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This is the eight post in the “Toolmaker Talks” series. The QS blog features intrepid self-quantifiers and their stories: what did they do? how did they do it? and what have they learned? In Toolmaker Talks we hear from QS enablers, those observing this QS activity and developing self-quantifying tools: what needs have they observed? what tools have they developed in response? and what have they learned from users’ experiences?
For me, some of the most interesting QS talks have been by those creatively repurposing existing sensor technologies for novel self-tracking applications — such as Mikolaj Habryn’s Noisebridge, at an early QS meetup, and Hind Hobeika’s ButterflEye goggles, at the QS Amsterdam conference. It’s fascinating to hear what the inventors are thinking long before their product is in the market. Here, Eric Gradman, master hardware hacker, tells how he is applying his skills to a focused life-logging application.
Q: How do you describe Facelogger? What is it?
Gradman: The Facelogger is a passive lifelogger that helps me remember every person I meet by creating flashcards of their face, name, where we met, and our conversation. Facelogger consists of an always-on videocamera necklace, a software suite to process the video, and a smartphone interface for reviewing the flashcards.
The camera is a commercially available Looxcie camera, which was modified with a prism so it hangs around the neck. This camera continuously captures activity, and has a button that allows you to save the preceding 30 seconds of footage (footage that’s not saved is automatically discarded). When I meet someone for the first time and they introduce themselves, I press the button. The camera preserves the previous 30 seconds of footage which hopefully includes a good video frame of the person, their name, and what they said about themselves.
When I next plug the camera into the computer, all the captured video clips are automatically uploaded to a server, and sent to Amazon Mechanical Turk. There, human beings identify the most representative faces from the video, determine their names, and even transcribe the conversation.
Facelogger gathers all the information and creates a Facecard, which can be reviewed later on a smartphone. A Facecard is like a flashcard, but it shows someone’s smiling face, their name, a map of where you met, a link to the video of the conversation, and often even a transcript of the introduction. I can search the text of the Facecards, sort them chronologically, or by geographic proximity.
Q: What’s the back story? What led to it?
Gradman: Like any self-respecting geek, I’ve always tried to stay a technological step ahead of my peers and a technological leap ahead of my parents. But when I discovered that my parents use the same model smartphone I do, I realized I was beginning to lose my edge. To me, the next frontier for personal electronics is wearable technology, and the natural application is self quantification.
But what to quantify? As a hardware hacker and artist, my first foray into QS wearable technology was definitely more for entertainment purposes. Called the Narcisystem, it was a biosensor suit featuring sensors for pulse, heading, EEG, pedometry, and breath alcohol level. I used the output of these sensors to drive the lights, sounds, and ambiance at a party venue. Fun, but not really a form of human augmentation.
I have terrible trouble remembering the names and faces of people I meet. Its hard to say which is worse: my face-blindness or my memory for names. I’ll meet someone, shake their hand, and we’ll introduce ourselves. Moments later I realize with panic that I’ve already forgotten their name! And hours later, if they’ve changed clothes, altered their hair, or removed their glasses, I’ll blithely reintroduce myself like we’ve never met. At least I’m not shy!
I’ve always wanted to offload the mental burden of remembering people. When I was in school and I needed to remember something I used flashcards. Why couldn’t that technique work for people too?
Q: What impact has it had? What reactions have you had?
Gradman: Because the Facelogger is a first-stage prototype I am its only user. Has it helped me remember people I meet? You bet it has. I’m amazed by the quality of the Facecards and by how effective they are at jogging my memory. I get the general sense that reviewing Facecards a day or two after meeting someone gives me an opportunity to properly commit someone’s name and face to memory at my own pace … something I simply cannot do “on the fly” as we meet.
There’s another purely psychological effect: because I’m confident that my technology is taking care of remembering for me, I can relax into the conversation. I was never shy about saying “hi” to people before, but I did experience stress over the fact that I immediately forgot their name and face. Now with that interaction captured and searchable, I’m not bothered at all.
I’m sensitive to the ethical concerns with capturing someone on video without their consent. When asked what I’m wearing around my neck—and as you might expect, that happens a lot—I never lie. I explain that I’m wearing a video camera to help me remember people I meet. Invariably, I’m asked “is it recording me now?” I’ve been asked to turn it off, and I always comply. But a surprising number of people tell me they want their own Facelogger. It turns out there’s demand for a device to help remember people’s faces and names!
Some have questioned the legality of wearing a video camera. But there are already cameras trained on us wherever we go. You can buy a video camera hidden in a pen, or a pair of sunglasses. Will our social mores (or our laws) surrounding cameras trail so far behind the technology?
Very few have actually questioned the morality of wearing a video camera. In the age of pervasive social networking we’re living highly examined lives. For anyone with a camera on their mobile phone, its not such a stretch to imagine wearing the camera around their neck.
Also, I’m careful to remove the Facelogger when I’m not likely to meet new people:at home, in a business meeting, etc. I do this because the purpose of this device is not to have a record of every conversation I have.
Q: What makes it different, sets it apart?
Gradman: Life-logging is always something that fascinated me, but I felt that an ever growing cache of unsearchable video of my life would just be a huge burden. Facelogger is an experiment in constrained lifelogging. By only capturing moments that share a particular characteristic and have common features Facelogger allows for a well-defined process of data extraction and collation that address a specific shortcoming.
Gordon Bell, the pioneer of life-logging described his always-on MyLifeBits image recorder as “write-once, read-never.” For me, the decline in storage costs is not sufficient reason to record my entire life on video. Huge amounts of unprocessed video is just video I’ll have to review someday! That’s why I find it so easy to resist the temptation to press the “capture button” more often. Unless I have automatic tools to convert video into a compact searchable representation—in this case, a Facecard representing a person I’ve met—the video just isn’t worth saving.
There are other tools out there designed to help remember names and faces. Evernote recently released Hello, a mobile app to record people. What distinguishes Facelogger is it’s passive form of information capture.
Q: What are you doing next? How do you see Facelogger evolving?
Gradman: Currently, a Facecard only expresses information captured in the 30-second clip. But APIs for face identification are getting really good. Soon the Facelogger will dig through my social network, and connect a Facecard to the social profile of the person it represents.
Next I will passively capture my meals, and use Mechanical Turk to help catalog my meals.
Face logging and food logging are only two well-defined applications of life-logging. I intend to identify others, and make them available as software for anyone wearing a compatible life-logging rig.
Q: Anything else you’d like to say?
Gradman: Face-blindness and poor memory for names are widespread problems! I designed the Facelogger with my own shortcomings in mind, but I’m now examining how I can make these tools more widely available, perhaps as a subscription service.
If you’re interested in updates on this project, have ideas to improve the system, or want to be contacted when the Facelogger service is available for beta-testing, please join the mailing list.
Platform: Currently, iOS. Coming soon to any HTML5 enabled smartphone.
Price: not yet for sale; to be contacted for beta-testing, please join the mailing list
(If you are a “toolmaker” and want to participate in this series, contact Rajiv Mehta at firstname.lastname@example.org)
Jeremy Johnson sent in this question for the illustrious QS Scientific Advisory Board, so we set about finding an answer for him. Gordon Bell and Seth Roberts responded with lightning speed! Jeremy’s question and their answers are below. If you have a question about your self-tracking that you’d like some help with, let me know.
My purpose is to track multiple variables related to sleep, exercise, diet and supplements to make evidence-based decisions
to increase my energy level.
Variables are tracked in a Google doc, http://docs.google.com/Doc?
My question is, what existing tool (iPhone or web) will minimize the burden of data collection so this is sustainable?
Gordon Bell’s Answer:
A couple of devices will focus on energy expended:
- BodyBugg captures energy expended using several measuring transducers;
- a plain old pedometer like the one from Oregon Scientific gives steps taken that is a stab at energy expended and it goes into your computer with no fuss or muss – all it requires is logging on to a site to be fed monthly.
Energy input (aka diet) is probably the most important and hardest to deal with. There are several packages like FitWatch that allow you to count calories. I did this for a few weeks to get the hang of calorie costs. A good kitchen scale is important.
Weight is important and change is just the difference of energy in – energy out. This says you really know your body. If you are overweight, reducing weight is clearly the easiest place to get energy!
Drugs: caffeine, vitamins, alcohol, etc. are all inputs I don’t understand or want to comment on. Less is probably more though.
Zeo looks interesting for sleep. A friend uses it. I haven’t bothered to try it because I am generally in a state of: What, me worry?
Stress. The BodyBugg actually tracks this through their skin resistivity sensor, but you can’t get hold of it. The company BodyMedia that sells them the device might make it available. This would tell how much stress one is under each day. A diary will have to suffice for now.
Seth Roberts’ Answer:
Jeremy, I think you are starting too big. You are trying to record too much. If I were you I would start by trying to record one thing day after day. It would be something I wanted to improve — maybe sleep or energy level.
After I’d managed to record one thing daily for several weeks then I would start doing little experiments. I would take one thing I can vary — say, how much coffee I drink. I start tracking it — measuring it each day. After several weeks, I would intentionally change it — say, drink less coffee — and see what happens for several weeks.
That’s three steps.
Step 1: Measure one thing you want to improve. Do that for several weeks.
Step 2: In addition, measure one thing you can easily control (e.g., coffee consumption, exercise) that might affect what you want to improve. Do that for several weeks.
Step 3: Change that thing you can easily control. See what effect that change has.
In other words, try to do the smallest easiest thing that will put you closer to your goal. That tiny little goal will be turn out to be much harder to reach than you imagine. In the beginning, the smallest easiest thing is to measure one variable day after day.
Thanks to Jeremy for the question and to Gordon and Seth for their answers! Wonderful QS readers, please send in your questions and we’ll do our best to find answers for you.
I recently came across Mikael Huss’ Follow the Data blog, which reports on data-driven trends in reality mining, self-tracking, and personalized medicine. In a recent post, Mikael talks about three bits of self-tracking news that are sure to create tingles up the spines of Quantified Self readers:
1. FitBit ships
At long last! FitBit, the accelerometer with the beautiful clip-on form factor and wireless uploading of exercise and sleep data, has arrived. A one-time fee of $99 puts passive motion tracking in your pocket.
2. DailyBurn launches FoodScanner iPhone app
Tracking your fitness and nutrition is going mobile. DailyBurn has a $0.99 iPhone app that lets you take pictures of the barcodes on foods you eat, helping you more smoothly track your caloric intake.
3. Gordon Bell and Jim Gemmell release Total Recall book
Based on their experience with the MyLifeBits project at Microsoft Research, Bell and Gemmell wrote Total Recall: How The E-Memory Revolution Will Change Everything. They talk about the future implications of being able to remember everything about your life in delicious detail.
These are definitely exciting times to be a Quantified Self enthusiast!