Categories
Assistive Technologies Sensors

“Artificial skin” senses touch, temperature, humidity

http://www.sciencedaily.com/releases/2013/07/130708124423.htm

Professor Hossam Haick at the Technion-Israel Institute of Technology has created a flexible sensor that could be integrated into electronic skin, enabling those with prosthetic limbs to feel changes in their environments.  The Technion invention simultaneously senses touch, humidity, and temperature. According to Professor Haick, it is at least 10 times more sensitive to touch than current systems.  It should be compared to the technology developed by University of Illinois Professor John Rogers (see ApplySci posts of March 13, 2013 and June 8, 2013) and being commercialized by mc10.

Categories
BCI Brain Machine Learning Signal Processing

Brain Computer Interface – a timeline

http://www.livescience.com/37944-how-the-human-computer-interface-works-infographics.html

From the Babbage Analytical Engine of 1822 through thought control – a brief history of the intersection of mind and machine.

Categories
Brain

Avatar therapy addresses voices in schizophrenia

http://www.uclb.com/news-and-events/news-post/avatar-therapy-helps-silence-voices-in-schizophrenia

Researchers at University College London and the Wellcome Trust have developed an avatar based system to enable those suffering from schizophrenia to control the voice of hallucinations.

The patient creates a computer-based avatar, choosing the face and voice of the entity they believe is talking to them. The system then synchronizes the avatar’s lips with its speech, enabling a therapist to speak to the patient through the avatar in real time. The therapist encourages the patient to oppose the voice and attempts to help them take control of their hallucinations.

Professor Julian Leff developed the therapy and is leading the project. He said: “Even though patients interact with the avatar as though it was a real person, because they have created it, they know that it cannot harm them, as opposed to the voices, which often threaten to kill or harm them and their family. As a result the therapy helps patients gain the confidence and courage to confront the avatar, and their persecutor.  We record every therapy session on MP3 so that the patient essentially has a therapist in their pocket which they can listen to at any time when harassed by the voices. We’ve found that this helps them to recognize that the voices originate within their own mind and reinforces their control over the hallucinations.”

Categories
Apps Sensors

Software senses mood of smartphone users

http://research.microsoft.com/apps/pubs/default.aspx?id=194498

Microsoft’s MoodScope is a “sensor” that measures a smartphone user’s mental state.  It analyzes an enormous array of interactions including app usage, phone calls, emails, text messages, browsing history, and geographic location — thousands of data points each day. 32 study participants used the system for two months, and completed mood self-assessments to gauge the accuracy of the software.  The app was able to guess someone’s mood with 66% accuracy.  When the software was “calibrated” for an individual user, accuracy increased to 93%.

Categories
Cancer Ultrasound

Sound waves detect disease related changes in red blood cell shape

http://www.cell.com/biophysj/abstract/S0006-3495(13)00624-3

Ryerson University investigators used photoacoustics to create detailed images to detect changing shapes of red blood cells associated with diseases including maria, sickle cell anemia and certain types of cancer.

A drop of blood is placed under a microscope that picks up sounds produced by the cells. Researchers then focus a laser beam on the samples. As the blood cells absorb energy from the laser pulse, they release some of it in the form of sound waves, enabling scientists to understand details about the shape of the cell.

Categories
Pregnancy

Algorithm determines embryo quality in IVF procedures

http://pc2013.afeka.ac.il/files/assets/basic-html/page238.html

Researchers from Tel Aviv’s Afeka College of Engineering and Sourasky Medical Center have developed software to find the best embryos for IVF procedures.  Their algorithm uses Matlab to process microscopic pictures to choose the highest quality fertilized egg.

Today embryologists use a microscope to find the best embryos, which five days later are inserted into the uterus. “The examination done now depends on the embryologist and isn’t precise. The new test increases the potential for choosing as healthy an embryo as possible,” said lead researcher Danai Menuhin.

Categories
Eyes

LCD display, embedded in contact lenses — Google Glass functionality with out headgear?

http://www.ugent.be/en/news/bulletin/augmented-reality-contact-lens

Professor Jelle De Smet of Ghent University has developed a spherical, curved LCD display which can be embedded in contact lenses and handle projected images using wireless technology.  This is the first step towards “fully pixelated contact lens displays” with the same detail as a television screen.  The technology could lead to a superimposed image projected onto the user’s normal view, similar to Google Glass but without the headgear.  The lenses could also be used for medical purposes, including controlling light transmission toward the eye’s retina when an iris is damaged, or to display directions or texts from a smartphone.

Categories
Brain

High resolution mapping uncovers brain circuit architecture

http://www.salk.edu/news/pressrelease_details.php?press_id=623

Salk and Gladstone Institute scientists have found a way to untangle neural networks by enhancing a brain mapping technique that they first developed in 2007.

“These initial results should be treated as a resource not only for decoding how this network guides the vast array of very distinct brain functions, but also how dysfunctions in different parts of this network can lead to different neurological conditions,” said Salk professor Edward Callaway.

The researchers combined mouse models with a tracing technique known as the monosynaptic rabies virus system to assemble maps of neurons that connect with the basal ganglia, a region of the brain that is involved in movement and decision making.

“The monosynaptic rabies virus approach is ingenious in the exquisite precision that it offers compared with previous methods, which were messier with a much lower resolution,” explained Gladstone investigator Professor Anatol Kreitzer.  “In this paper, we took the approach one step further by activating the tracer genetically, which ensures that it is only turned on in specific neurons in the basal ganglia. This is a huge leap forward technologically, as we can be sure that we’re following only the networks that connect to particular kinds of cells in the basal ganglia from other parts of the brain.”

Categories
Apps Eyes mHealth

Smartphone diagnostic and cloud platform make eye care accessible

http://eyenetra.com/netra-g.html

Vinod Khosla and others have invested in MIT Media Lab’s EyeNetra, a smartphone attachment that claims to diagnose nearsightedness, farsightedness and astigmatism.  The device is positioned as a less bulky alternative to the Shack-Hartmann Wavefront sensor.  A $2 eyepiece is clipped onto a phone.  The user then clicks to align the displayed patterns.  The number of clicks required to bring the patterns into alignment indicates the refractive error.  Patients connect to corrective lens providers through a cloud based system.  The technology provides access to eye exams in the developing world.

Categories
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.

Categories
Sensors

Non-invasive nanotube device detects disease with one drop of blood

http://www.njit.edu/news/2013/2013-218.php

Professors Reginald Farrow and Alokik Kanwal of the New Jersey Institute of Technology have created a carbon nanotube-based device to non-invasively and quickly detect mobile single cells with the potential to maintain a high degree of spatial resolution.  They are now overseeing the manufacture of a prototype lab-on-a-chip that would enable a physician to detect disease or virus from just one drop of liquid, including blood.

The military was the initial funder of the research, in an attempt to identify biological warfare agents.  Farrow believes that it can be applied much more widely to detect viruses, bacteria, or cancer.  The next phase of research will include a study of the device’s ability to assess the health of brain neurons.

Categories
AI Heart

Algorithm analyzes head movements to measure heart rate

http://web.mit.edu/newsoffice/2013/seeing-the-human-pulse-0620.html

MIT researchers have developed an algorithm that gauges heart rate by measuring tiny head movements in video data.  A subject’s heart rate was consistently measured within a few beats per minute when compared to results from electrocardiograms. The algorithm was also able to provide estimates of time intervals between beats, which can be used to identify patients who are at risk for cardiac events.

The algorithm uses face recognition to differentiate between the person’s head and the rest of the image.  It then randomly picks 500 to 1,000 exact points, clustered around the person’s mouth and nose.  Movements are followed from frame to frame, and filtered when the temporal frequency falls below the range of a regular heartbeat – about 0.5 to 5 hertz, or 30 to 300 cycles per minute. This eliminates movements that continue at a lower frequency, such as those caused by regular breathing and slow alterations in posture.  Principal component analysis is used to break down the resulting signal into many constituent signals, which stand as part of the uncorrelated leftover movements. Of those signals, it chooses one that appears to be the most regular and that drops within the typical frequency band of the human pulse.