We use cookies to understand how you use our site and to improve your experience. This includes personalizing content and advertising. To learn more, click here. By continuing to use our site, you accept our use of cookies. Cookie Policy.

Features Partner Sites Information LinkXpress
Sign In
Advertise with Us

Download Mobile App




AI Study Sees through Walls and Occlusions

By HospiMedica International staff writers
Posted on 28 Jun 2018
Print article
Image: A new study shows how artificial intelligence can identify human motion and posture, even through walls (Photo courtesy of CSAIL).
Image: A new study shows how artificial intelligence can identify human motion and posture, even through walls (Photo courtesy of CSAIL).
A new study describes how artificial intelligence (AI) can be used to analyze radio signals bouncing off people's bodies so as to study posture and movement, even through walls.

The Massachusetts Institute of Technology (MIT, Cambridge, MA, USA) RF-Pose project is based on a deep neural network approach that parses wireless signals in the WiFi frequencies in order to estimate human poses and postures. One of the stumbling blocks in the process is that teaching AI networks to identify visual patterns relies on human annotation; but since radio signals cannot be annotated, the researchers used a state-of-the-art vision model to provide cross-modal supervision.

This involved collecting thousands of examples of both wireless device data and matched photographic images of people doing activities like walking, talking, sitting, opening doors, and waiting for elevators. They then used the images to extract stick figures, which they showed to the AI neural network along with the corresponding radio signal. The combined data enabled the AI system to learn the association between the radio signal and the stick figures of the people in a given scene. Once trained, the network used only the wireless signal for pose estimation.

The results showed that when tested on visible scenes, the radio-based system is almost as accurate as the vision-based system used to train it. But unlike vision-based pose estimation, the radio-based system can also estimate two-dimensional (2D) poses through walls, despite never being trained on such scenarios. The researchers suggest the system could monitor patients with Parkinson's disease, multiple sclerosis (MS), and other issues, as well as provide an added security for seniors at home by monitoring falls, injuries, and changes in activity patterns. The study was presented at the annual conference on Computer Vision and Pattern Recognition (CVPR), held during June 2018 in Salt Lake City (UT, USA).

“Just like how cellphones and Wi-Fi routers have become essential parts of today's households, I believe that wireless technologies like these will help power the homes of the future,” said senior author Professor Dina Katabi, PhD, of the MIT Computer Science and Artificial Intelligence Laboratory (CSAIL). “We've seen that monitoring patients' walking speed and ability to do basic activities on their own gives healthcare providers a window into their lives that they didn't have before, which could be meaningful for a whole range of diseases.”

Related Links:
Massachusetts Institute of Technology

Gold Member
Real-Time Diagnostics Onscreen Viewer
GEMweb Live
Gold Member
SARS‑CoV‑2/Flu A/Flu B/RSV Sample-To-Answer Test
SARS‑CoV‑2/Flu A/Flu B/RSV Cartridge (CE-IVD)
Silver Member
Compact 14-Day Uninterrupted Holter ECG
NR-314P
New
Critical Care Trolley
CCT-PX

Print article

Channels

Critical Care

view channel
Image: Researchers have developed an advanced shear-thinning hydrogel for aneurysm repair (Photo courtesy of TIBI)

New Hydrogel Features Enhanced Capabilities for Treating Aneurysms and Halting Progression

Aneurysms can develop in blood vessels in different body areas, often as a result of atherosclerosis, infections, inflammatory diseases, and other risk factors. These conditions lead to chronic inflammation,... Read more

Surgical Techniques

view channel
Image: The living replacement knee will be tested in clinical trials within five years (Photo courtesy of ARPA-H)

Living Knee Replacement to Revolutionize Osteoarthritis Treatment

Osteoarthritis is the most prevalent type of arthritis, characterized by the progressive deterioration of cartilage, or the protective tissue covering the bone ends, resulting in pain, stiffness, and impaired... Read more

Patient Care

view channel
Image: The newly-launched solution can transform operating room scheduling and boost utilization rates (Photo courtesy of Fujitsu)

Surgical Capacity Optimization Solution Helps Hospitals Boost OR Utilization

An innovative solution has the capability to transform surgical capacity utilization by targeting the root cause of surgical block time inefficiencies. Fujitsu Limited’s (Tokyo, Japan) Surgical Capacity... Read more

Health IT

view channel
Image: First ever institution-specific model provides significant performance advantage over current population-derived models (Photo courtesy of Mount Sinai)

Machine Learning Model Improves Mortality Risk Prediction for Cardiac Surgery Patients

Machine learning algorithms have been deployed to create predictive models in various medical fields, with some demonstrating improved outcomes compared to their standard-of-care counterparts.... Read more

Point of Care

view channel
Image: The new eye-safe laser technology can diagnose traumatic brain injury (Photo courtesy of 123RF)

Novel Diagnostic Hand-Held Device Detects Known Biomarkers for Traumatic Brain Injury

The growing need for prompt and efficient diagnosis of traumatic brain injury (TBI), a major cause of mortality globally, has spurred the development of innovative diagnostic technologies.... Read more
Copyright © 2000-2024 Globetech Media. All rights reserved.