Title: Are High-Tech Blood Pressure Monitors Really Worth It?
Category: Health News
Created: 8/16/2022 12:00:00 AM
Last Editorial Review: 8/16/2022 12:00:00 AM

Background:

Continuous glucose monitoring (CGM) for patients with type 1 and type 2 diabetes is associated with improved clinical, behavioral, and psychosocial patient health outcomes and is part of the American Diabetes Association’s Standards of Medical Care. CGM prescription often takes place in endocrinology practices, yet 50% of adults with type 1 diabetes and 90% of all people with type 2 diabetes receive their diabetes care in primary care settings. This study examined primary care clinicians’ perceptions of barriers and resources needed to support CGM use in primary care.

Sleep is a fundamental feature of life for virtually all multicellular animals, but many questions remain about how sleep is regulated and what biological functions it plays. Substantial headway has been made in the study of both circadian rhythms and sleep in the fruit fly Drosophila melanogaster, much of it through studies of individual fly activity using beam break counts from Drosophila activity monitors (DAMs). The number of laboratories worldwide studying sleep in Drosophila has grown from only a few 20 years ago to hundreds today. The utility of these studies is limited by the quality of the metrics that can be extracted from the data. Many software options exist to help analyze DAM data; however, these are often expensive or have significant limitations. Therefore, we describe here a method for analyzing DAM-based data using the sleep and circadian analysis MATLAB program (SCAMP). This user-friendly software has an advantage of combining several analyses of both sleep and circadian rhythms in one package and produces graphical outputs as well as spreadsheets of the outputs for further statistical analysis. The version of SCAMP described here is also the first published software package that can analyze data from multibeam DAM5Ms, enabling determination of positional preference over time.

The positional preference of an animal can be very informative regarding the choices it makes about how to interact with its environment. The fruit fly Drosophila melanogaster has been used as a robust system for examining neurobiological mechanisms underlying behavior. Fruit fly positional preference can be gathered from TriKinetics Drosophila activity monitors (DAMs), which contain four infrared beams, allowing for tracking the position of individual flies along the length of a tube. Here, we describe a method for using DAM5Ms to examine food preference. Specifically, we show an example in which circadian changes in food preference are compared between different Drosophila species. More information about the evolution of behavior can be gathered by measuring feeding preference relative to time of day. Noni, fruit from Morinda citrifolia, contains octanoic acid, a chemical toxic to many species of Drosophila. D. melanogaster and D. simulans, both food generalists, show high sensitivity to octanoic acid, whereas D. sechellia, a specialist, can tolerate high concentrations. When two different food substrates are provided at each end of a tube, food preference can be inferred at various times of the day, using the sleep and circadian analysis MATLAB program (SCAMP) to extract and analyze positional data from DAM5Ms. Data gathered from these analyses can be used to compare avoidance or attraction to nutrients, tastants, or odors between species and genotypes or after specific different treatments. Additionally, such data can be examined as a function of time of day.

Sleep is a fundamental feature of life for virtually all multicellular animals, but many questions remain about how sleep is regulated by circadian rhythms, homeostatic sleep drive that builds up with wakefulness, and modifying factors such as hunger or social interactions, as well as about the biological functions of sleep. Substantial headway has been made in the study of both circadian rhythms and sleep in the fruit fly Drosophila melanogaster, much of it through studies of individual fly activity using Drosophila activity monitors (DAMs). Here, we describe approaches for the activation of specific neurons of interest using optogenetics (involving genetic modifications that allow for light-based neuronal activation) and thermogenetics (involving genetic modifications that allow for temperature-based neuronal activation) so that researchers can evaluate the roles of those neurons in controlling rest and activity behavior. In this protocol, we describe how to set up a rig for simultaneous optogenetic or thermogenetic stimulation and activity monitoring for analysis of sleep and circadian rhythms in Drosophila, how to raise appropriate flies, and how to perform the experiment. This protocol will allow researchers to assess the causative role in the regulation of sleep and activity rhythms of any genetically tractable subset of cells.

Sleep is important for survival, and the need for sleep is conserved across species. In the past two decades, the fruit fly Drosophila melanogaster has emerged as a promising system in which to study the genetic, neural, and physiological bases of sleep. Through significant advances in our understanding of the regulation of sleep in flies, the field is poised to address several open questions about sleep, such as how the need for sleep is encoded, how molecular regulators of sleep are situated within brain networks, and what the functions of sleep are. Here, we describe key findings, open questions, and commonly used methods that have been used to inform existing theories and develop new ways of thinking about the function, regulation, and adaptability of sleep behavior.

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Los Angeles CA (SPX) Nov 09, 2024
Data from NISAR will improve our understanding of such phenomena as earthquakes, volcanoes, and landslides, as well as damage to infrastructure. Earth's surface is in a state of continuous motion, although often unnoticed. Scientists have utilized satellite and ground-based technology to observe movements linked to geological events such as earthquakes, landslides, and volcanic activity. A

This article is part of our exclusive IEEE Journal Watch series in partnership with IEEE Xplore.

Sea turtles are remarkable creatures for a number of reasons, including the way they hear underwater—not through openings in the form of ears, but by detecting vibrations directly through the skin covering their auditory system. Inspired by this ability to detect sound through skin, researchers in China have created a heart-monitoring system, which initial tests in humans suggest may be a viable for monitoring heartbeats.

A key way in which doctors monitor heart health involves “listening” to the heartbeat, either using a stethoscope or more sophisticated technology, like echocardiograms. However, these approaches require a visit to a specialist, and so researchers have been keen to develop alternative, lower cost solutions that people can use at home, which could also allow for more frequent testing and monitoring.

Junbin Zang, a lecturer at the North University of China, and his colleagues specialize in creating heart-monitoring technologies. Their interest was piqued when they learned about the inner workings of the sea turtle’s auditory system, which is able to detect low-frequency signals, especially in the 300- to 400-hertz range.

“Heart sounds are also low-frequency signals, so the low-frequency characteristics of the sea turtle’s ear have provided us with great inspiration,” explains Zang.

At a glance, it looks like turtles don’t have ears. Their auditory system instead lies under a layer of skin and fat, through which it picks up vibrations. As with humans, a small bone in the ear vibrates as sounds hit it, and as it oscillates, those pulses are converted to electrical signals that are sent to the brain for processing and interpretation.

iStock

But sea turtles have a unique, slender T-shaped conduit that encapsulates their ear bones, restricting the movement of the similarly T-shaped ear bones to only vibrate in a perpendicular manner. This design provides their auditory system with high sensitivity to vibrations.

Zang and his colleagues set out to create a heart monitoring system with similar features. They created a T-shaped heart-sound sensor that imitates the ear bones of sea turtles using a tiny MEMS cantilever beam sensor. As sound hits the sensor, the vibrations cause deformations in its beam, and the fluctuations in the voltage resistance are then translated into electrical signals.

The researchers first tested the sensor’s ability to detect sound in lab tests, and then tested the sensor’s ability to monitor heartbeats in two human volunteers in their early 20s. The results, described in a study published 1 April in IEEE Sensors Journal, show that the sensor can effectively detect the two phases of a heartbeat.

“The sensor exhibits excellent vibration characteristics,” Zang says, noting that it has a higher vibration sensitivity compared to other accelerometers on the market.

However, the sensor currently picks up a significant amount of background noise, which Zang says his team plans to address in future work. Ultimately, they are interested in integrating this novel bioinspired sensor into devices they have previously created—including portable handheld and wearable versions, and a relatively larger version for use in hospitals—for the simultaneous detection of electrocardiogram and phonocardiogram signals.

This article appears in the July 2024 print issue as “Sea Turtles Inspire Heart-Monitor Design.”

For people with diabetes, glucose monitors are a valuable tool to monitor their blood sugar. The current generation of these biosensors detect glucose levels with thin, metallic filaments inserted in subcutaneous tissue, the deepest layer of the skin where most body fat is stored.

Medical technology company Biolinq is developing a new type of glucose sensor that doesn’t go deeper than the dermis, the middle layer of skin that sits above the subcutaneous tissue. The company’s “intradermal” biosensors take advantage of metabolic activity in shallower layers of skin, using an array of electrochemical microsensors to measure glucose—and other chemicals in the body—just beneath the skin’s surface.

Biolinq just concluded a pivotal clinical trial earlier this month, according to CEO Rich Yang, and the company plans to submit the device to the U.S. Food and Drug Administration for approval at the end of the year. In April, Biolinq received US $58 million in funding to support the completion of its clinical trials and subsequent submission to the FDA.

Biolinq’s glucose sensor is “the world’s first intradermal sensor that is completely autonomous,” Yang says. While other glucose monitors require a smartphone or other reader to collect and display the data, Biolinq’s includes an LED display to show when the user’s glucose is within a healthy range (indicated by a blue light) or above that range (yellow light). “We’re providing real-time feedback for people who otherwise could not see or feel their symptoms,” Yang says. (In addition to this real-time feedback, the user can also load long-term data onto a smartphone by placing it next to the sensor, like Abbott’s FreeStyle Libre, another glucose monitor.)

More than 2,000 microsensor components are etched onto each 200-millimeter silicon wafer used to manufacture the biosensors.Biolinq

Biolinq’s hope is that its approach could lead to sustainable changes in behavior on the part of the individual using the sensor. The device is intentionally placed on the upper forearm to be in plain sight, so users can receive immediate feedback without manually checking a reader. “If you drink a glass of orange juice or soda, you’ll see this go from blue to yellow,” Yang explains. That could help users better understand how their actions—such as drinking a sugary beverage—change their blood sugar and take steps to reduce that effect.

Biolinq’s device consists of an array of microneedles etched onto a silicon wafer using semiconductor manufacturing. (Other glucose sensors’ filaments are inserted with an introducer needle.) Each chip has a small 2-millimeter by 2-millimeter footprint and contains seven independent microneedles, which are coated with membranes through a process similar to electroplating in jewelry making. One challenge the industry has faced is ensuring that microsensors do not break at this small scale. The key engineering insight Biolinq introduced, Yang says, was using semiconductor manufacturing to build the biosensors. Importantly, he says, silicon “is harder than titanium and steel at this scale.”

Miniaturization allows for sensing closer to the surface of the skin, where there is a high level of metabolic activity. That makes the shallow depth ideal for monitoring glucose, as well as other important biomarkers, Yang says. Due to this versatility, combined with the use of a sensor array, the device in development can also monitor lactate, an important indicator of muscle fatigue. With the addition of a third data point, ketones (which are produced when the body burns fat), Biolinq aims to “essentially have a metabolic panel on one chip,” Yang says.

Using an array of sensors also creates redundancy, improving the reliability of the device if one sensor fails or becomes less accurate. Glucose monitors tend to drift over the course of wear, but with multiple sensors, Yang says that drift can be better managed.

One downside to the autonomous display is the drain on battery life, Yang says. The battery life limits the biosensor’s wear time to 5 days in the first-generation device. Biolinq aims to extend that to 10 days of continuous wear in its second generation, which is currently in development, by using a custom chip optimized for low-power consumption rather than off-the-shelf components.

The company has collected nearly 1 million hours of human performance data, along with comparators including commercial glucose monitors and venous blood samples, Yang says. Biolinq aims to gain FDA approval first for use in people with type 2 diabetes not using insulin and later expand to other medical indications.

This article appears in the August 2024 print issue as “Glucose Monitor Takes Page From Chipmaking.”

Emteq Labs wants eyewear to be the next frontier of wearable health technology.

The Brighton, England-based company introduced today its emotion-sensing eyewear, Sense. The glasses contain nine optical sensors distributed across the rims that detect subtle changes in facial expression with more than 93 percent accuracy when paired with Emteq’s current software. “If your face moves, we can capture it,” says Steen Strand, whose appointment as Emteq’s new CEO was also announced today. With that detailed data, “you can really start to decode all kinds of things.” The continuous data could help people uncover patterns in their behavior and mood, similar to an activity or sleep tracker.

Emteq is now aiming to take its tech out of laboratory settings with real-world applications. The company is currently producing a small number of Sense glasses, and they’ll be available to commercial partners in December.

The announcement comes just weeks after Meta and Snap each unveiled augmented reality glasses that remain in development. These glasses are “far from ready,” says Strand, who led the augmented reality eyewear division while working at Snap from 2018 to 2022. “In the meantime, we can serve up lightweight eyewear that we believe can deliver some really cool health benefits.”

Fly Vision Vectors

While current augmented reality (AR) headsets have large battery packs to power the devices, glasses require a lightweight design. “Every little bit of power, every bit of weight, becomes critically important,” says Strand. The current version of Sense weighs 62 grams, slightly heavier than the Ray-Ban Meta smart glasses, which weigh in at about 50 grams.

Because of the weight constraints, Emteq couldn’t use the power-hungry cameras typically used in headsets. With cameras, motion is detected by looking at how pixels change between consecutive images. The method is effective, but captures a lot of redundant information and uses more power. The eyewear’s engineers instead opted for optical sensors that efficiently capture vectors when points on the face move due to the underlying muscles. These sensors were inspired by the efficiency of fly vision. “Flies are incredibly efficient at measuring motion,” says Emteq founder and CSO Charles Nduka. “That’s why you can’t swat the bloody things. They have a very high sample rate internally.”

Sense glasses can capture data as often as 6,000 times per second. The vector-based approach also adds a third dimension to a typical camera’s 2D view of pixels in a single plane.

These sensors look for activation of facial muscles, and the area around the eyes is an ideal spot. While it’s easy to suppress or force a smile, the upper half of our face tends to have more involuntary responses, explains Nduka, who also works as a plastic surgeon in the United Kingdom. However, the glasses can also collect information about the mouth by monitoring the cheek muscles that control jaw movements, conveniently located near the lower rim of a pair of glasses. The data collected is then transmitted from the glasses to pass through Emteq’s algorithms in order to translate the vector data into usable information.

In addition to interpreting facial expressions, Sense can be used to track food intake, an application discovered by accident when one of Emteq’s developers was wearing the glasses while eating breakfast. By monitoring jaw movement, the glasses detect when a user chews and how quickly they eat. Meanwhile, a downward-facing camera takes a photo to log the food, and uses a large language model to determine what’s in the photo, effectively making food logging a passive activity. Currently, Emteq is using an instance of OpenAI’s GPT-4 large language model to accomplish this, but the company has plans to create their own algorithm in the future. Other applications, including monitoring physical activity and posture, are also in development.

One Platform, Many Uses

Nduka believes Emteq’s glasses represent a “fundamental technology,” similar to how the accelerometer is used for a host of applications in smartphones, including managing screen orientation, tracking activity, and even revealing infrastructure damage.

Similarly, Emteq has chosen to develop the technology as a general facial data platform for a range of uses. “If we went deep on just one, it means that all the other opportunities that can be helped—especially some of those rarer use cases—they’d all be delayed,” says Nduka. For example, Nduka is passionate about developing a tool to help those with facial paralysis. But a specialized device for those patients would have high unit costs and be unaffordable for the target user. Allowing more companies to use Emteq’s intellectual property and algorithms will bring down cost.

In this buckshot approach, the general target for Sense’s potential use cases is health applications. “If you look at the history of wearables, health has been the primary driver,” says Strand. The same may be true for eyewear, and he says there’s potential for diet and emotional data to be “the next pillar of health” after sleep and physical activity.

How the data is delivered is still to be determined. In some applications, it could be used to provide real-time feedback—for instance, vibrating to remind the user to slow down eating. Or, it could be used by health professionals only to collect a week’s worth of at-home data for patients with mental health conditions, which Nduka notes largely lack objective measures. (As a medical device for treatment of diagnosed conditions, Sense would have to go through a more intensive regulatory process.) While some users are hungry for more data, others may require a “much more gentle, qualitative approach,” says Strand. Emteq plans to work with expert providers to appropriately package information for users.

Interpreting the data must be done with care, says Vivian Genaro Motti, an associate professor at George Mason University who leads the Human-Centric Design Lab. What expressions mean may vary based on cultural and demographic factors, and “we need to take into account that people sometimes respond to emotions in different ways,” Motti says. With little regulation of wearable devices, she says it’s also important to ensure privacy and protect user data. But Motti raises these concerns because there is a promising potential for the device. “If this is widespread, it’s important that we think carefully about the implications.”

Privacy is also a concern to Edward Savonov, a professor of electrical and computer engineering at the University of Alabama, who developed a similar device for dietary tracking in his lab. Having a camera mounted on Emteq’s glasses could pose issues, both for the privacy of those around a user and a user’s own personal information. Many people eat in front of their computer or cell phone, so sensitive data may be in view.

For technology like Sense to be adopted, Sazonov says questions about usability and privacy concerns must first be answered. “Eyewear-based technology has potential for a great future—if we get it right.”

Pending post verification are claims that total $279 million for the March-May 2007 period. The areas of greatest concern to us include costs for helicopter operations ($83 million annually), radar maintenance ($65 million annually) and Joint Staff operations ($5 million annually).

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