Search Results for: sleep
One of the benefits of long-term self-tracking is that one builds up a toolbox of investigatory methods that can be drawn upon when medical adversity hits. One year ago, when Mark Drangsholt experienced brain fog during a research retreat while on Orcas Island in the Pacific Northwest, he had to draw upon the self-tracking tools at his disposal to figure out what was behind this troubling symptom.
Watch this invaluable talk on how Mark was able to combine his self-tracking investigation with his medical treatments to significantly improve his neurocognitive condition.
Here is Mark’s description of his talk:
What did you do?
I identified that I had neurocognitive (brain) abnormalities – which decreased my memory function (less recall) – and verified it with a neuropsychologist’s extensive tests. I tried several trials of supplements with only slight improvement. I searched for possible causes which included being an APOE-4 gene carrier and having past bouts of atrial fibrillation.
How did you do it?
Through daily, weekly and monthly tracking of many variables including body weight, percent body fat, physical activity, Total, HDL, LDL cholesterol, depression, etc. I created global indices of neurocognitive function and reconstructed global neurocog function using a daily schedule and electronic diary with notes, recall of days and events of decreased memory function, academic and clinical work output, etc. I asked for a referral to a neuropsychologist and had 4 hours of comprehensive neurocog testing.
What did you learn?
My hunch that I had developed some neurocognitive changes was verified by the neuropsychologist as “early white matter dysfunction”. A brain MRI showed no abnormalities. Trials of resveratrol supplements only helped slightly. There were some waxing and waning of symptoms, worsened by lack of sleep and high negative stress while working. A trial with a statin called, “Simvastatin” (10 mg) began to lessen the memory problems, and a dramatic improvement occurred after 2.5-3 weeks. Subsequent retesting 3 months later showed significant improvement in the category related to white matter dysfunction in the brain. Eight months later, I am still doing well – perhaps even more improvement – in neurocog function.
It’s a long one today, so buckle in and get ready for some great stuff!
The Quantified Self: Bringing Science into Everyday Life, One Measurement at a Time by Jessica Wilson. This piece, from the Science in Society Office at Northwestern University, explores the Quantified Self movement, with a particular focus on the local Chicago QS meetup. Always interesting to see how individuals draw distinctions between self-tracking projects and “real science.”
Diversity of Various Tech Companies By the Numbers by Nick Heer. Recently Apple released data about the diversity of their employee workforce. This marked the last major tech company to publish data about diversity. In this short post Nick takes that data and shows how it compares to data from the US Bureau of Labor Statistics. Interested in more than just the big six listed here? Check out this great site for more tech company diversity data (Hat tip to Mark Allen for finding that link!)
Intel Explores Wearables for Parkinson’s Research by Christina Farr, Reuters. Intel is in the news lately based on their interest in developing and using their technological prowess for qs-related activities. In this post/press release, they describe how they’re partnering with the Michael J. Fox Foundation to explore how they can use wearable devices to track and better understand patients with Parkinson’s Disease. It appears they’re also working to get their headphone heart rate tracking technology out to market.
Spying on Myself by Richard J. Anderson. I’m always interested in how people talk to themselves about self-tracking. This short essay describes the tools that Richard uses and why he continues or discontinues using them. His follow up is also a must read.
Dexcom Mac Dance by Kerri Sparling. You know we’re fascinated by the techniques and tools developed and refined by the the diabetes community. In this short post, Kerri highlights the work of Brian Bosh, who developed a Chrome extension to access and download data from Dexcom continuous glucose monitors on a Mac. (Bonus link: Listen to Chris Snider’s great podcast episode where he talks to John Costik, one of the originators of the CGM in the Cloud/Nightscout project.)
The Three-Year Long Time Tracking Experiment by Lighton Phiri. Lighton is a graduate student at the University of Capetown. In 2011 he became curious about how he was spending his time. After installing a time-tracking tool on his various computers, he started gathering data. Recently, after 3 years of tracking, he downloaded and analyzed his data. Read this excellent post to find out what he learned.
Experimenting with Sleep by Gwern. One of our favorite self-experimenters is back with some more detailed analysis of his various sleep tracking experiments. Read on to see what he learned about how caffeine pills, alcohol, bedtime, and wake uptime affects his sleep.
QS Bits and Bobs by Adam Johnson. Adam gave talk at a recent QS Oxford Meetup about his lifelogging and self-tracking, his custom tools for importing data to his calendar, and what he’s learned from his experiences. Make sure to also check out the neat tool he’s developed to log events to Google Calendar.
FuelBand Fibers by Variable. A design team was given Nike FuelBand data from seven different runners and created this interesting visualization of their daily activity.
I don’t Sleep That Well: A Year of Logging When I Sleep and When I’m at Work by Reddit user mvuljlst. Posting on the r/dataisbeautiful subreddit, this user tracked a year of their sleep and location data using Sleepbot and Moves. If you have similar data and are interested in exploring your own visualization the code is also available.
In the City that We Love by Brian Wilt/Jawbone. The data science team at Jawbone continues to impress with their production of meaningful and interesting data visualizations based on data from UP users. In this post and corresponding visualizations they explore the daily patterns of people from around the world. Make sure to read the technical notes!
Want to receive the weekly What We Are Reading posts in your inbox? We’ve set up a simple newsletter just for you. Click here to subscribe. Do you have a self-tracking story, visualization, or interesting link you want to share? Submit it now!
Enjoy this week’s list!
The Five Modes of Self-Tracking by Deborah Lupton. One of our favorite sociologists, Deborah Lupton, explores the typologies of self-trackers she’s identified for an upcoming paper. A very nice and clear explanation of the self-tracking practices in regards to different “loci of control.” (Make sure to also read Deborah’s great post, “Beyond the Quantified Self: The Reflexive Monitoring Self“)
In-Depth: How Activity Trackers are Finding Their Way Into the Clinic by MobiHealthNews. An interesting look at the recent influx FDA-cleared activity and movement trackers and how clinicians are looking to use them. Surprising to me is the lack of data access for the patient in these devices (at least on first glance).
The Reluctantly Quantified Parent by Erin Kissane. As a new mother, Erin was hesitant to use what she deemed “anxious technology.” After some hard nights of little sleep she began to slowly incorporate some self-tracking technology into her routine with her newborn daughter. A great read about using tools then putting them away once they’ve served their purpose. (Reminded me of this great talk by Yasmin Lucero.)
Returns to Leisure by Tom VanAntwerp. Tom was interested in his return on investment from his leisure time actives. He tracked his time spent in different non-work activities for two weeks and calculated the cost of participating in those activities.
The Quantified Microbiome Self By Carl Zimmer. The great science writer, Carl Zimmer, writes about a recent experiment and journal article by two MIT researchers who tracked their microbiome every day for a year. Fascinating findings, including a successful self-diagnosis of salmonella poisoning. You can also read the original research paper here.
Better Living Through Data by James Davenport. We recently highlighted one of James’ posts on how his laptop battery tracking led him to understand his computer use habits. In this post he dives deeper into the data.
A Personal Analysis of 1 Year of Using Citibike by Miles Grimshaw. Miles was interested in understanding more about his use of the Citibike bike share system in New York City. Using some ingenious methods he was able to download, visualize, and analyze his 268 total trips. I especially appreciate his addition of a simple “how-to” so other Citibike users can make the same visualizations.
Visualizing Runkeeper Data in R by Dan Goldin. In 2013 Dan ran 1000 miles and tracked them using the popular Runkeeper app. Runkeeper has a quick and easy data export function and Dan was able to download his data and use R to visualize and analyze his runs. (Bonus Link: If you’re a Runkeeper user you might be interested in this fantastic how-to for making a heatmap of your runs.)
This Week on Quantifiedself.com
Natty Hoffman: The Enlightened Consumer
QSEU14 Breakout: Passive Sensing With Smartphones
Jenny Tillotson: Science, Smell, and Fashion
Paul LaFontaine: We Never Fight on Wednesdays
Vanessa Sabino on Tracking a Year of Sleep
Vanessa Sabino was curious about how well she was sleeping. By using the Sleep as Android app, she was able to track a year of sleep data. Before she was able to dig into the data she ran into a problem with the data export format and had to write her own custom data parser to create usable CSV files. Vanessa was then able to use the data to explore her question, “When do I get the most amount of deep sleep?” In this talk, presented at the Toronto QS meetup group, Vanessa explains her process and what she learned from analyzing 340 days of sleep data.
Jenny Tillotson is a researcher and fashion designer who is currently exploring how scent plays a role in emotion and psychological states. As someone living with bipolar disorder, she’s been acutely aware of what affects her own emotions states and has been exploring different methods to track them. In this talk, presented at the 2014 Quantified Self Europe Conference, Jenny discusses her new project, Sensory Fashion, that uses wearable tracking technology and scent and sensory science to improve wellbeing. Be sure to read her description below when you finish watching her excellent talk.
You can also view the slides here.
What did you do?
I established a new QS project called ‘SENSORY FASHION’, funded by a Winston Churchill Fellowship that combines biology with wearable technology to benefit people with chronic mental health conditions. This allowed me to travel to the USA and meet leading psychiatrists, psychologists and mindfulness experts and find new ways to build monitoring tools that SENSE and balance the physiological, psychological and emotional states through the sense of smell. My objective was to manage stress and sleep disturbance using olfactory diagnostic biosensing tools and micro delivery systems that dispense aromas on-demand. The purpose was to tap into the limbic system (the emotional centre of our brain) with aromas that reduce sleep and stress triggers and therefore prevent a major relapse for people like myself who live with bipolar disorder on a day to day basis. I designed my own personalized mood-enhancing ‘aroma rainbow’ that dispenses a spectrum of wellbeing fragrances to complement orthodox medication regimes such as taking mood stabilizers.
How did you do it?
Initially by experimenting with different evidence-based essential oils with accessible clinical data, such as inhaling lavender to aid relaxation and help sleep, sweet orange to reduce anxiety and peppermint to stimulate the brain. I developed a technology platform called ‘eScent’ which is a wearable device that distributes scent directly into the immediate vicinity of the wearer upon a biometric sensed stimuli (body odor, ECG, cognitive response, skin conductivity etc). The scent forms a localized and personalized ‘scent bubble’ around the user which is unique to the invention, creating real-time biofeedback scent interventions. The result promotes sleep hygiene and can treat a range of mood disorders with counter-active calming aromas when high stress levels reach a pre-set threshold.
What did you learn?
I learnt it is possible to track emotional states through body smells, for example by detecting scent signals that are specific to individual humans. In my case this was body odor caused by chronic social anxiety from increased cortisol levels found in sweat and this could be treated with anxiolytic aromas such as sweet orange that create an immediate calming effect. In addition, building olfactory tools can boost self-confidence and communication skills, or identify ‘prodromal symptoms’ in mood disorders; they learn your typical patterns and act as a warning signal by monitoring minor cognitive shifts before the bigger shifts appear. This can easily be integrated into ‘Sensory Fashion’ and jewelry in a ‘de-stigmatizing’ manner, giving the user the prospect of attempting to offer them some further control of their emotional state through smell, whether by conscious control or bio-feedback. The next step is to miniaturize the eScent technology and further explore the untapped research data on the science of body (emotional) odor.
Enjoy this week’s list of articles, links, show&tells, and visualizations.
Personal Health Data: Five Key Lessons for Better Health by Patti Brennan and Stephen J. Downs. A fantastic post by two great thinkers in the world of personal health and data. They outline five key challenges that must be addressed in order to have meaningful use of personal health data.
It’s Time for Open Data on Open Data by Luke Fretwell. A short but meaningful post here. With all the clamor for more government open data portals it’s time to start exploring how they’re actually being used and what can be done to improve them.
The NFL Gets Quantified Intelligence, Courtesy Of Shoulder Pad-Mounted Motion Trackers by Darrell Etherington. As a sports fan and spouse of someone who works in sports media production I am fascinated by how the world of personal data is quickly colliding with professional athletics. We’ve long looked towards athletes for inspiration and examples of how data can be used to understand and improve and I’m very interested to see how the NFL will make use of this data. Maybe we’ll see more sabermetric-like player and team analysis?
Heart Rate Variability While Giving a Public Speech by Pau LaFontaine. Paul gave a show&tell talk at a recent Bay Area QS meetup and tracked his heart rate variability. This post explains his data, and what he learned about the stress involved with public speaking. Be on the lookout soon for his show&tell talk video.
Chronic Diease and Self-Tracking – Part 1 by Sara Riggare. Sara is a longtime contributor in the Quantified Self community, having spoken at each of our three QS Europe Conferences. In this post she explains her new exploration of her resting heart rate and poses some interesting questions. We’d love to have you help her out!
Raspberry Pi Sleep Lab How-To by Nick Alexander. Nick was bothered by a common nightly occurrence, kicking off his covers in the middle of the night. Like any enterprising technologist, he enlisted his technical expertise to help examine this problem. This post is an amazingly detailed “How To” for building and setting up your own personal sleep monitoring tool complete with video, environmental information, sound, and sleep data.
This week I’ve been exploring how people are making using physical data visualizations. During some research I found a great resource, the List of Physical Visualizations. A few images below are from that great list, be sure to spend some time exploring the many different examples and then reading the excellent research paper linked below.
Evaluating the Efficiency of Physical Visualizations by Yvonne Jansen, Pierre Dragicevic, and Jean-Daneil Fekete. The first empirical study of the effectiveness of physical visualizations for conveying information. Using 3D bar charts as a primary example, the authors were abel to show that physical visualizations are more effective than their digital on-screen counterparts for some information retrieval tasks.
From the Forum
Want to receive the weekly What We Are Reading posts in your inbox? We’ve set up a simple newsletter just for you. Click here to subscribe.
The St. Louis QS meetup group just checked in with a recap of their fifth show&tell meetup. They’ve been growing fast, with now over 100 members in their community and are exploring fun new ways to encourage and inspire their group.
Last week, about 20 members got together to watch and discuss some of their favorite QS show&tell talks. After some discussion, they selected three talks:
The St. Louis QS group is also taking an active part in turning their experience and enthusiasm for data collection into projects for their local community. Last month, they participated in the National Day of Civic Hacking and proposed two QS-themed projects that they are currently developing:
1. A context-sensitive Geo-Polling app/initiative that would allow communities to become aware of how people feel in various areas (e.g. happiness, safety, etc.).
2. A Personal Environmental Tracker (PET) that would allow St. Louis citizens to keep tabs, not only on their own environmental impact, but also on the community as a whole in an engaging way.
(If you are interested in finding out more and participating in either of these projects at any level, you can join the meetup and get in touch with the organizers.)
Thanks to St. Louis QS Organizer William Dahl for sending in a great recap of their meetup. If you’re in the St. Louis area, we invite you to join the group!
A nice long list of amazing posts, show&tells, and visualizations for you!
Social Wearables by Noah Feehan. In this blog post, from the New York Times R&D lab, Noah expands on the idea of measurement and tracking devices that support “social affordances.” Fits in nicely with our post from Rain Ashford on “Emotive Wearables”.
Have Professional CGMs Passed Their Prime? by Will Dubois. In our continued exploration of the role of data access in the diabetes community we have run across many interesting stories. Wil’s amazing post here describes how some people with diabetes are never given access to what could be the most important data in their lives.
How the Technological Design of Facebook Homogenizes Identity and Limits Personal Representation by Ben Grosser. Each piece of software we use has built-in methods that allow or do not allow us to represent ourselves to the world in a personally relevant manner. In this article, Ben Grosser, describes the various methods that the largest online identity platform uses to curtail freedom of identity expression. (For those interested in Ben’s work, we suggest reading our post about his “Demetricator” project.)
Qualitative Self-Tracking and the Qualified Self by Mark Carrigan. In this post, Mark makes the case for measurement of and reflection on the quality of our human experiences to engage in qualitative self-tracking:
“… using mobile technology to recurrently record qualities of experience or environment, as well as reflections upon them, with the intention of archiving aspects of personal life that would otherwise be lost, in a way susceptible to future review and revision of concerns, commitments and practices in light of such a review.”
Why Silicon Valley Needs the Coder GRRLS of Double Union, the Feminists Hacker Space by Rebecca Greenfield. A wonderful profile of the Double Union hacker/maker space for women in San Francisco. Directed by our friend, Amelia Grenhall, Double Union is making a real difference for the female and feminist community.
What is Public? by Anil Dash. A great post here by Anil Dash on why we need to fight to define “public” in an era where communication and information is increasingly occurring in online media platforms.
“By continuing to stretch the definition of what’s public, and to expand the realm of what’s considered acceptable use of public information, we enable a pervasive surveillance culture.”
“Letting Go of Things We Can’t Control” + Remembering That Sleep Matters by Dana Lewis. We’ve shared Dana’s and Scott’s work on their DIY Pancreas project in the WWAR list before and we will probably share it again in the future. For now, this is an excellent post about how Dana was able to turn a long-distance relay race into a learning opportunity.
An Experiment: The Psychic Impact of Our Connected Lives by Deborah Schultz. Deborah, a co-founder of the YxYY festival, discusses why she downloaded the Red Alert, an app to inform and warn Israelis about incoming rocket attacks, and what she experienced after a week of near constant alerts.
Using RescueTime to Answer the Question: When Do I Write? by Jaime Todd Rubin. Another great post by Jaime explaining how he uses the RescueTime personal tracking software to learn more about his writing habits. For those interested, Jaime also has a nice article here about his thoughts on getting started with self-tracking.
Reportr.io by Sammy Pessé. Personal data dashboards are becoming more common on the web, a way to reflect your data back to the world at large. Sammy Pessé recently released an open-source project to help you get started with creating your own personal data dashboard.
Dave Jacoby’s Fitbit Heatmap by Dave Jacoby. Dave piped up on my Twitter feed during a discussion about using the popular If This Then That web service to save self-tracking sensor data. It turns out he’s been doing some really interesting data processing and visualizing work with his Fitbit data. Learn more about what he’s up to on his Github project page.
Meal of Fortune by Emi Nomura. Emi is a data scientist at Jawbone and is working on their UP tracking system. This data project was intended to look at what types of foods people eat together. Make sure to click through for the interactive visualization.
VizRisk Challenge. From our friends at the US Department of Health and Human Services comes the first government-backed competition to visualize behavioral health data. We’d love to see our QS community get involved.
From the Forum
Access to Data from Clinical Trials
What do you find to be the most valuable metrics and how do you track/plot them all?
Tracking Music Activities
Tracking HRV During the Workday
Want to receive the weekly What We Are Reading posts in your inbox? We’ve set up a simple newsletter just for you. Click here to subscribe.
Today’s Tidings dispatch is from Daniel Gartenberg, co-organizer of the Washington DC meetup group. Read below to hear about their recent meetup. It sounds like a great time and we can’t wait to share the videos from these interesting talks.
We had our biggest meetup yet at 1776 – a start-up hub located in the heart of our nations capital. At the meetup there were three great talks, fun socializing over sandwiches, and lively QS Discussions. We had three wonderful talks:
James Norris – serial entrepreneur and avid self-experimenter gave a captivating talk about tracking his “firsts”. This included everything from his first kiss to his first time meditating on a train. One thing that James found was that traveling was one of the key factors that impacted his “firsts” – but only up to a limit – where after some time traveling, there are diminishing returns to “firsts”.
Next, Daniel Gartenberg gave a talk on his new efforts to evaluate and improve sleep. He described a study that he is conducting with the QS community where participants can receive $50 for tracking 2 weeks of their sleep data. Some participants will even have the opportunity to use a Hexoskin, actiwatch, and galaxy gear. However, users must have an iPhone and be willing to take 10 minutes out of their day for cognitive testing. Please contact Daniel Gartenberg at email@example.com if you are interested in participating in the study.
Finally, Daniel Martinez showed off an amazing visualization of more than 1800 days of his sleep data that he calculated using pencil and paper and inputting the data into Mathemetica software. Daniel created a new tool for evaluating sleep, which included categorizing time as “up and at em”, dozing, sleeping, and awake while trying to sleep. Using these categories he presented visualizations of sleep and showed a bimodal distribution in his bedtime and a new way to evaluate his sleep quality.
If you’re in the Washington, DC area we invite you to join this great meetup group!
As much as we talk about self-tracking being about health or fitness. . . I think it’s about identity. I think it’s about us. It’s about seeing something meaningful in who we are.
Laurie Frick is a self-tracker and visual artist. It this unique combination that has led her down a path of learning about herself while using the data she collects to inform her artistic work. What started with time and sleep tracking rapidly expanded to included other types of data. In this short talk, presented at the 2014 Quantified Self Europe Conference, Laurie explains how her past experiences have informed her new way of thinking about data, “Don’t hide. Get more.”
If you’re interested in Laurie’s artistic work I highly recommend spending some time browsing the gallery on her website.