in real time. The model represents these at different granularities, starting with face and head movements and building those in time and in space to form a clearer model of what mental state is being represented.
Peter Robinson Software from Never vision identifies 24 feature points on the face and tracks them in real time. Movement, shape and colour are then analyzed to identify gestures like a smile or eyebrows being raised. Combinations of these occurring over time indicate mental states.
Prior knowledge of how particular mental states are expressed in the face is combined with analysis of facial expressions and head gestures occurring in real time. Software from Nevenvision identifies 24 feature points on the face and tracks them in real time. Movement, shape and color are then analyzed to identify gestures like a smile or eyebrows being raised.
Combinations of these occurring over time indicate mental states. For example, a combination of a head nod, with a smile and eyebrows raised might mean interest. The relationship between observable head and facial displays and the corresponding hidden mental states over time is modeled using Dynamic Bayesian Networks. Imagine a future where we are surrounded with mobile phones, cars and online services that can read our minds and react to our moods.
Scientists are working with a major car manufacturer to implement this system in cars to detect driver mental states such as drowsiness, distraction and anger. Current projects in Cambridge are considering further inputs such as body posture and gestures to improve the inference. The same models can be used to control the animation of cartoon avatars.
Scientists are also looking at the use of mind-reading to support on-line shopping and learning systems. The mind-reading computer system may also be used to monitor and suggest improvements in human-human interaction. Looking at the functional magnetic resonance imaging fMRI scan results; the scientists were able to predict what had been displayed on the computer screen better than volunteers. Approaches used in Mind reading computer technology The two approaches which are used as basic for mind reading technology are bio feedback and stimulus and response.
These instruments rapidly and accurately 'feedback' information to the user. The presentation of this information often in conjunction with changes in thinking, emotions, and behaviour supports desired physiological changes.
Over time, these changes can endure without continued use of an instrument. A subject is connected to an electroencephalograph EEG and particular groups of brain signals are monitored. The problem with biofeedback is that the training period can stretch to months, and the results can be very variable between subjects and the tasks they try to perform.
The user wears a sort of futuristic headband that sends light in that spectrum into the tissues of the head where it is absorbed by active, blood-filled tissues. The headband then measures how much light was not absorbed, letting the computer gauge the metabolic demands that the brain is making.
The results are often compared to an MRI, but can be gathered with lightweight, non-invasive equipment. Wearing the fNIRS sensor, experimental subjects were asked to count the number of squares on a rotating onscreen cube and to perform other tasks. The subjects were then asked to rate the difficulty of the tasks, and their ratings agreed with the work intensity detected by the fNIRS system up to 83 percent of the time. A person wearing futuristic headband The particular area of the brain where the blood-flow change occurs should provide indications of the brain's metabolic changes and by extension workload, which could be a proxy for emotions like frustration.
Measuring mental workload, frustration and distraction is typically limited to qualitatively observing computer users or to administering surveys after completion of a task, potentially missing valuable insight into the users' changing experiences. A computer program which can read silently spoken words by analyzing nerve signals in our mouths and throats has been developed by NASA.
Preliminary results show that using button-sized sensors, which attach under the chin and on the side of the Adam's apple, it is possible to pick up and recognize nerve signals and patterns from the tongue and vocal cords that correspond to specific words. Web search using mind-reading computer For the first test of the sensors, scientists trained the software program to recognize six words - including "go", "left" and "right" - and 10 numbers.
Participants hooked up to the sensors silently said the words to themselves and the software correctly picked up the signals 92 per cent of the time. Then researchers put the letters of the alphabet into a matrix with each column and row labeled with a single-digit number.
In that way, each letter was represented by a unique pair of number co-ordinates. These were used to silently spell "NASA" into a web search engine using the program. This proved we could browse the web without touching a keyboard. Huge crowds at the fair gathered round a man sitting at a pinball table, wearing a cap covered in electrodes attached to his head, who controlled the flippers with great proficiency without using hands.
But the technology is much more than a fun gadget, it could one day save your life. This wheelchair can move with the power of mind. This thing works by mapping brain waves when you think about moving left, right, forward or back, and then assigns required actions to a wheelchair command of actually moving left, right, forward or back. This could be useful for people who are paralyzed, and are unable to control parts of their body enough to physically activate the joystick of an electric wheelchair.
Many people may be able to use this technology to gain some independence, and to take a break from needing an attendant to push their wheelchair so they can get some fresh air. The parts of this system include an electric wheelchair, a laptop computer, an Arduino, an interface circuit, an EEG headset, and a collection of ready-made and custom software.
The EEG headset, which connects wirelessly to the laptop, allows the operator to simply think "forward" or "left" or "right" to cause the wheelchair to move. Performance is related to practice by the user, proper configuration of the software, and good contact made by the EEG electrodes on the scalp of the operator. The interface circuit connects between the Arduino's digital pins and the joystick of the wheelchair.
When the Arduino receives a command from the computer, it causes the circuit to "fool" the wheelchair into thinking that the operator has moved the joystick. Keyboards and mouse may be the history in coming 5 years, and would be simply used in teaching of evolution of computers. IBM researcher are using a simple brain-machine interface BMI that can detect different kinds of brainwaves and tell a computer to respond a certain way.
So that in an emergency stop situation, the brain activity kicks in on average around milli-seconds before even an alert driver can hit the brake. Users wear futuristic-looking headbands to shine light on their foreheads, and then perform a series of increasingly difficult tasks while the device reads what parts of the brain are absorbing the light.
That info is then transferred to the computer, and from there the computer can adjust its interface and functions to each individual. How to build a baby that can read minds: Cognitive mechanisms in mindreading. Current Psychology of Cognition, 13 5 —, Baron-Cohen and T. And while the detection of brain-wave patterns has been possible for decades, the missing ingredient was the ability to interpret them. But now, thanks to artificial intelligence A.
The general process is this. Once mapped, future readouts can be read, interpreted and used for various kinds of mind-revealing or mental-control applications.
For example, MIT geniuses have invented a face-mounted device, plus a machine-learning application, that performs real-time speech-to-text conversion — but without the speech part. Electrodes on the device intercept neuromuscular signals sent by the brain to the face, and the machine-learning application transcribes them into text.
Researchers use a neural network to match specific neuromuscular signals with specific words. The device also provides bone conduction output. That means you could make requests of a virtual assistant and get results audible only to you, all without the knowledge of people sitting right in front of you. Also, it merely takes an existing behavior — spoken and audible interaction with a virtual assistant — and makes it silent and invisible, thereby increasing the range of situations where one could use a virtual assistant.
A video shows just how well this could work. Of course, the device itself looks ridiculous. Instead of understanding the words a person is subvocalizing, it can detect what that person is hearing, with brain activity alone. The researchers took advantage of a kind of epilepsy treatment whereby electrodes are implanted directly on the surface of the brain. Scientists used those electrodes for a second purpose, which was to monitor brain waves in the auditory cortex.
They took that data and used algorithms to decode the specific speech sounds as they were being heard by the subject. Even Facebook has a mind-reading project in the works. One example is to turn down the volume of music based on the mental activity of being irritated by loud noise.
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