Category: Autism

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Autism Brain Wearables

Glass apps help autistic kids communicate

Brain Power‘s Google Glass apps and hardware help autistic kids develop social and communication skills, and provide feedback to parents.

The device’s accelerometer tracks children’s head gestures when they look or don’t look at parents, as well as repetitive movements.  “Social engagement module monitors” assess the child’s engagement, specifically if they are looking at a parent’s face and eyes.  Software helps the wearer interpret expressions through games and exercises.  The goal is to help them understand facial emotions  when they aren’t wearing Glass.

To develop language skills, objects are identified through machine vision, and their names are displayed and spoken through the speaker or earbud.  Children will eventually receive personalized language and conversation coaching.  Software will also use the accelerometer to predict over-excitement and provide calming suggestions.

 

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Autism Brain Children EEG

EEG could lead to earlier autism diagnosis

Albert Einstein College of Medicine professor Sophie Molholm has published a paper describing the way that autistic children process sensory information, as determined by EEG.  She believes that this could lead to earlier diagnosis (before symptoms of social and developmental delays emerge), hence earlier treatment, which might reduce the condition’s symptoms.

EEG readings were taken from 40 children, ages 6-17, who were diagnosed with autism,  and compared to those of unaffected children of similar age.  All were given either a flash cue, a beep cue or a combination, and asked to press a button when these stimuli occurred.  A 70 electrode cap measured brain responses every two milliseconds, including those that recorded how the brain first processed the information.

The children with autism showed a distinctly different brain wave signature from those without the condition.  There were differences in the speed in which the sights or sounds were processed, and in how the sensory neurons recruited neurons in other areas of the brain to register and understand the information. The more different this multi-processing was, the more severe the child’s autistic symptoms.

Professor Molholm acknowledges that the sample was too small to use the profile for diagnosing autism, but it could lead to such a test if the results are confirmed and repeated.

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Autism Brain

Brain blueprint links autism to early brain development

As part of their BrainSpan project, the Allen Institute for Brain Science has published a paper in Nature detailing a high-resolution blueprint for how to build a human brain, with a map of where different genes are turned on and off during mid-pregnancy at unprecedented anatomical resolution.  The data provides insight into diseases like autism that are linked to early brain development.

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Autism Brain

Micromovement study for diagnosing autism severity

http://news.medicine.iu.edu/releases/2013/12/jose-neuroscience.shtml

Indiana University professor Jorge V. José and Rutgers professor Elizabeth Torres are building on findings involving the random nature of movements of people with autism.  Earlier research looked at the speed maximum and randomness of movement during a computer exercise that involved tracking the motions of youths with autism when touching an image on the screen to indicate a decision.  In the new study, the researchers looked at the entire movement involved in raising and extending a hand to touch a computer screen. The device they use can record 240 frames per second, which allows them to measure speed changes in the millisecond range.

According to Professor Jose:  “Looking at the speed versus time curves of the motion in much more detail, we noticed that in general many smaller oscillations or fluctuations occur even when the hand is resting in the lap. We decided to carefully study that jitter. Our remarkable finding is that the fluctuations in this jitter are not just random fluctuations, but they do correspond to unique characteristics of the degree of autism each child has.”

The next step is to compare the output of the new methodology in individuals with autism of idiopathic origins with those with autism of known etiology. The new refinement may help advance research in autism spectrum disorder to develop treatments tailored to the individual’s needs and capabilities.

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Autism Brain Eyes Machine Learning Parkinson's

Eye tracking data helps diagnose autism, ADHD, Parkinson’s

http://www.scientificamerican.com/article.cfm?id=eye-tracking-software-may-reveal-autism-and-other-brain-disorders

USC’s Laurent Itti and researchers from Queen’s University in Ontario have created a data heavy, low cost method of identifying brain disorders through eye tracking.  Subjects watch a video for 15 minutes while their eye movements are recorded. An enormous amount of data is generated as the average person makes three to five saccadic eye movements per second.  Itti’s team uses advanced machine learning algorithms to enable a computer to recognize patterns without explicit human instruction.

The proof of concept study found that the algorithm could classify mental disorders through eye movement patterns.  Parkinson’s patients were identified with nearly 90 percent accuracy.  Children with ADHD or fetal alcohol spectrum disorder were identified with 77 percent accuracy.  “This is very different from what people have done before. We’re trying to have completely automated interpretation of the eye movement data,” said Itti.

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Autism

Research links autism to environmental factors

https://imfar.confex.com/imfar/2013/webprogram/Paper14885.html

New studies lend strength to the notion that environmental influences before birth play a role in the risk for the autism.

At the recent International Society for Autism Research annual conference, Marc Weisskopf of the Harvard School of Public Health presented results from a large national study, known as the Nurses’ Health Study II.  The research suggested that a mother’s exposure to high levels of certain types of air pollutants, such as metals and diesel particles, increased the risk of autism by an average of 30% to 50%, compared with women who were exposed to the lowest levels.