Tag Archives: music
It’s hard for me to like an album the first time I listen to it. I can almost feel some part of my brain reject the music, even from bands I like, because it’s not familiar. However, after a few listens, the album will grow on me and I’ll find myself humming melodies that I previously couldn’t sit through. That is, unless I turned off the album the first time around and never gave it a second listen.
I suspected that this behavior was having a negative impact on my ability to appreciate new music when I noticed that almost none of the music that I listen to has come out after 2006.
In this talk, given at a recent QS Bay Area meetup, I discuss the system I set up that scheduled when I should listen to an album to help me over the hump to appreciating an album on it’s own terms instead of rejecting it because it wasn’t familiar.
QS17 is coming soon
Our next conference is June 17-18 in lovely Amsterdam. It’s the perfect event for seeing the latest self-experiments, debating the most interesting topics in personal data, and meeting the most fascinating people in the Quantified Self community. There are a limited number of tickets left. We can’t wait to see you there.
“I love reading random papers about the human body.”
Ahnjili Zhuparris came across a study on the menstrual cycle’s influence on cognition and emotion and was curious to see how hormonal changes may affect her day-to-day behavior. She figured her internet use may be a convenient and easy data set to assemble and examine for this effect. Using a few chrome plugins, Ahnjili was able to see not only where she spent her time online, but how she interacted with sites like Facebook and Youtube.
Her analysis yielded some interesting patterns. She found the most distinctive behaviors occurred during the fertile window, a span of about six days in the menstrual cycle when the body is most ready for conception. Looking at her shopping data from a clothing website:
”I found that there was no change in the amount of money I spent or the amount of time I shopped online… but while I was most fertile, I bought more red items. In fact, it was the only time I bought red items.”
In this talk, Ahnjili shows the differences in how she browsed Facebook, swiped in Tinder, and listened to music on YouTube.
Here are a few of the tools and papers that Ahnjili cites in her talk:
- Period Diary (iOS)
- timeStats (Chrome)
- Facebook Stats (defunct, it seems)
- Youtube Stats (Chrome)
- Menstrual cycle influence on cognitive function and emotion processing-from a reproductive perspective.
- Natural Born Cyborgs by Andy Clark
- A randomized trial of the effect of estrogen and testosterone on economic behavior.
- Romantic Red: Red Enhances Men’s Attraction to Women
- On the frequency of intercourse around ovulation: evidence for biological influences.
DNA Got a Kid Kicked Out of School—And It’ll Happen Again by Sarah Zhang. This a potent example of the unexpected ways that genetic information can be used against someone. We’ve already seen how 23andMe data can be used for nefarious ends. In this case, it’s a child who was transferred from his school as if he has cystic fibrosis, but only has the genetic markers for the disease. A set of norms or rights around personal data (and genetic information, in particular) has barely been established, so it will be interesting to see how many similar incidents we will see. What’s tricky is that neither side is acting irrationally. At heart is this question: How do you manage risk when a person’s DNA is part of the equation? -Steven
When Wearable Makers Shut Down, Getting Your Data Isn’t Always Easy by Stephanie M. Lee. San Francisco QS Show&Tell co-organizer Greg Schwartz is quoted in this Buzzfeed story about the recent shutdown of BodyMedia servers and bricking of the devices. In January Greg posted a how-to video users who still wanted to get their data, but this only worked until the servers were taken offline on January 31, 2016 Article author Stephanie M. Lee talked a bit about the defunct QS companies Lark, and Zeo. The Zeo shutdown sparked a record thread on the QS Forum where users still trade tips to keep instances of this late, lamented sleep tracker in action. -Gary
Working memory training could help beat anxiety by Christian Jarrett. Dual n-back tests have been championed as a brain game that actually works since a 2008 study showed that the exercise improved fluid intelligence (i.e., IQ). Those results have since been in dispute, but a new study cautiously supports the idea that dual n-back, by improving working memory, may also lessen anxiety symptoms. -Steven
Graphing When Your Facebook Friends Are Awake by Alex. There are at least five reasons to love this post about building graphs of Facebook Friends’ awake/asleep time: a surprising revelation of hidden system, uh, features; a “procedural” on hacking them that is basically comprehensible even if – like me – you don’t understand all the details; a useful general lesson about public exposure of personal data from seemingly friendly and low level status tracking; a hilarious stream-of-consciousness narrative that tries, half-successfully, to answer the question “why;” and, for all of us who have ever tried to do something meaningful with our own data, the comforting admission that the real trouble started when it came time to make a graph. Really a great post that this preview doesn’t do justice, so go read it. -Gary
This Canadian Lab Spent 20 Years Ruining Lives by Tess Owen. As much as it’s claimed that there’s a fair amount of skepticism of science, especially in the United States, there is no doubt that it carries authority in legal matters. This article shows the damage that can happen when seemingly rigorous test procedures and results are accepted without scrutiny. It’s especially galling to see how sloppy commercial testing procedures can become, and how dangerous it is to assume that professional measurement is more reliable than personal measurement, human dialog, and common sense. -Steven
Give Up Your Data to Cure Disease by David B. Agus. Another article on the opportunities and pitfalls of making medical records available for health research. While this opinion piece argues for the value of the opportunities, it makes clear that we need better data security practices to ensure that health information is used for the greater good, rather than used against individual patients. However, nowhere is the point made that research subjects can play an active role in investigating disease and making new discoveries. -Steven
Three Years of Logging my Inbox by Mark Wilson. The number of emails in Mark’s inbox correlates very well with his stress level. After passively tracking his email for three years, Mark explores how his inbox count reflects his stress level and influences his sense of self. -Steven
Measuring My Indoor Environment: Indoor Quality and Water Quality by Bob Troia. The first two parts in a multi-part series, Bob shows the tools and measurements he’s using to understand the quality of his living space. -Steven
Maniac Weeks for Extreme Productivity by Bethany Soule. A “maniac week” (coined by Nick Winter) is spent doing nothing but working and sleeping while documenting your face and screen with a time-lapse video. Bethany talks about her successes, failures, and side effects of this level of extremism. -Steven
This Chart Shows Who Marries CEOs, Doctors, Chefs and Janitors by Adam Pearce and Dorothy Gambrell. With data from the U.S. Census Bureau, this interactive chart allows you to select a profession and see the five most likeliest occupations of the partner. It will also show whether if the partner is more likely a member of one sex or the other. Refreshing to see that it represents same-sex partnerships as well. -Steven
How China’s economic slowdown could weigh on the rest of the world by Carlo Zapponi, Seán Clarke, Helena Bengtsson, Troy Griggs and Phillip Inman. The interconnectedness of global economies can be difficult to wrap your head around, but this series of visualizations from the Guardian do a good job of illustrating which economies’ rely on exports to China, and how much they are exposed to a downturn in the world’s second biggest economy. -Steven
Música hecha con el corazon. A website where you tap your current heart rate and it finds a song that matches the beat. The site is in Spanish but is easy enough to figure out. Just put one finger on the artery in your neck and click in the circle in time with your pulse. -Steven
The Chart Book: An Overview of Standard Celeration Chart Conventions and Practices. Owen R. White, Malcolm D. Neely. This pdf covers how to use a Celeration chart. Used for the assessment of students by teachers, this chart template aspires to be flexible enough to chart data clearly no matter the scale. It would be interesting to see this used for personal data. Thanks to Ryan O’Donnell. -Steven
In this fascinating talk Rocio Chongtay shares her novel and thoughtfully designed experiments in using music to adjust her concentration and relaxation depending on what she’s doing. Using a consumer EEG device from Neurosky, Rocio tried different types of music while tracking the relaxation and concentration dimensions identified by the Neurosky algorithm. She had experience experimenting with Neurosky in her lab, and then turned these techniques on understanding something about her own mind.
A few notes up top here. First, if you haven’t yet checked it out please give our new QS Radio podcast a listen. We’d love to hear what you think!
Second, our QS15 Conference & Exposition is fast approaching. It’s going to be a wonderful and jam-packed three days of talks, sessions, and amazing demos. Our Early Bird tickets are almost gone. Register before Monday (May 11th) to get $200 off the regular price!
Now, on to the links!
Data (v.) by Jer Thorp. So many people in my network were sharing this over the last few days I had to give it a read, and I’m happy I did. Jer Thorp makes a succinct argument for turning the word “data” from a amorphous blob of a noun into a verb.
By embracing the new verbal form of data, we might better understand its potential for action, and in turn move beyond our own prescribed role as the objects in data sentences.
How Not to Drown in Numbers by Alex Peysakhovich and Seth Stephens-Davidowitz. In this great article, two data scientists make the case for “small data” – the surveys and rich contextual information from open-ended questions.
We are optimists about the potential of data to improve human lives. But the world is incredibly complicated. No one data set, no matter how big, is going to tell us exactly what we need. The new mountains of blunt data sets make human creativity, judgment, intuition and expertise more valuable, not less.
Data, Data, Everywhere, but Who Gets to Interpret It? by Dawn Nafus. We’ve been collaborating with Dawn and her team at Intel for quite a while, and we’ve learned a lot. Reading this wonderful piece lead to even more learning. Dawn uses this article to describe not only the community of individuals who track, but also why, and what happens when it comes time to interpret the data. (You can explore DataSense, the tool Dawn and her team have been working on, here: makesenseofdata.com)
Applying Design Thinking to Protect Research Subjects by Lori Melichar. Lori is a director at the Robert Wood Johnson Foundation and recently did some work related to how institutional review boards (IRBs) function. For those who don’t know, IRBs are the groups/committee that evaluate the benefits and harms of human subjects research. Their process hasn’t changed much in the few decades, but the face of research has. In this short post Lori describes the ideas that came from thinking about how we might re-design the current system.
ResearchKit and the Changing Face of Human Subjects Protections by Avery Avrakotos. As mentioned above, research is changing, and one of the big changes we’re currently seeing is the use of mobile systems like Apple’s ResearchKit. It’s not all sunshine and roses though, the popularity and excitement that goes along with these new methods also means we have to think hard about we protect those who choose to participate.
I measured my brain waves and task performance on caffeine- here’s what I found by John Fawkes. John was interested in how much caffeine he should be ingesting to help with his mental and physical performance. In this post he details some of what did, how he tested himself, and what he learned about how caffeine, and how much of it, affects different aspects of his life.
The Quantified Self & Diabetes by Tom Higham. Tom was diagnosed with diabetes in the late 80s. In this short post he details some of the different apps and tools he uses to “get my HbA1c down to the best levels it’s ever been.”
2014: A Year in New Music by Eric Boam. I had the pleasure of meeting Eric recently in Austin and was blown away by his ongoing music tracking project. I’m excited to see this new report and learn a bit more about what he’s discovered.
Apple Watch Heart Rate Comparison by Brad Larson. Brad used a simple script to export the heart rate values from his Apple Watch and compare it to two different heart rate measurement devices. Above is a comparison with the Mio Alpha, and he also compared is to a more traditional chest strap and found the readings to be “nearly identical.”
From the Forum
This week on QuantifiedSelf.com
The validity of consumer-level, activity monitors in healthy adults worn in free- living conditions: a cross-sectional study by Ty Ferguson, Alex Rowland, Tim Olds, and Carol Maher. A very interesting research study examining the accuracy of different consumer activity trackers when compared to “research-grade devices.” Free living only lasted a few days, but it’s a great start to what I hope to see more of in the research – actual use out in the wild.
The Healing Power of Your Own Medical Records by Steve Lohr. Steven Keating has a brain tumor. He also has over 70GB of his medical data, much of which is open and available for anyone to peruse. Is he showing us our future? One can hope.
Mr. Keating has no doubts. “Data can heal,” he said. “There is a huge healing power to patients understanding and seeing the effects of treatments and medications.”
Why the DIY part of OpenAPS is important by Dana Lewis. Always great to read Dana’s thoughts on the ever evolving ecosystem of data and data-systems for people living with diabetes.
Why I Don’t Worry About a Super AI by Kevin Kelly. I, for one, am super excited for advancements in artificial intelligence. There are some that aren’t that excited. In this short post our QS co-founder, Kevin Kelly, lays out four reasons why he, and maybe why all of us, shouldn’t be fearful of AI now or into the future.
Responding to Mark Cuban: More is not always better by Aaron Carroll. Earlier this week Mark Cuban started a bit of an kerfuffle by tweeting out, “1) If you can afford to have your blood tested for everything available, do it quarterly so you have a baseline of your own personal health.” What followed, and is still ongoing, is a great discussion about the usefulness of longitudinal medical testing. I’m not sure I agree with the argument made here in this piece, but interesting nonetheless.
My Quantified Email Self Experiment: A failure by Paul Ford. Paul takes a look at his over 450,000 email messages dating back 18 years. He find out a lot, but states that he doesn’t learn anything. I disagree, but then again, I’m not Paul. Still fascinating regardless of the outcome.
Filling up your productivity graph by Belle Beth Cooper. Want to understand your productivity, but not sure where to start? This is a great post by Belle about how she uses Exist and RescueTime to track and understand her productive time.
2014: An Interactive Year In New Music by Eric Boam. We’ve featured some of Eric’s visualization work here before, but this one just blew me away. So interesting to see visualization of personal data, in this case music listening information, turned into something touchable and engaging.
“Women and Children First” by Alice Corona. A fascinating deep data dive into the Titanic disaster. Was the common refrain, “Women and children first!” followed? Read on to find out.
HHS Expands Its Approach to Making Research Results Freely Available For the Public
European Food Safety Authority (EFSA) Grants Public Access to Data through Scientific “Data Warehouse”
FDA ‘Taking a Very Light Touch’ on Regulating the Apple Watch
Selling your right of privacy at $5 a pop
From the Forum
In 2009 Tim Ngwena switched on Last.fm and he’s been running in across all his devices ever since. Earlier this year he decided to take a deep dive into his listening data to see what he could learn.
I realized that I was listening to the same old thing and I began to think about changing what I was listening to. But how can I change? Where can I start? I also wanted to learn something about my music, what I was listening to and who was behind the sounds. I decided to focus on music because it was doable.
In this talk, presented at the London QS meetup group, Tim explains how he was able to make sense of almost five years of data and learn more about himself and his listening habits.
What Did Tim Do?
Tim explored his music data along side additional information such as location data from Moves to learn about his musical tastes, listening habits, and explore new visualization and data analysis techniques.
How Did He Do It?
Tim exported his data, used the Last.fm API and some data cleaning and organizational tools to create a simplified and extensive database of his music listening history and associated data. He then visualized that data using Tableau.
What Did He Learn?
Tim learned a lot about himself and what the music he listens to says about him. He describes a few of the most interesting below,
Basically 80% of my listening comes form 10% of the artists that I have in my library.
I’ve listened to Erykah Badu for over a week (7.2 days). It led me to ask what is she saying to me?
Monday is my jam time. I’m listening from the morning into the evening.
I listen to music mostly when I’m walking.
Tim also learned a lot through the process of designing and creating his data visualization. The visualization, which you can explore here, made him think about being able to see the big picture when he has so much linked data.
I think context is important and you need to see all that information in one place and the tools I’m using allows me to do this.
Douglas Mason didn’t know who the Beatles were until he went to grad school. As a classically trained musician, he was blown away when he saw their unique chord choices. He started to investigate why the Beatles’ music sounded so good. Douglas created a shorthand musical notation to represent songs as strings and analyze things like melody, time signatures, chord changes, and lyrics. He describes his project and what he has learned in the video below. (Filmed by the Boston QS Show&Tell meetup group.)
A recent meeting of the Amsterdam Quantified Self group saw a talk about health insights gleaned through accidental lifelogging. The speaker (who asked not to be named) has bipolar disorder, and has been using last.fm over the past 7 years to track his music listening and compare it with his friends’ music patterns. He talks about insights he has gained using various tools that make use of last.fm’s API. For example, he discovered a pattern of listening intensely when he’s feeling good, and not listening to music when he is feeling depressed, usually in the summer. He also suggests it would be great to have a similar service for groceries, so you could correlate your mood with foods you eat. Watch his engaging story below. (Filmed at Amsterdam QS Show&Tell #3.)