health
U.S. funds research towards street intersection analyzer for the blind
The U.S. National Institutes of Health (NIH) is providing $400,000 in funding to Dr. James Coughlan, of the Smith-Kettlewell Eye Research Institute, to develop tools to help the visually impaired. Building on the team's existing computer vision software for detecting crosswalks and 'walk' lights, the new system will help the blind and visually impaired navigate across intersections via continous feedback. The goal is to deploy the system in the form of free smartphone apps for common platforms such as Android and iOS so that users will not have to carry a separate device.
New MIT algorithm speeds up MRI scans
Researchers from MIT (Elfar Adalsteinsson and Vivek Goyal) have developed a new imaging algorithm that could reduce magnetic resonance imaging (MRI) scans from 45 to 15 minutes. Using information from the MRI's first contrast scan, the algorithm predicts the likely object boundaries between different types of tissues in subsequent scans. The researchers are now working to improve the algorithm and accelerate the processing time on a GPU. More information is available in a MIT news article.
Computer vision and 3D printing for drug discovery
A fastcodesign.com article reports on an augmented reality (AR) tool for molecular drug design. Arthur Olson of the Scripps Institute Molecular Graphics Laboratory has developed a aystem in which a 3D printer creates solid models of drug and enzyme molecules; and a web cam tracks them to create AR overlays that help scientists figure out how the molecules can fit together.
Computer vision used to confirm hand washing in hospitals
In a press release, Sealed Air announced the release of its Vision Safety Solutions (VSS) system which monitors staff handwashing in hospitals. An RFID tag in a badge identifies the staff member, and computer vision algorithms analyze imagery to verify the duration of hand washing and that soap was used.
Kinect used for privacy-sensitive monitoring in assisted-care facilities
Researchers at the University of Missouri have developed a monitoring system for assisted-care facilities. Using the Microsoft Xbox Kinect device, behaviors and changes in routines in patients can be monitored. According to the researchers, "the Kinect uses infrared light to create a depth image that produces data in the form of a silhouette, instead of a video or photograph...this alleviates many seniors’ concerns about privacy when traditional web camera-based monitoring systems are used." More information is available in a press release.
U.S. funds research on computer vision for physical rehabilitation
The U.S. National Science Foundation (NSF) has awarded a $1.2 million grant to Yun Fu, Venkat Krovi, and Dan Ramsey of SUNY-Buffalo to use computer vision to help patients with physical rehabilitation.
Abstract of the research:
Quantitative Visual Sensing of Dynamic Behaviors for Home-based Progressive Rehabilitation
The objective of this research is to develop a comprehensive theoretical and experimental cyber-physical framework to enable intelligent human-environment interaction capabilities by a synergistic combination of computer vision and robotics. Specifically, the approach is applied to examine individualized remote rehabilitation with an intelligent, articulated, and adjustable lower limb orthotic brace to manage Knee Osteoarthritis, where a visual-sensing/dynamical-systems perspective is adopted to: (1) track and record patient/device interactions with internet-enabled commercial-off-the-shelf computer-vision-devices; (2) abstract the interactions into parametric and composable low-dimensional manifold representations; (3) link to quantitative biomechanical assessment of the individual patients; (4) facilitate development of individualized user models and exercise regimen; and (5) aid the progressive parametric refinement of exercises and adjustment of bracing devices. This research and its results will enable us to understand underlying human neuro-musculo-skeletal and locomotion principles by merging notions of quantitative data acquisition, and lower-order modeling coupled with individualized feedback. Beyond efficient representation, the quantitative visual models offer the potential to capture fundamental underlying physical, physiological, and behavioral mechanisms grounded on biomechanical assessments, and thereby afford insights into the generative hypotheses of human actions.
U.S. issues 8,000,000th patent for a vision-related invention
The U.S. Patent Office issued patent number 8,000,000 on August 16th for a vision-related invention. Inventors Robert Greenberg, Kelly McClure, and Arup Roy of Second Sight Medical Products were awarded U.S. patent number 8,000,000 for a Visual Prosthesis, a device that performs video processing (for example, edge detection) on camera input to generate patterns which then electrically stimulate a retina in patients with low vision.
This patent was issued 100 years and 1 week after the 1,000,000th patent. The millionth patent, issued at the dawn of the automobile era, was for improvements in tires. It is fitting that the 8,000,000th patent is for video processing and biomedical engineering, two fields that are rapidly advancing, important technologies in the 21st century.
User intent through eye movement
Researchers at the Royal Holloway, University of London, have developed a computer program that recognizes the intent of children with disabilities by analyzing their eye movements. The patterns of eye movements for a particular child are matched against preferences. More information is available from The Engineer (United Kingdom) article.
BabyBeat prevents SIDS using vision
Researchers at Ben-Gurion University of the Negev (BGU) have developed BabyBeat, a vision-based system to monitor infants and prevent Sudden Infant Death Syndrome (SIDS). By analyzing the baby's heartbeat and skin tone in video footage, BabyBeat can detect the abonormal signs that are indicators of SIDS. The work is led by Tomer Apel and Anava Finesilver. More information is available in a press release.
Computer vision to enhance quality of life for vision-impaired
A University of Oxford research team led by Dr. Stephen Hicks is developing glasses to enhance the quality of life for patients with severe visual impairment. The system uses computer vision algorithms for motion detection and recognition, then presents relevant information about the detected events in a visual form that that the wearer can benefit from. The vision prosthesis, which was demonstrated at the Royal Society Summer Science Exhibition, is expected to aid patients with conditions such as age-related macular degeneration (AMD) and retinitis pigmentosa. More information is available from the Royal Society's web site.