Hackensack Meridian Health, Maimonides Medical Center piloting sensor-embedded clothing for COVID-19 patients

The research collaboration with Hackensack and Maimonides involves Nanowear's adjustable undergarment that enables physicians to remotely capture and assess multiple physiological signals. (Nanowear)

Two New York City metro health systems are collaborating with a startup to research the use of sensor-embedded clothing to monitor COVID-19 patients.

New Jersey-based Hackensack Meridian Health Systems and Maimonides Medical Center in Brooklyn, New York are working with Nanowear to use clinical-grade wearable technology—an undershirt with embedded nanosensors—to detect physiological and biomarker changes with patients either confirmed or suspected to have COVID-19.

Nanowear's sensors can detect changes indicative of clinical deterioration that may require further intervention from the hospital systems, according to the company. In 2016, the New York City-based startup received clearance from the Food and Drug Administration (FDA) for its SimplECG, a remote cardiac monitoring undergarment. 

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The research collaboration with Hackensack and Maimonides involves Nanowear's SimpleSENSE technology, a one-size-fits-all adjustable undergarment that enables physicians to remotely capture and assess multiple physiological signals – including real-time ECG, systolic and diastolic blood pressure, blood flow hemodynamics, respiration, lung volume and fluid, and temperature trends.

RELATED: Providence St. Joseph using Twistle remote monitoring technology for 700 COVID patients

The technology captures these signals without the need for an in-person visit or physical touch.

The technology is not yet FDA-cleared. The startup has submitted its SimpleSENSE device and mobile platform to the FDA for Class II 510(k) clearance.

“When we talk about telemedicine, we often talk about video conferencing. But to truly enable remote diagnostics we must incorporate clinical-grade remote monitoring that is affordable, comfortable, and simple for patients to use," said Venk Varadan, Nanowear co-founder and CEO in a statement. 

Many healthcare organizations are researching the use of wearable technology to monitor COVID-19 patients or to use sensors to diagnosis the virus. Geisinger Health System and Providence St. Joseph Health stood up remote monitoring programs for COVID patients.

Stanford Medicine is exploring the use of wearable data to detect the early onset of infectious diseases, including COVID.

Nanowear’s sensor-embedded undergarment replaces a stethoscope, blood pressure cuff, multi-channel Holter monitor, and Capnogram (End-tidal CO2), providing a diagnostic quality monitoring system in a form factor that is easy to ship, easy to wear, and easy for the patient to use, Varadan said.

Nanowear’s garment captures 120 million data points per patient per day across cardiac, pulmonary, and circulatory biomarker data, which is transmitted to clinical staff, so that they may make informed and quicker decisions remotely, the company said.

As New York City emerges from coronavirus lockdown, health systems are looking for novel technologies to better understand and combat the unprecedented severity of COVID-19. 

Nanowear’s remote monitoring technology gives physicians an "exponential amount of relevant data metrics about the heart and lungs from an all-in-one product" that should ultimately enable providers to triage lower-risk patients and stratify high-risk patients, according to Sameer Jamal, M.D., a cardiologist at Hackensack Meridian Health.

RELATED: A look inside Geisinger's new remote monitoring program for COVID-19 patients

“What we need to understand about COVID-19 is why certain patients develop a cytokine-mediated immune response from the virus,” said Jamal, who also is the national principal investigator of the research collaboration.

"This resulting inflammation within the circulatory system often leads to severe complications or death, which we have seen first-hand in New York City and the surrounding area. Diagnosis and co-morbidities alone is not enough to determine risk to admitted patients before they need to be transferred to ICU," Jamal said.

Varadan invented the cloth-based nanotechnology in 2013 with founding engineers Pratyush Rai, Ph.D., Prashanth Shyam Kumar, Mouli Ramasamy and Gyanesh Mathur, Ph.D.

A year later, the group launched the company as an early-stage developer of cloth-based diagnostic monitoring nanosensor technology.

In 2018, the company was one of seven medical technology companies selected for Google's Launchpad Studio accelerator program.

The venture-backed company has raised $3.6 million to date, according to Pitchbook.

RELATED: Stanford Medicine is using data and digital tools to predict the next COVID-19 surge

The COVID-19 pandemic has transformed healthcare delivery and diagnosis, according to the company.

"The COVID-19 paradigm shift has accelerated healthcare systems’ need to implement staff-contactless monitoring involving acute and chronic disease-related hospitalizations,” said John Marshall, M.D., head of the emergency department at Maimonides Medical Center, in a statement.

“The continuity of in-patient monitoring, patient-to-home monitoring, and at-home monitoring across 8-10 biomarkers with a very easy-to-use product is what makes Nanowear's solution compelling and unique," he said.

Unlike consumer-grade wearable garments, smartwatches, smart rings, or limited-metric adhesive patches, Nanowear’s textile-embedded nanosensors are clinical-grade, analyzing multiple cardiac, pulmonary, and circulatory biomarkers, creating a holistic personalized digital signature for each patient, according to the company.

“With billions of touchpoints per centimeter and large vectors across the heart and lungs, Nanowear’s skin-to-impedance barrier is lower than other wearable sensors, resulting in location-agnostic, high signal-to-noise raw data from basic skin contact," said Suraj Kapa, M.D., director of augmented and virtual reality innovation at Mayo Clinic.

"The breadth of metrics, quality and quantity of data, and comfortable user experience are key for machine learning algorithms in various diagnostic verticals, even beyond healthcare," Kapa said.

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