Remoticon 2021 // Debra Ansell Connects PCB In Ways You Didn’t Expect

“LEDs improve everything.” Words to live by. Most everything that Debra Ansell of [GeekMomProjects] makes is bright, bold, and blinky. But if you’re looking for a simple string of WS2812s, you’re barking up the wrong tree. In the last few years, Debra has been making larger and more complicated assemblies, and that has meant diving into the mechanical design of modular PCBs. In the process Debra has come up with some great techniques that you’ll be able to use in your own builds, which she shared with us in a presentation during the 2021 Hackaday Remoticon.

She starts off with a quick overview of the state of play in PCB art, specifically of the style that she’s into these days: three dimensional constructions where the physical PCB itself is a sculptural element of the project. She’s crossing that with the popular triangle-style wall hanging sculpture, and her own fascination with “inner glow” — side-illuminated acrylic diffusers. Then she starts taking us down the path of creating her own wall art in detail, and this is where you need to listen up. Continue reading “Remoticon 2021 // Debra Ansell Connects PCB In Ways You Didn’t Expect”

flow chart for Assessment of the Feasibility of Using Noninvasive Wearable Biometric Monitoring Sensors to Detect Influenza and the Common Cold Before Symptom Onset paper

Wearables Can Detect The Flu? Well…Maybe…

Surprisingly there are no pre-symptomatic screening methods for the common cold or the flu, allowing these viruses to spread unbeknownst to the infected. However, if we could detect when infected people will get sick even before they were showing symptoms, we could do a lot more to contain the flu or common cold and possibly save lives. Well, that’s what this group of researchers in this highly collaborative study set out to accomplish using data from wearable devices.

Participants of the study were given an E4 wristband, a research-grade wearable that measures heart rate, skin temperature, electrodermal activity, and movement. They then wore the E4 before and after inoculation of either influenza or rhinovirus. The researchers used 25 binary, random forest classification models to predict whether or not participants were infected based on the physiological data reported by the E4 sensor. Their results are pretty lengthy, so I’ll only highlight a few major discussion points. In one particular analysis, they found that at 36 hours after inoculation their model had an accuracy of 89% with a 100% sensitivity and a 67% specificity. Those aren’t exactly world-shaking numbers, but something the researchers thought was pretty promising nonetheless.

One major consideration for the accuracy of their model is the quality of the data reported by the wearable. Namely, if the data reported by the wearable isn’t reliable itself, no model derived from such data can be trustworthy either. We’ve discussed those points here at Hackaday before. Another major consideration is the lack of a control group. You definitely need to know if the model is simply tagging everyone as “infected” (which specificity does give us an idea of, to be fair) and a control group of participants who have not been inoculated with either virus would be one possible way to answer that question. Fortunately, the researchers admit this limitation of their work and we hope they will remedy this in future studies.

Studies like this are becoming increasingly common and the ongoing pandemic has motivated these physiological monitoring studies even further. It seems like wearables are here to stay as the academic research involving these devices seems to intensify each day. We’d love to see what kind of data could be obtained by a community-developed device, as we’ve seen some pretty impressive DIY biosensor projects over the years.

Comfortable, wearable packaging for biometric device for monitoring physiological data and pushing the data to the cloud

A DIY Biometric Device With Some Security Considerations

Biohacking projects are not new to Hackaday and it’s certainly a genre that really piques our interest. Our latest biohacking device comes courtesy of [Manivannan] who brings his flavor of a wearable biosensor with some security elements built-in through AWS.

The hardware is composed of some impressive components we have seen. He has an AD8232 electrocardiogram front end, the MAX30102 integrated pulse oximeter IC for determining blood oxygen and heart rate, and the ever-popular LM35 for measuring body temperature. Either of these chips would be perfect for your next DIY biosensor project though you might try the MAX30205 body temperature sensor given its 0.1-degree Celsius accuracy. However, what really piqued our interest was the use of Microchip’s AVR-IoT WA Development Board. Now we’ve talked about this board before and also mentioned you could probably do all the same things with an ESP-device, but perhaps now we get to see the board a bit more in action.

[Manivannan] walks the reader through the board’s setup and everything looks to be pretty straightforward. He ultimately rigged together a very primitive dashboard for viewing all his vitals in real-time, demonstrating how you could put together your own patient dashboard for remote monitoring of vitals or other sensor signals. He emphasizes that all this is powered through AWS, giving him some added security layers that are critical for protecting his data from unwanted viewers.

Though [Manivannan’s] security implementation doesn’t rise to the standard of medical devices, maybe it will serve as a case study in the growing open-source medical device movement.

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An NFC Antenna Ring With A Chip As Its Jewel

Contactless payment by means of NFC-enabled bank cards has made our everyday transactions far more convenient over the last decade, but there still remains the tedious task of finding the card and waving it over the reader. Maybe embedded chips are a step too far for many of us, but how about a bank card in a wearable such as a ring? [Jonathan Limén] shows us how, by taking the NFC chip module from a bank card and mounting it on a ring with a wire coil antenna embedded within it.

The chip in a bank card comes mounted on a small thin PCB with contacts on one side and a coil on the other that serves as its antenna. It’s not sensitive enough to work reliably with most card readers, so the card incorporates a separate printed circuit layer that forms a large-sized tuned circuit which couples to the chip antenna. After taking us through the removal of the chip from the card with some acetone, he proceeds to create a replacement for the card antenna by winding a wire coil round the ring. This becomes a trial-and-error process, but in the end, the result is a working NFC payment ring.

We quite like this idea, but would be tempted to both take away some of the trial and error with a vector network analyzer, and run a couple of turns of the wire as a closer coupling coil for the chip. This is a subject we’ve looked at before here at Hackaday, and we wouldn’t mind having another go at it.

E4 Empatica device for measuring location, temperature, skin conductance, sleep, etc. on arm

Wearable Sensor For Detecting Substance Use Disorder

Oftentimes, the feature set for our typical fitness-focused wearables feels a bit empty. Push notifications on your wrist? OK, fine. Counting your steps? Sure, why not. But how useful are those capabilities anyway? Well, what if wearables could be used for a more dignified purpose like helping people in recovery from substance use disorder (SUD)? That’s what the researchers at the University of Massachusetts Medical School aimed to find out.

In their paper, they used a wrist-worn wearable to measure locomotion, heart rate, skin temperature, and electrodermal activity of 38 SUD patients during their everyday lives. They wanted to detect periods of stress and craving, as these parameters are possible triggers of substance use. Furthermore, they had patients self-report times during the day when they felt stressed or had cravings, and used those reports to calibrate their model.

They tried a number of classification models such as decision trees, discriminant analysis, logistic regression, and others, but found the most success using support vector machines though they failed to discuss why they thought that was the case. In the end, they found that they could detect stress vs. non-stress with an accuracy of 81.3% and craving vs. no-craving with an accuracy of 82.1%. Not amazing accuracy, but given the dire need for medical advancements for SUD, it’s something to keep an eye on. Interestingly enough, they found that locomotion data alone had an accuracy of approximately 75% when it came to indicating stress and cravings.

Much ado has been made about the insufficient accuracy of wearable devices for medical diagnoses, particularly of those that measure activity and heart rate. Maybe their model would perform better, being trained on real-time measurements of cortisol, a more accurate physiological measure of stress.

Finally, what really stood out to us about this study was how willing patients were to use a wearable in their treatment strategy. It’s sad that society oftentimes has a very negative perception of SUD patients, leading to fewer treatment options for patients. But hopefully, with technological advancements such as this, we’re one step closer to a more equitable future of healthcare.

Respiratory rate measuring device attached to volunteer's abdomen along with automated antidote injection system

Researchers Use Wearable To Detect And Reverse Opioid Overdoses In Real-Time

Opioid overdose-related deaths have unfortunately been increasing over the last few decades, with the COVID-19 pandemic exacerbating this public health crisis even further. As a result, many scientists, healthcare professionals, and government officials have been working tirelessly to end this deadly epidemic. Researchers at the University of Washington are one such group and have recently unveiled a wearable to both detect opioid overdose and deliver an antidote, in real-time, restoring normal bodily function.

As the researchers describe in their paper, opioid overdose causes respiratory rate depression which will lead to hypoxia (insufficient oxygen in the blood) and ultimately death. Fortunately, opioid overdose can be readily reversed using naloxone, a compound that binds to receptors in the brain, outcompeting the opiates themselves, and restoring normal breathing. Unfortunately, if someone is overdosing, they are unable to self-administer the antidote and with many opioid overdoses occurring when the victim is alone (51.8%), it is necessary to develop an automated system to deliver the antidote when an overdose is detected.

The researchers begin by describing their process for measuring respiration, of which there are several options. You could use photoplethysmography in much of the same way we measure heart rate. Or you could measure the changing impedance of the chest cavity during breathing or even use an intraoral sensor that measures airflow in the mouth. Instead, the researchers opt to measure respiration by attaching accelerometers to the patient’s abdomen and measuring the movement of the abdominal cavity during breathing. They admit their technique becomes problematic when the patient is not stationary, but argue that in the case of a drug overdose, the patient is likely to be immobilized and the device would be able to measure respiration with ease. They tested their device across dozens of healthy, human volunteers, and even some opiate users themselves, and showed their technique had good agreement with a reference respiratory belt placed around the volunteers’ chests.

The cool part about this paper is that they demonstrated a “closed-loop” feedback system in which their device measured respiration, detected cessation in breathing (indicating an overdose), and delivered the antidote. To deliver naloxone, they leveraged an existing, commercially-available drug delivery system that requires a user to manually activate the device by pressing a button. They hacked the device a bit such that the trigger could be actuated using a servo motor properly positioned to depress the button when an opioid overdose is detected. They simulated an overdose by asking the healthy, human volunteers to hold their breath for a period greater than 15 seconds. They were able to successfully deliver the antidote to 100% of their volunteer group, indicating the device could potentially work in real-world settings.

Now, the form factor of the device undoubtedly needs to improve in order to deploy this device into the field, but we imagine those are improvements are underway and patients have shown willingness to wear such devices already. Also, there’s still a bit of a question of whether or not accelerometer-based breathing detection is optimal since some drug overdoses cause seizures. Nevertheless, this is an important step in combating the alarming rise in opioid overdose-related deaths and we hope to see many more advances in patient monitoring technologies in this field.

PiGlass V2 Embraces The New Raspberry Pi Zero 2

Well, that certainly didn’t take long. It’s been just about a month since the Raspberry Pi Zero 2 hit the market, and we’re already seeing folks revisit old projects to reap the benefits of the drop-in upgrade that provides five times the computational power in the same form factor.

Take for example the PiGlass v2 that [Matt] has been working on. He originally put the Pi Zero wearable together back in 2018, and while it featured plenty of bells and whistles like a VuFine+ display, 5 MP camera, and bone conduction audio, the rather anemic hardware of the original Zero kept it from reaching its true potential.

But thanks to the newly released Pi Zero 2, slapping quad-core power onto the existing rig was as easy as unplugging a couple cables and swapping out the board. With the increased performance of the new Pi, he’s able to play multimedia content through Kodi, emulate classic games with RetroPie, and even stream live video to YouTube. Using the custom menu seen in the video below, a small off-the-shelf Bluetooth controller from 8BitDo is all he needs to control the wearable’s various functions without getting bogged down with a full keyboard and mouse.

Although it might not have the punch of its larger siblings, the new Pi Zero 2 is definitely a very exciting platform. The highly efficient board delivers performance on par with the old Pi 3, while still being well positioned for battery powered projects like this one. We’re eager to see what develops as the new SBC finds its way into the hands of more hackers and makers in the coming months.

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