17 March 2019

Facebook Reality Labs Creates Realistic Avatars

Facebook Reality Labs (FRL) believes AR and VR will be the primary way people work, play, and connect in the future. Dubbed ‘Codec Avatars’, the Pittsburgh office is using what they call groundbreaking 3D capture technology and AI systems to generate lifelike virtual avatars that could provide the basis of a quick and easy personal avatar creator of the future. The company says at this point these sorts of real-time, photorealistic avatars require quite the gear to achieve. The lab’s two capture studios—one for the face, and one for the body—are admittedly both large and impractical at this point. 


The ultimate goal however is to achieve all of this through lightweight headsets, although FRL Pittsburgh currently uses its own prototype Head Mounted Capture systems (HMCs) equipped with cameras, accelerometers, gyroscopes, magnetometers, infrared lighting, and microphones to capture the full range of human expression. Using a small group of participants, the lab captures 1GB of data per second in effort to create a database of physical traits. In the future, the hope is consumers will be able to create their own avatars without a capture studio and without much data either.

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16 March 2019

Non-Invasive Biofluid Sensor

Researchers from the University of Cincinnati examined the potential bio-fluids to test human health with tiny, portable sensors. They developed wearable technology by creating the world's first continuous-testing device that samples sweat as effectively as blood but in a non-invasive way and over many hours. Remarkably, many of the innovations in the field of biosensors and sweat technology were developed in Cincinnati (i.e. the first glucose monitor for diabetes). 


Now researchers identified four waves of discovery when it comes to testing human health. First, doctors began drawing and shipping blood to labs in an invasive, time-consuming and labor-intensive process that patients still undergo today. After examining the use of saliva, tears and interstitial fluid, they concluded that sweat holds the most promise for non-invasive testing because it provides similar information as blood and its secretion rate can be controlled and measured.

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03 March 2019

Schizophrenia Patients May be Calmed by Video Games

People with schizophrenia can be trained by playing a video game to control the part of the brain linked to verbal hallucinations, researchers say. Patients in a small study were able to land a rocket in the game when it was connected to the brain region sensitive to speech and human voices. In time, the patients learnt to use the technique in their daily lives to reduce the power of hallucinations. But this is a small pilot study and the findings still need to be confirmed. The research team, from King's College London's Institute of Psychiatry, Psychology and Neuroscience and the University of Roehampton, says the technique could be used to help schizophrenia patients who do not respond to medication.


People with the condition are known to have a more active auditory cortex, which means they are more sensitive to sounds and voices. All 12 patients in the study experienced nasty and threatening verbal hallucinations every day - a common symptom of schizophrenia. To try to control their symptoms, they were asked to play a video game while in an MRI scanner, using their own mental strategies to move a computerised rocket - and in doing so they were able to turn down the volume on the external voices they heard as well. all the patients in the study, who each had four turns in the MRI scanner, found that their voices became less external and more internal, making them less stressful. They were also better able to cope with them.

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01 March 2019

EEG Enlights the Subcortical Areas of Brain

The subcortical areas of the brain, situated in its deepest reaches, remain a mystery. Scientists are aware of the critical role they play in motor, emotional and associative activity but do not know precisely how they work. A number of serious diseases are directly linked to these areas, including Parkinson’s, Tourette syndrome and obsessive-compulsive disorders (OCD). Existing treatments for regulating and measuring the activity of the subcortical areas are highly invasive, and sometimes work without us really knowing how. Researchers from the University of Geneva (UNIGE), Switzerland, and Cologne University (Germany) decided to see whether a non-invasive method – electroencephalography (EEG) – could be employed in tandem with mathematical algorithms to measure this brain activity externally. They proved for the first time that this technique is able to record signals usually only seen by implanting electrodes in the brain. 


Current treatments, based on deep brain stimulation are highly invasive: implanting electrodes into the centre of the brain, which are stimulated electrically by an external stimulator. Although this technique has been shown to be effective in Parkinson’s, unfortunately it doesn’t work so well for OCD and Tourette syndrome. Since implanting electrodes is an extremely invasive technique, another method was called for to increase the number of subjects studied. Researchers were able to measure and record the electrical activity of the subcortical areas of four OCD and Tourette’s patients who had been given electrode implants. At the same time, these individuals were equipped with an EEG as the scientists measured the activity of the same areas from the surface. The mathematical algorithms that they developed meant that they could accurately interpret the data provided by the EEG and ascertain where the brain activity was coming from.

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27 February 2019

Gestures for Social Robots

Social robots are designed to communicate with human beings naturally, assisting them with a variety of tasks. The effective use of gestures could greatly enhance robot-human interactions, allowing robots to communicate both verbally and non-verbally. Researchers at Vrije Universiteit Brussel, in Belgium, have recently introduced a new approach based on a generic gesture method to study the influence of different design aspects. The method devised by this team of researchers could overcome difficulties in transferring gestures to robots of different shapes and configurations. Users can input a robot's morphological information and the tool will use this data to calculate the gestures for that robot. To ensure that their method would be applicable to different types of robots, the researchers drew inspiration from a human base model. This model consists of different chains and blocks, which are used to model the various rotational possibilities of humans.


The researchers assigned a reference frame to each joint block using the human base model as a reference to construct the general framework behind their method. As different features are important for different kinds of gestures, the method devised by the researchers is designed to work in two different modes, namely the block mode and end effector mode. The block mode is used to calculate gestures such as emotional expressions in instances when the overall arm placement is crucial. The end effector mode, on the other hand, calculates gestures in situations in which the position of the end-effector is important, such as during object manipulation or pointing. In their study, the researchers applied their method to the virtual model of a robot called Probo. They used this example to illustrate how their method could help to study the collocation of different joints and joint angle ranges in gestures.

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24 February 2019

Understanding Optical Illusions Using Computer Vision

Optical illusions, images that deceive the human eye, are a fascinating research topic, as studying them can provide valuable insight into human cognition and perception. Researchers at Flinders University, in Australia, have recently carried out a very interesting study using a computer vision model to predict the existence of optical illusions and the degree of their effect.


In their study, the researchers evaluated a computational filtering model that is designed to model the lateral inhibition of retinal ganglion cells and their responses to different geometric illusions. Adopting this approach, the researchers hoped to achieve a better understanding of these illusions, predicting the degree of their effect.

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