Tag Archives: Self-Tracking
Dale Lane is a software developer for IBM living and working in Hampshire and he has been developing neat personal tools for his self tracking for the last few years. Let’s take a look at a few of them.
Tracking TV Watching
Inspired by the background data collection offered by last.fm designed to capture music listening habits Dale set out to create his own “scrobbler” to better understand his TV viewing habits. What he came up with is amazing:
Using a bit of code running on his media PC he is able to track a number of variables including time of day, what program he’s watching, his most watched channels, and many many more. Take a bit of time to check out his comprehensive blog post about the project and the TV Scrobbling project page.
Not satisfied while merely understanding what he was watching on TV, Dale took it upon himself to better understand how we was reacting to what he was watching. Using a webcam and a bit more code he was able to piece together a program that snaps a picture and then uses the Face.com API to determine interesting characteristics about the picture. The Face.com API enables him to see if he’s smiling as well as estimating his mood based on the facial characteristics that show up in the webcam shot. This little program has enabled him to find out some really interesting things such as:
He was also able to track his estimated emotional state while gaming and found some interesting insights:
This shows my facial expressions while playing Modern Warfare 3 last night. Mostly “sad”, as I kept getting shot in the head. With occasional moments where something made me smile or laugh, presumably when something went well.
These are really interesting and unique methods for understanding ourselves and our behavior. Dale’s work on self-tracking is fascinating and is an inspiration to those of us looking to expand our understanding of ourselves and how we interact and react with the digital world. Be sure to check out his blog for more self-tracking projects and interesting tools!
Every few weeks be on the lookout for new posts profiling interesting individuals and their data. If you have an interesting story or link to share leave a comment or contact the author here.
This is the first time we’ve had video of a new meetup’s very first gathering! Ciaran Lyons started QS Singapore, and recorded his introductory remarks as well as his own self-tracking story. Great to watch for people new to QS or thinking of starting a meetup group. Thanks Ciaran!
In the last session of the day, we had a few experimental talks on noticing how food changes physical condition. It was also an interesting series of talks that shows the importance of collecting our own subjective data to back up or refute the other technological data that we might also have access to.
I kicked off the session with my talk “Quantifying My Genetics: Why I have been banned from caffeine”. My colleagues and friends helped me quantify my behavior after one, two, or three cups of coffee by giving my agitation a number from 0-10.
I found out that I’m a slow caffeine metabolizer from my genetic results and it seems like there is a correlation between how caffeine affects me and my genes. My genes are not deterministic, I couldn’t have known how caffeine affects me without making my own independent observations.
On a fun note, the crowd guessed that I had one cup of caffeine today, they were right, I had a cup of tea earlier down in the restaurant, away from the conference.
Next we had Martha Rotter who talked about how she experimented with her diet to solve her skin problems after doctors told her there was not much she could do. She did one allergy test where the results said she was allergic to chicken and soy- but after cutting out both of those foods, she did not see any changes but it gave her the idea to test different food groups.
After her experiment with a chicken and soy-less diet, she tried a few other food groups, eventually hitting on cutting out dairy. Her skin cleared up within two weeks of stopping drinking milk, eating cheese.
I think the take away message from our two sessions this afternoon, don’t be afraid to do your own testing, trust in your results.
A colleague I’ll call John has decided to start tracking his mood for a long period of time (years). He explains why:
A few years ago, after a severe manic attack, I was diagnosed with bipolar disorder. The attack was preceded by an intense period of stress, then two weeks of elevated mood, increased social activity (hanging out and meeting people), and racing thoughts (hypomania). Then I skipped a few nights of sleep, wandered down roads in the middle of the night, and eventually became psychotic, in that I could no longer distinguish between reality and imagination. I was chased by cops on several occasions, and was involuntarily committed to the mental health wing of a hospital for a month. It put a massive dent in my life.
Family, medicine, and time helped me recover. Being out of control like that was fun only for the first two weeks. Having my life turned upside down was not fun either. As I recovered I became increasingly interested in finding ways to prevent a relapse. One doctor said: You have a vulnerability. You need to protect yourself. I agreed.
Looking back on the experience, I realized there was a rise in odd behaviors two weeks before I started to skip nights of sleep and fell into psychosis. There was an even longer buildup of stress, anxiety, and fear in the months before the mania hit. During the last two weeks before the mania, my behavior was different from what is normal for me. I felt elated and had a sense of general “breakthrough”. I suddenly felt no fear and anxiety. I felt on top of the world. I was constantly taking notes because ideas and thoughts were running through my head. I scheduled meetings and social activities almost constantly throughout these two weeks and shared my experiences as my new self. As I started to sleep less and skip nights of sleep, others later told me I seemed agitated and down.
Maybe it is possible to catch these early warning signs and take counter measures before they worsen into mania or depression. This is why I have started to track my behavior starting with mood and sleep. If I can get a baseline of my behavior and know what is ‘normal’ for me, it will be easier to notice when I am outside my normal range. I can alert myself or be alerted by others around me who are monitoring me. Long-term records of mood will also help me experiment to see which things influence my mood. This may give me more control over my mood.
Mood tracking might be a good idea for anyone to do, but it may be especially helpful for people with a bipolar diagnosis. Everyone has mood variation. For bipolars, however, mood swings can be more extreme (in both directions, up and down) , have far worse consequences (psychosis on one end and suicide on the other), change more rapidly, and be more vulnerable to environmental triggers like stress. The good news is that the first changes in mood can happen hours or days before more extreme changes. This gives people a chance to take countermeasures to prevent more extreme states.
The project name refers to the fact that Van Gogh had bipolar disorder.
The report is called The Social Life of Health Information, and has several interesting findings. Here is an excerpt:
Carol Torgan, a health science strategist, points out that anyone who makes note of their blood pressure, weight, or menstrual cycle could be categorized as a “self-tracker.”10 Add an online component, and you have the ingredients for a social health application or an electronic health record. Our survey finds that 15% of internet users have tracked their weight, diet, or exercise routine online. In addition, 17% of internet users have tracked any other health indicators or symptoms online. Fully 27% of adult internet users say yes to either question.
Wireless users are more likely than other internet users to track health data online. Eighteen percent of wireless users have tracked their weight, diet, or exercise routine online, compared with 9% of internet users who do not have a wireless-enabled laptop or other device. Nineteen percent of wireless users have tracked any other health indicators or symptoms online, compared with 11% of non-wireless internet users.
Separately, looking just at the 85% of adults who own a cell phone, 9% say they have software applications or “apps” on their phones that help them track or manage their health.
Sandy Santra gives a short, passionate talk below on turning Quantified Self data into knowledge. He tracks his migraines, time alone, happiness, meltdowns, panic attacks, and “zombification.” (I’d like to see a follow-up talk on that last one!) He gave the audience a framework for how to turn their own data into knowledge, for human improvement. UPDATE: Sandy has provided a PDF copy of his document, which you can download here. (Filmed at the NY Quantified Self Show&Tell #11 at Parsons The New School for Design.)
I recently received an email from someone having trouble keeping up with her experiment. While there is lots of general advice about discipline and motivation, this got me thinking about how doing personal experiments might differ. Following are a few brief thoughts, but I’d love to hear ways that you keep motivated in your quantified self work.
The desire to get an answer. The main point of an experiment is to get an answer to the initial question. “Will a Paleo diet help me manage my weight?” “Does talking less bring me closer to my kids?” Maybe the principle at play is that experiments which motivate start with great questions.
Built-in progress indicators. If you’ve set up your experiment well, you should have measures that come in regularly enough to keep you interested. This is assuming, of course, that you care about the results, i.e., that you’ve linked data and personal meaning (see below). But unlike other types of projects, maybe we can use the periodic arrival of measurements to stimulate our motivation, such as celebrating when new results appear.
The joy of satisfying a mental itch. Curiosity is a deep human motivation, and experiments have the potential of giving your brain a tasty shift – such as when you are surprised by a result. I especially like when a mental model of mine is challenged by a result. Well, sometimes I like it.
Sharing with like-minded collaborators. At a higher level of motivation, experimenting on yourself is an ideal framework for collaboration with folks who are either 1) interested in your particular topic (e.g., sleeping better or improving your marriage), or 2) are living an experiment-driven life. It is encouraging to get together with people to share your work, and to receive support, feedback, and ideas. Of course it feels good to so the same for them.
Desire to make a change. Finally, if we come back to why we experiment, there should be a strong self-improvement component to what we are tracking. My argument is that, ultimately, it’s not about the data, but about making improvements in ourselves for the purpose of being happier. If the change you are trying is not clearly leading that direction, then it might make sense to drop it and try something more direct. Fortunately, with self-experimentation there is usually something new you can try.
Underlying all of these, however, is the fact that the work of experimentation takes energy. Every step of an experiment’s life-cycle involves effort, from thinking up what you’ll do (creating a useful design), through running the experiment (capturing and tracking data), to making sense of the results (e.g., the “brain sweat” of analysis). Given our crazy-busy lives, there are times when we simply can’t take on another responsibility. So if you find yourself flagging and losing interest in one of your self-experiments, then maybe that is itself some data. Thoughts?
[Image from Steve Harris]
With all the disparate data streams coming out of Quantified Self tools, Stephanie Gerson saw a need to create a tool to bring them all together. In the video below, she presents her project Trackify, a new way for people to find correlations and trends in their data streams. Stephanie also puts out a call for building a Self-Trackers’ Bill of Rights. (Filmed at the NY Quantified Self Show&Tell #11 at Parsons The New School for Design.)
We see a lot of cool things here that people are experimenting with, such as health (sleep, water intake, mood) or productivity (interruptions, hours/day, attention), but we are also trying odder things. My interest is in widening the definition of what could be considered an experiment, so I thought I’d ask, what off-the-wall things have you tracked? I’m also curious to know what kind of support or push back you got from those around you, if they were social experiments. While maybe not terribly odd, here are some of the things I’ve tried:
- Experimented with ways to keep my feet warm while mountain biking in winter (tracked left/right foot comfort).
- Tried changing my thinking around positive events (tracked the event and whether it helped me feel happier to relive it later).
- Played with different ways to prevent “wintry mix” ice buildup on sidewalks (tracked likelihood of falling – with careful testing). (Are you detecting a northern climate?)
- Tested different kinds of one-day contact lenses (tracked ease of insertion, visibility, and comfort).
- Dressed better in public (normally I’m very casual), including wearing a hat (tracked psychological and physical comfort, reactions of others, including – surprise! – special treatment at businesses).
[Image: Office Board by John F. Peto
This is a guest post by Chloe Fan:
Hi! I’m a graduate student at Carnegie Mellon in Human-Computer Interaction, and I’m interested in learning about the barriers that you may encounter while collecting or reflecting on your personal information (e.g., too tedious to collect, information not useful, forgetting to collect).
I’m also interested in learning how long-term users have overcome these barriers. The area of personal informatics/self-tracking is not yet well-studied in academic research, so this research on how people respond and cope with barriers to tracking and reflecting can help us design better tools for tracking personal information.
This study consists of a short 5-10 minute online survey about the personal information you’re collecting, the tool you are using, and any barriers that come up during the collecting and reflecting process. At the end of the survey, you will have the option to enter your contact information if we can follow up with a phone interview. This interview should last about an hour.
If you complete the online survey, you will be entered into a $25 online gift card raffle. If you are chosen for the interview and choose to participate, you will be compensated $10 an hour.
Thank you, and I look forward to hearing about your experiences!
Survey Link: https://www.surveymonkey.com/s/F77P7Q7