What is Artificial Intelligence?

a new IT tool that automatically regulates administration of anesthesia to patients undergoing surgery

A new artificial intelligent system has been recently launched to regulate specific administration of anesthesia during a surgery.

Before the advent of artificial intelligent system, surgeons and anesthesiologists have no accurate way of knowing the how long or how effective is a kind of anesthesia to a patient during critical operations. They mainly rely on physical reactions of the patient to pain, thus immediately increasing dosage of anesthesia.

In Canary Islands, a team of research scientists from the Anesthesia Control Group at the University of La Laguna (ULL) developed a new IT tool that constantly monitors the level of hypnosis or unconsciousness of the patient while being operated.

With a team of anesthetists from the University Hospital of the Canary Islands, Juan Albino Méndez, lead author and researcher, spearheaded this project which regulates doses of anesthesia in operating theaters via a computer.

This artificial intelligent system uses sensors and a computer monitor to keep track of the patient's EEG and bi-spectral index (BIS), a parameter that measures hypnotic states without units.

The program relies on a detection algorithm that automatically controls a pump to inject anesthesia to the patient whenever needed.

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Left brain after the first trial; Right brain after 10 minutes of practice controlling movement of cursor through imagination

The human brain signals has been a subject of curiosity and exploration. And in a recent study, it showed that by just thinking about controlling the movement of a computer cursor, brain neurons populate to make it happen in real life.

As published in Proceedings of the National Academy of Sciences, scientists from the University of Washington observed the brain signals in its surface while using imagination to control the movements of computer cursor. The activity was proven with the brain-computer interface connecting the brain through tiny electrodes.

The team of experts studied eight patients awaiting surgery for epilepsy at two hospitals in Seattle. They were placed with electrodes connected to their brains' surface during the week of observation prior to the scheduled surgery.

They asked these patients to imagine moving their arms while brain activities were recorded. Then, they asked the patients to imagine moving a computer cursor towards a target object in the computer screen. And after just 10 minutes of doing so, they actually enjoyed controlling the movement of the computer cursor like it was something they do physically.

Now, this findings also provide marks on which brain signals to tap to aid in the treatment of brain-related diseases like epilepsy.

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Flame, the first ever walking robot to imitate humans

A new robot named Flame was developed by Daan Hobbelen, a PhD student at TU Delft in the Netherlands.

This robot is based on the principles of human walking and this is considered to be most advance robot in its kind. Flame can cope to achieve great stability while remaining energy efficient.

In the two groups of walking robot, Flame is categorized in the second group which is designed to imitate human walking in the sense that the robot is executing a controlled fall forward. This type of robot is not very energy consuming and is not that costly.

Flame is 1.3 m in height and is about 15 kg. It has seven motors. It does not fall and can manage to stay stable because of “organ balance” and a sequence of algorithms which calculate where and how far apart the robot’s ‘feet’ should be placed.

The upper body of Flame has PC104 computer which has a real-time Linux kernel (RTAI) running a control loop and can implement torque and/or position control on all actuated joints.

According to Hobbelen, Flame is the first walking robot with electric actuation. This research might further the development of treatment and diagnosis for people who have difficulty in walking.

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Scientists from the Max Planck Institute for Biological Cybernetics discovered that we are able to classify an expression much better when it moves naturally.

Scientists from the Max Planck Institute for Biological Cybernetics in Tübingen, Germany learned that we can recognize facial expressions better when it is moving naturally rather than when it is in a static photograph.

There are many explanations for each facial expression. A frown may say: “Please explain that again!". A nod may signify that you understand.

We must see the expression moving for at least 100 milliseconds in order for us to gain the advantage of dynamic information. Our brain is less capable of decoding the facial motion if the video sequence is shorter.

There are series of experiments that these scientists do in order for them to prove their theories. The result of the experiment shows that either pictures or motion alone are what is needed, but it’s the combination of the temporal sequence and the right facial motion to consistently interpret facial expressions.

Dr. Christian Wallraven, co-author of the study said, "Our results also have implications for the area of computer animation, since its goal is to create artificial avatars and facial animations that are able to communicate realistically and believably."

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Matt Bunting, student with his very own Hexapod

"One of the things I wanted to explore was the idea of reinforcement learning using an artificial intelligence... I wanted it to figure out how to walk straight forward on its (hexapod) own”, said Matt Bunting, a senior at the University of Arizona in electrical engineering.

Hexapod was Bunting's final class project on cognitive robotics. Built from spare parts, and to let the robot adaptively learn how to move he used an Intel Atom processor powering an Ubuntu OS computer. With Logitech Quick Cam to watches what happens when movements are initiated, and a changing scene to determine what effect the movements are having.

Intel ordered themselves two copies to take on an international publicity tour for the Atom processor. A couple days after Matt posted a video of his bot on YouTube, Then, the company who provided Matt with the servos, Crust Crawler Robotics, asked Matt to help develop a software for some of their hexapod kits.

Matt's hexapod Artificial intelligence learning can be applied to tasks other than wait, it can relearn how to walk. The robot even has foot contact sensors that can be used for terrain adaptation.

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