Tag: COVID

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Asthma COVID 19 Sensors

Chest sensor detects worsening asthma, respiratory disease

The RESP Sensor from Strados labs received FDA clearance for early, remote detection of lung acoustic and ventilation pattern changes to predict worsening respiratory disease.

Lung sounds associated with asthma, COPD, heart failure and infectious diseases including COVID-19 are detected.

Frequency of wheezing, coughing, shortness of breath, and respiratory dynamics including rate and excursion are collected and anlyzed using a noninvasive chest sensor and cloud platform.

Individuals can monitor themselves at home, and the data can be integrated into telehealth, tele ICU, clinical trial management platforms and telemetry systems.

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COVID 19 Sensors

Sensors monitor physiological variables post vaccine

Wearable sensors could improve clinical trials by enabling earlier identification of abnormal reactions. Currently, vaccine safety in clinical trials is primarily determined by participants’ subjective self-reporting.

Dan Yamin, Yiftach Gepner, and Tel Aviv University colleagues used a chest patch sensor to monitor various health indicators in 160 participants, before and after receiving the Pfizer BioNTech COVID 19 vaccine. Participants also self-reported using a mobile phone app.

Significant changes in health indicators following vaccine administration were detected by the chest patch sensor in participants who did and did not report changes. Three days following vaccination, participant health indicators returned to the levels observed the day before vaccination in both groups.

Click to view Tel Aviv University video

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COVID 19 Sensors

Hopkins developed saliva sensor improves speed and accuracy of COVID detection

David Gracias and Ishan Barman at Johns Hopkins have developed a COVID 19 sensor which provides fast and accurate results using a drop of saliva placed on a device. No additional chemical modifications like molecular labeling or antibody functionalization are required, which could allow the sensor to be used in wearable devices.

Current PCR tests are highly accurate, but require complicated sample preparation, with results taking hours or even days to process in a laboratory. Rapid tests are less successful at detecting early infections and asymptomatic cases and can lead to erroneous results.

The Gracias/Barman developed sensor is nearly as sensitive as a PCR test and as convenient as a rapid antigen test. In a study, the sensor demonstrated 92% accuracy at detecting SARS-COV-2 in saliva samples—comparable to that of PCR tests. It was also highly successful at rapidly determining the presence of other viruses, including H1N1 and Zika.

The sensor material can be placed on any type of surface, from doorknobs and building entrances to masks and textiles, or potentially be integrated with a hand-held testing device for fast screenings at crowded places like airports or stadiums.

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Biomarkers

Blood test distinguishes bacterial vs viral infections in 15 minutes

MeMed BV is a blood test which uses the body’s immune response to distinguish between bacterial and viral infections. It does not detect the cause of an infection — instead it analyzes the “host response,” measuring levels of three proteins that appear differently, depending on whether the immune system is fighting a virus or bacteria. Results appear within 15 minutes.

Used to rapidly treat patients properly, only using antibiotics when appropriate, the test, which recently received FDA approval and will be used in emergency rooms, is a potential breakthrough.

MeMed also has received CE clearance for a COVID severity test, which can provide an early indication of deterioration and predict disease progression and recovery.

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AI Covid-19

AI detects COVID in chest x rays

DeepCOVID-XR is a Northwestern University developed algorithm that automatically detects the signs of COVID-19 on a basic X-ray of the lungs. The system is able to detect COVID-19 in X-rays 10 times faster than thoracic radiologists and 1% to 6% more accurately.

The developers said the AI could be used to rapidly screen patients at hospital admission, and trigger protocols to help protect healthcare workers.

Accoring to Professor Aggelos Katsaggelos, the alorithm will not replace testing, but will enable the use of cheap, routine, safe x-rays to determine if a patient needs to be isolated.

In 17,000 X-ray images, the algorithm identified lungs which appeared patchy and hazy, as air sacs became inflamed and filled with fluid instead of air, which is common in COVID-19.

When put up against five experienced, fellowship-trained radiologists, DeepCOVID-XR was able to process a set of 300 test X-rays in about 18 minutes, compared to about two and a half to three and a half hours. The AI also delivered an accuracy rate of 82%, about on par with the group’s range of 76% to 81%.

“Radiologists are expensive and not always available,” Katsaggelos said. “X-rays are inexpensive and already a common element of routine care. This could potentially save money and time—especially because timing is so critical when working with COVID-19.”

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Covid-19 Sensors Wearables

Presymptomatic COVID detection with wearables

Stanford’s Michael Snyder and colleagues have used smartwatch data to detect early, presymptomatic COVID-19 in 31 individuals out of a cohort of 5,000.

They demonstrated that COVID-19 infections are associated with alterations in heart rate, steps and sleep in 80% of cases. Physiological alterations were detected prior to, or at, symptom onset in 85% of the positive cases, in some cases nine or more days before symptoms.

A method to detect onset of COVID-19 infection in real-time was developed, which detected 67% of infection cases at or before symptom onset.

The study intends to provide a roadmap to a rapid and universal diagnostic method for the large-scale detection of respiratory viral infections in advance of symptoms.

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Click to view Professor Snyder’s talk at the 2019 ApplySci conference at Stanford.

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Covid-19 Sensors

Single sensor could simultaneously detect, differentiate between flu, coronavirus

University of Texas professor Deji Akinwande is developing a graphene sensor that can tell the difference between flu and coronavirus, and test for both simultaneously. The goal is to save time, medical resources, and cost, and speed appropriate treatment, as a second COVID wave could correspond with the next flu season.

The sensor is the size of a micro USB drive and is infused with antibodies of both COVID-19 and influenza. One part of the device is sensitive only to the flu, while another part will react only to the coronavirus.

The researchers will use inactive samples of COVID-19 and influenza for initial testing, and will measure how he sensor connects with the coronavirus’s spike proteins, which help it enter human cells by binding with them.

The work builds on the team‘s previous iron deficiency detecting graphene sensor work. “It became clear that just by changing the antibody, we could pivot the platform to focus on the coronavirus,” Akinwande said.

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3-D Printing Covid-19 Sensors

Sensors 3D printed directly on lungs, heart could be used with surgical robots to diagnose, monitor disease

Michael McAlpine and University of Minnesota colleagues used 3D printing and motion capture technology to print electronic sensors directly on organs that are expanding and contracting, such as the heart and lungs. This could be used to diagnose and monitor the lungs of patients with COVID-19.

This builds on the team’s technique which enabled the printing of electronics directly on the skin of a hand that moved left to right or rotated.

They used a balloon-like surface and a specialized 3D printer, with motion capture tracking markers to help the 3D printer adapt its printing path to the expansion and contraction movements on the surface. An animal lung in the lab was artificially inflated and a soft hydrogel-based sensor was printed directly on the surface.

According to McAlpine, “the broader idea behind this research, is that this is a big step forward to the goal of combining 3D printing technology with surgical robots. In the future, 3D printing will not be just about printing but instead be part of a larger autonomous robotic system. This could be important for diseases like COVID-19 where health care providers are at risk when treating patients.”