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New QS Devices

While a student at UC Berkeley, I was awed by the miniaturized devices created in the engineering department for neuroscientists. Eventually, these devices will enable entirely new kinds of Quantified Self projects. Here are three especially promising projects I came across while studying for my degree in neurobiology.

Temporary Tattoo EEG

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Where: UC San Diego

Who: Professor Todd Coleman’s Neural Interaction Lab, and recent graduate Dr. Dae Kang

What it does: Continuous monitoring of vital signs can be uncomfortable, high noise, and restricted to hospital environments. However, recent developments in flexible, stretchable electronics are allowing metrics like brain activity (via EEG) to be measured wirelessly and with high precision. A typical EEG involves attaching electrodes to the scalp with glue and gel, connected to wires and heavy machinery. The temporary tattoos under development in the Coleman lab accomplish the same thing wirelessly. Due to improved conformability to the skin – they can even reduce motion artifacts in comparison to standard machinery. Further, the technique is modifiable: different miniature sensors can be added depending on the desired application.

QS Impact: Consumer versions of this bendable technology could help improve the notoriously low efficacy of wearable sleep staging and improve hospital visits. For example, Dr. Dae Kang is developing the use of a single wearable tattoo for determining sleep stage. Dae has also helped develop stretchable electronics for monitoring neonatal EEG and temperature. These permitted infants in the neonatal intensive care unit to be held by caregivers and freed of the isolating tangle of wires that normally monitor their vital signs.

Non Invasive Gut Activity Monitoring

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Where: UC San Diego

Who: Professor Todd Coleman’s Neural Interaction Lab, and recent graduate Dr. Armen Gharibans.

What it does: Think of the electrogastrogram (EGG) as an EEG for your gut. Because your gut contains the largest number of nerve endings outside your central nervous system, it gives off quite a bit of electrical activity. The location and intensity of this signaling can be used to extract information about digestive activity comparable to that normally attained via invasive measures (is the activity stably periodic, or disrupted? Is the power of the activity lower or higher than is normal for you?). These invasive measures – picture a gastroduodenal manometry probe wired down your throat – are uncomfortable, can require sedation, and limit regular mobility. Further, current methods typically gather recordings for only a few hours, limiting the ability to observe digestion over the ‘cycle’ of a day or more.  By contrast, the EGG is worn as an electrode array on the abdomen. It collects up to 24 hours of continuous gut activity and heart rate as the wearer walks, sleeps, eats and even exercises. Because it’s fairly comfortable (I was lucky enough to use it in a QS project and can attest to this!) it’s easy to collect multiple days of data – allowing comparison of that individual to themselves rather than to a population average. Dr. Ghariban’s technique is a breakthrough in filtering: locating a clean and biologically relevant signal through the skin and muscle wall as the electrodes are jostled by the person’s movements is no small feat. With a cleaner and easier-to-acquire signal, Armen can begin to gather enough recordings to start classifying which patterns are representative of ”healthy” and ”unhealthy” gut activity.

QS Impact: Researchers are currently using the EGG to study how our digestion works during wake, sleep, and recovery from illness. The goal is to map the periodic process of digestive motility and generate non-invasive biomarkers for health and impending illness. Rather than being constant through time, or changing linearly, gut activity oscillates across the day and night. These patterns need much more study, but hint that it might be possible to find a phase of oscillation during which it is better to eat a meal.  The EGG was recently used as part of an incredible case study: observing the restart and re-stabilization of intestinal activity following bowel surgery. In concert with microbiome testing, target applications of the EGG include diagnosing functional gastric disorders like gastroparesis (a condition affecting more than half of diabetics and Parkinson’s patients, where food is not moved through the digestive tract in a timely manner), and helping you learn what times of day are physiologically best for you to eat.

Smart ‘Dust’

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Where: UC Berkeley

Who: Professor Kris Pister, PhD candidate David Burnett

What it does: Wearables are shrinking over time, but how small could they become? The Smart Dust project seeks to overcome size constraints in power source and radio communication in order to reduce the size of an autonomous sensor to 1 mm. In one fascinating part of this project, The Pister Lab and PhD candidate David Burnett are creating 4mm sq. chip. It can capture light, temperature and activity – but will be modifiable to carry more sensors. What is novel about the approach is the integration of a new kind of radio, and a solar rather than battery power source. Both provide engineering challenges, but the result will be a sensor that powers itself, and is able to send and receive information from a much much smaller chip.

QS Impact: Integrating these chips into clothing or jewelry, and scattering them about the environment have many potential applications. The application for which the chip is initially being designed is the continuous monitoring of circadian rhythms: our body’s way of anticipating periodic environmental change. Disruption of these rhythms is associated with myriad chronic diseases, but these rhythms are not usually monitored with an eye toward mitigating disruption.

For example, we all hear that we should limit blue light exposure in the evening – and that a weekend of camping can help re-align our bodies to the day night cycle. But we currently lack easy, consumer wearables that are tailored to measure just how ‘misaligned’ our bodies are. Smart dust that collects light, temperature and activity data from users and their ‘natural environments’ aims to create a poignant representation of health by helping people understand the stability of their behavior and physiology in relation to their environment. A more distant application is the development of autonomous sensor networks. Precise, wirelessly transmitting and energy harvesting, these networks could be used for health monitoring with zero input from the user, to allow them to truly forget they are ‘wired in’ to a device.

The push for smaller, more efficacious, and less invasive health monitoring devices continues to generate fascinating new technology. The projects deserve our attention and support. And while they aren’t on the consumer market yet, we can’t wait to try them.

 

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Meetups This Week

 

BreakoutImage2-LongThis week we have three meetups spanning three continents. Hong Kong’s 6th meetup will share the results of a month-long self-tracking project. Hamburg will be having it’s 10th meetup with talks on meditation and fitness tracking. In Denver, a Zen master and professional cyclist will be among the attendees.

To see when the next meetup in your area is, check the full list of QS meetup groups in the right sidebar. Don’t see one near you? Why not start your own! If you are a QS Organizer and want some ideas for your next meetup, check out the myriad of meetup formats that other QS organizers are using here.

Wednesday, August 16

Hong Kong, China

Thursday, August 17

Denver, Colorado
Hamburg, Germany

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Is My Data Valid?

How much do I trust this data?

This question has kept me awake many a night, both in the lab and during self-tracking experiments. Researchers do validation tests even when using expensive and widely trusted laboratory equipment, and these tests often expose unexpected problems. Commercial self-tracking devices present similar challenges, especially because company-sponsored validation tests may not be independently verified and may be difficult to understand and replicate individually. Though this problem won’t be solved overnight, there are several steps you can take to better understand the constraints of your new technology.

In this post, I’m going to take you through some lessons I’ve learned from a recent attempt to validate a widely used lipid test kit. Some of these lessons are generally applicable, and I hope they will be useful to you as you do your own tests.

I’ve been working on a Quantified Self project to support people doing unusually high frequency home lipid testing. For the project to succeed, we need to determine the accuracy and precision of the CardioChek® Plus from PTS diagnostics. (Accuracy refers to how close a device output is to its real value; precision measures how consistent a measure is across identical trials.) We chose this device from among almost a dozen different options and approaches, because it was in common use, was easily accessible, and was approved by the FDA for home use. But in order to ask sensible questions about our data, we needed to know how well it would do under real conditions. With some work, I was able to find the reported accuracy and precision of the device, verify both in my own hands, and alleviate considerable anxiety about generating believable data.

Here are some tips based on my experience. Of course success is not guaranteed; it will depend on the device you have, the time you’re willing to invest, and a bit of luck. But these general suggestions should get you on your way.

  1. Look carefully through the wearable’s website and read the fine print. Some manufacturers report their in-house testing online, but tucked in a corner where it’s hard to find. Although companies typically won’t report bad results, it’s at least a place to start.
  2. Pubmed. This is the watering hole for finding scientific literature. Try searching the name of your wearable here. Abstracts are generally available.
  3. Check the QS forum. Someone there may have the details of your device.
  4. Contact the company, and frame your questions about getting the most accurate and valid data as positively as possible. Many of these companies are small. Yes, they might brush you off, but they might be willing to give you insider tips on how to best use your device, or even raw data from their own trials to compare with your own. If you are able to explain a personal experiment requiring a particular degree of accuracy or precision, a one-on-one conversation is more likely to get you a relevant an honest answer than hours of googling. There are often hidden factors (lighting and humidity in my case) that make a huge difference in your data quality.
  5. Find a medical/industry standard to compare your device to. It’s very important to not only read reports of a device’s accuracy and precision, but to test it in your own hands. For me, this meant making a doctor’s appointment for a fasting lipid panel, taken at the same time as I did my own finger prick test with the CardioCheck. This is not always possible (most of us are unlikely to have access to polysomnography), but do your best.
  6. Replicate your results under similar conditions. This one is often easier.
    If you measuring, say temperature, do so many times in a row to see the amount of variability. To see how accurate your step or distance tracker, walk from your house to the park several times and compare results. In my case, I pricked my fingers a few times in a row (ouch, but necessary).
  7. Take time of day into account when you are doing any measurement. Circadian rhythms are prominent in pretty much every system in your body. This means you should expect variability in any output by time of day. Let’s say that you’re tracking your basal body temperature (BBT) upon waking up as part of tracking ovulatory cycle. Sleeping until 11am on Saturday when you usually record at 6am on weekdays will confound the prediction of your cycle for sure! A perfectly accurate device can’t be a stand-in for good controls in your personal experiment.
  8. Once you know the constraints of your device, work within them. This may seem obvious, but it’s common to put too much faith in unverified data. Numbers aren’t magic. They are the outputs of sensors with strengths and weaknesses and calculations programmed by humans. Even a device with imperfect accuracy, but is consistent, can give useful information: you just have to figure out the right questions to ask.
  9. Don’t give up. This process takes time, but pays off in the long run. The trust gained from putting an honest effort into validation will save you hours, days or even weeks of confusion from trying to explain results that are just noise in the system, or from having to re-do an entire experiment. Save that time now.
  10. Embrace uncertainty. One of the toughest parts about navigating the validation of a new device is getting comfortable with uncertainty. A peek under the hood often reveals a lot we might wish we didn’t know. Sure, it would be nicer if the world delivered perfect data with every wearable purchase, but it isn’t so. Like all learning endeavors, it’s a continually evolving process that will not guarantee perfection. Questioning one’s potentially false sense of certainty, and leaning into the tricky process of confronting unknowns is a good practice to keep us honest anyways.

If you have done a validation test of a self-tracking tool, we’d like to hear about it.

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Meetup This Week in Cambridge, United Kingdom

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This Wednesday the Cambridge QS Group is hosting a meetup on making exercise more fun. If you want to see how multiplayer gaming, science museums, and office furniture hacks can help you get more movement into your day, this is a meetup for you.

Wednesday, August 9

Cambridge, England

To see when the next meetup in your area is, check the full list of the over 100 QS meetup groups in the right sidebar. Don’t see one near you? Why not start your own! If you are a QS Organizer and want some ideas for your next meetup, check out the myriad of meetup formats that other QS organizers are using here.

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QS17 Highlight: My Scars by Ellis Bartholomeus

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Ellis Bartholomeus gave a talk at QS17 that is a definite “must watch.”

We all accumulate physical scars throughout our lives. My own history consists of scrapes from trees, kitchen burns and a misadventure with liquid nitrogen. Ellis has taken a quantitative and thoughtful look at the form and meaning of her scars. At left, is a map of decades’ worth of Ellis’ scars. In her talk, she walks through that history and the way she turned it into data, which allowed novel findings, such as, if she added the lengths of her scars, the total is over a meter.

We often spend our time trying to appear and feel unworn by our years, covering them with clothing or makeup and ignoring the memories they represent. While Ellis embraces the past, she discusses the frustration associated with the limitations imposed by her injuries. Still, she uses her scars as a visual reminder to appreciate her own history and resilience.

You may watch the entire talk at her project’s page.

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Meetups This Week

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We have meetups on both sides of the pond this week . Manchester and London will have a great program of show&tell talks, and Austin will be talking about accountability groups and fitness.

Tuesday, August 1st
Manchester, England — Only 12 spots left!

Thursday, August 3rd
Austin, Texas, United States
London, England

To see when the next meetup in your area is, check the full list of the over 100 QS meetup groups in the right sidebar. Don’t see one near you? Why not start your own! If you are a QS Organizer and want some ideas for your next meetup, check out the myriad of meetup formats that other QS organizers are using here.

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Meetup This Week in L.A.

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Live near the USC campus and have a QS project to share? The QS L.A. meetup is getting started again by hosting a show&tell session tomorrow.

Tuesday, July 25th
Los Angeles, California

We haven’t been doing these posts as often recently - but meetups have still been happening! To see when the next meetup in your area is, check the full list of the over 100 QS meetup groups in the right sidebar. Don’t see one near you? Why not start your own! If you are a QS Organizer and want some ideas for your next meetup, check out the myriad of meetup formats that other QS organizers are using here.

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QS17 Highlight: Taking on my Osteoporosis

Justin LawlerA persistent theme at the 2017 Quantified Self Conference was how self-tracking can help those with chronic conditions spot associations between symptoms and lifestyle that a clinician might not have time to uncover. These personal discoveries can help improve one’s health.

In this show&tell, Justin Lawler talks about learning that he has early onset osteoporosis and the several metrics, including diet, microbiome, exercise, sleep and bone density, he tracks to help manage and understand the disease.

I love that the talk emphasizes that many QS projects are long term – even lifelong. Most conventional research projects have a start and end date, garnering a lot of information but only addressing a limited window in time. The self awareness that comes with self tracking can be useful across months and years, elucidating subtle patterns that might otherwise be undetectable.

Watch Justin’s show&tell talk at it’s project page.

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QS17 Highlight: Body Temperature and Ovulatory Cycles

Azure TalkI was thrilled to have the chance to do a Show&Tell talk about tracking my ovulatory cycle via minute-by-minute body temperature during the final plenary session at QS17 Conference. It’s an ongoing project that explores what high-temporal-resolution body temperature can help us learn about our reproductive state. Daily body temperature readings are already used to aid fertility tracking, but several of you expressed interest in collecting more frequent data with me. You inspired me to start uploading my cycle tracking code on Github. I’ll be adding to this repository over time, so check back and shoot me a message if you have an idea you’d like me to try!

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QS17 Amsterdam Highlight: Tracking Crying

Robin_Weis_CrymotionWe’re back from QS17 and eager to share the conference with you from beginning to end. This, our ninth conference, covered a lot of ground: we showcased self-tracking projects, investigated our relationship with technology, and discussed the past and future of QS. Over the coming weeks, we’ll share some conference highlights.

Today I want to share our opening Show & Tell from Robin Weis, which captures the personal discovery and data-driven spirit of QS. If you’re new to QS, you might not know that the community is about much more than tracking your steps or your hours of sleep: it’s about gaining personal insight by putting numbers to any important aspect of your life. Robin Weis tracked an unusual metric – crying – over a long period of time and did an inspiring job tying together her personal story with her data. Click the link above, check it out, and come back in a few days for another talk!

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