Once the Trump administration established Operation Warp Speed (OWS) in response to the ongoing pandemic, the Cybersecurity and Infrastructure Security Agency (CISA) "quickly began working with the Department of Health and Human Services, the Department of Defense, and the pharmaceutical industry to identify these entities and ensure they directly received necessary additional cyber security support, such as vulnerability scanning services, information sharing, and incident response," Brandon Wales, acting director of CISA, told a Senate panel.

Wales said that 62 percent of the "most important" entities involved in OWS have adopted CISA's Cyber Hygiene service, which performs regular scans of an organization's public facing web address for known vulnerabilities and automatically reports results to the entity. He said 100 percent of OWS prime entities responsible for delivering COVID-19 vaccines have adopted Cyber Hygiene.

The same percentages of adoption hold true for these entities receiving a service from CISA and the intelligence community called Overwatch that monitors threats involving organization names, domains and internet protocol addresses, Wales said.

At the outset of the pandemic, 5 percent of the OWS entities were receiving Cyber Hygiene services and none the Overwatch services, he said in his written testimony to the Homeland Security and Governmental Affairs Subcommittee on Federal Spending Oversight and Emergency Management.

OWS stood up in May. Since then, CISA has conducted six incident investigations, published two cyber advisory alerts about threats targeting OWS entities, provided notifications of eight critical vulnerabilities, provided four advanced warnings of state-sponsored cyber threats, and provided six notifications to entities regarding critical vulnerabilities, threat targeting or compromise, Wales said.

"Through our cyber security defensive services, our vulnerability scanning, and our information sharing mechanisms, we are engaging with these critical organizations to assist them in establishing a strong defense today as well as a culture of resilience moving forward," Wales said. "In addition, we continue to assess the national critical functions, which allows us to identify and mitigate risk before it impacts critical infrastructure."

The post CISA Services In High Demand Related To COVID Vaccine Response appeared first on IIOT Connection.

Researchers from the Massachusetts Institute of Technology, Cambridge, have developed an artificial intelligence (AI) tool that can detect COVID-19 by listening to patients' coughs, regardless if they are symptomatic or not.

To build the tool, the researchers solicited audio recordings of patients coughing and accompanying information about their conditions via an online website. They collected a dataset of more than 70,000 recordings containing an average of three coughs per patient and an estimated 2,600 patients with a positive case, to date.

Using the COVID-19 cough recordings and an equal number of COVID-19 negative recordings randomly selected from the dataset of 5,320, the researchers developed, trained, and validated a model that listens for specific acoustic biomarkers related to muscular degradation, vocal cord changes, sentiment or mood changes, and changes in the lungs or respiratory tract.

The tool discriminated COVID-19 positive patients with 97.1% accuracy, 98.5% sensitivity, and 94.2% specificity. The model performed at 100% accuracy when detecting coughs from asymptomatic positive cases.

This tool can provide a free, non-invasive, real-time large-scale COVID-10 asymptomatic screening test to augment current approaches, the researchers say. Practical uses include daily screening of students, workers, and the public, or for pool testing to quickly alert groups to outbreaks.

The post AI tool detects COVID-19 by listening to patients’ coughs appeared first on IIOT Connection.

Led by Huanyu “Larry” Cheng, Dorothy Quiggle Career Development Professor in the Penn State Department of Engineering Science and Mechanics, the team published their results in ACS Applied Materials & Interfaces. 

“In this article, we report a simple yet universally applicable fabrication technique with the use of a novel sintering aid layer to enable direct printing for on-body sensors,” said first author Ling Zhang, a researcher in the Harbin Institute of Technology in China and in Cheng’s laboratory. 

Cheng and his colleagues previously developed flexible printed circuit boards for use in wearable sensors, but printing directly on skin has been hindered by the bonding process for the metallic components in the sensor. Called sintering, this process typically requires temperatures of around 572 degrees Fahrenheit (300 degrees Celsius) to bond the sensor’s silver nanoparticles together. 

“The skin surface cannot withstand such a high temperature, obviously,” Cheng said. “To get around this limitation, we proposed a sintering aid layer — something that would not hurt the skin and could help the material sinter together at a lower temperature.”

By adding a nanoparticle to the mix, the silver particles sinter at a lower temperature of about 212 F (100 C). 

“That can be used to print sensors on clothing and paper, which is useful, but it’s still higher than we can stand at skin temperature,” Cheng said, who noted that about 104 F (40 C) could still burn skin tissue. “We changed the formula of the aid layer, changed the printing material and found that we could sinter at room temperature.” 

The room temperature sintering aid layer consists of polyvinyl alcohol paste — the main ingredient in peelable face masks — and calcium carbonate — which comprises eggshells. The layer reduces printing surface roughness and allows for an ultrathin layer of metal patterns that can bend and fold while maintaining electromechanical capabilities. When the sensor is printed, the researchers use an air blower, such as a hair dryer set on cool, to remove the water that is used as a solvent in the ink. 

“The outcome is profound,” Cheng said. “We don’t need to rely on heat to sinter.” 

The sensors are capable of precisely and continuously capturing temperature, humidity, blood oxygen levels and heart performance signals, according to Cheng. The researchers also linked the on-body sensors into a network with wireless transmission capabilities to monitor the combination of signals as they progress. 

The process is also environmentally friendly, Cheng said. The sensor remains robust in tepid water for a few days, but a hot shower will easily remove it. 

“It could be recycled, since removal doesn’t damage the device,” Cheng said. “And, importantly, removal doesn’t damage the skin, either. That’s especially important for people with sensitive skin, like the elderly and babies. The device can be useful without being an extra burden to the person using it or to the environment.” 

Next, the researchers plan to alter the technology to target specific applications as needed, such as a precise on-body sensor network placed to monitor the particular symptoms associated with COVID-19. 

Other contributors include Hongjun Ji, Senpei Xie, Yaoyin Li, Ziheng Ye, Tiesong Lin, Xiangli Liu, Xuesong Leng, Mingyu Li, Pengdong Feng, Jiaheng Zhang and Xing Ma, all of whom are affiliated with the Harbin Institute of Technology; Houbing Huang and Xiaoming Shi, both with the Beijing Institute of Technology; and Ning Yi, with the Penn State Department of Materials Science and Engineering.  

This work was supported by Penn State, the National Science Foundation, the American Chemical Society Petroleum Research Fund, the Shenzhen Science and Technology Program, the Bureau of Industry and Information Technology of Shenzhen and the National Science Foundation of China.

Author: Ashley J. WennersHerron

Posted by D. Lozowski

The post Printing Wearable Sensors Directly onto Skin appeared first on IIOT Connection.

Researchers from the University of Minnesota and M Health Fairview are using artificial intelligence (AI) to detect COVID-19 in chest x-rays of hospitalized patients.

The researchers used 18,000 x-rays from COVID-19 patients and 100,000 x-rays from patients without the disease to develop and train an AI program to discover COVID-19-related patterns in the images.

When patients arrive in the emergency department with suspected COVID-19, it is standard protocol to take a chest x-ray. This program can help physicians learn if a patient has COVID-19 much quicker than traditional testing.

The researchers now plan to tweak the AI program and use it to predict the progression of the disease in different patients.

The post Researchers use AI to diagnose COVID-19 in chest x-rays appeared first on IIOT Connection.

Leandro Pecchia, PhD, associate professor of biomedical engineering at the University of Warwick, Coventry, UK, has been awarded £13 million (nearly $17 million) for the ODIN project.

The project will explore the use of robots and artificial intelligence (AI) to ease pressures on hospitals during recovery from COVID-19 and future disasters.

Dr Pecchia has identified 11 hospital challenges the project will take on, using robotics, Internet of Things (IoT), and artificial intelligence (AI).

The interventions will be piloted in six top hospitals in Europe and will span from clinical to logistic procedures, including patient management, medical device and PPE management, disaster preparedness, and hospital resiliency.

Dr Pecchia and his team also will work with three medical device manufacturers–Samsung, Philips, and Medtronic–and seven other enterprises.

The post AI, robots to transform hospitals’ resilience to COVID-19, future disasters appeared first on IIOT Connection.

By redefining their care process and the ways providers make themselves available, patients are a driving force for much of this change. Self-managed care is a growing requirement, with more than 50 percent of patients expecting providers to have digital capabilities according to Accenture’s 2019 Digital Health Consumer Survey.

Read the full article here.

The post Embracing New Technologies for Patient Care appeared first on IIOT Connection.

The National Institutes of Health (NIH) on August 5 announced the launch of the Medical Imaging and Data Resource Center, which will create new tools using artificial intelligence (AI) and medical imaging to diagnose and personalize therapies for COVID-19 patients.

The Center will build a large repository of COVID-19 chest images so that researchers can evaluate lung and cardiac tissue data, ask critical research questions, and develop predictive COVID-19 imaging signatures.

A major challenge is to rapidly and accurately identify these signatures and evaluate this information in combination with other clinical symptoms and tests.

The goals of the Center are to lead the development and implementation of new diagnostics, including machine learning algorithms, that will allow rapid and accurate assessment of the patient's COVID-19 disease status and help physicians optimize treatment.

The post NIH harnesses power of AI for COVID-19 diagnosis, treatment appeared first on IIOT Connection.

The use of an automated web-based symptom monitoring tool as part of Maine’s COVID-19 contact tracing program made the state’s contact tracing and monitoring faster and more efficient.

The tool was well received, with the majority of monitored contacts (96.4%) agreeing to the automated system. Contacts automatically received daily symptom questionnaires via their choice of e-mailed weblink, test message, texted weblink, or telephone call until they completed their quarantine.

The system promptly identified COVID-19 in the monitored contacts, with 190 (11.7%) of 1,622 developing COVID-19.

Contacts who refused automated monitoring or could not be enrolled because of language barriers were monitored using direct monitoring by the contact tracing team.

Automated monitoring tools can augment traditional contact tracing, but they can't take the place of a large, trained public health workforce needed for a COVID-19 response, the authors say.

The post Automated monitoring tool facilitates contact tracing of COVID-19 patients appeared first on IIOT Connection.

The Curial AI test, an artificial intelligence (AI) program developed at the University of Oxford, UK, can identify COVID-19 within 1 hour of a patient arriving at an emergency department (ED), the July 31 Belfast Telegraph reports.

The AI test analyzes patient data, such as blood tests and vital signs gathered in the ED, to determine the chance of a patient testing positive for COVID-19.

The AI program has been tested on data from 115,000 ED patient visits and has a more than 90% accuracy rate.

The post AI program can detect COVID-19 in 1 hour appeared first on IIOT Connection.

The Joint Cybersecurity Advisory said that APT29, which is also known as "the Dukes" or "Cozy Bear," is "almost certainly part of the Russian intelligence services" and is using custom malware that is "highly likely" being used "with the intention of stealing information and intellectual property relating to the development and testing of COVID-19 vaccines."

The advisory also said that the U.S. National Security Agency agrees that APT29 is behind the espionage. It also said the espionage campaign will likely continue.

"APT29 is likely to continue to target organizations involved in COVID-19 vaccine research and development, as they seek to answer additional intelligence questions relating to the pandemic," the Joint Cybersecurity Advisory concluded.

Adam Schiff (D-Calif.), chairman of the U.S. House Intelligence Committee, issued a statement saying the committee has asked for briefings on the latest Russian espionage but also pointed out that President Trump has yet to "condemn" Russian leader Vladimir Putin for any of Russia's actions against the U.S. and its allies, including interference in the 2016 U.S. presidential election and poisoning of Russian dissidents in democratic countries.

"The only question remaining is whether Donald Trump will condemn this latest aggression by Putin's Russia, and if not, why not?" Schiff stated.

The post U.S., U.K., Canada Say Russian Intelligence Targeting COVID-19 Vaccine Development appeared first on IIOT Connection.