Re:View is a self-care system for taking time-lapse first person photos during your day.
Here are some drawing of my story board for my final video presentation.
The biggest thing to document in my process since I decided my first order loop is the process of wearing the camera was actually logging all the pictures I have been taking. The process of taking pictures brought many of the challenges my real system would require were it deployed.
Camera – I decided to use an old android phone I had for my proto type. It’s form factor allowed me to easily hang it from my neck. I looked into the Android SDK to develop an app that would take time lapse photos. The task seemed unnecessary and I started looking at the android marked for a camera app that would operate in the background and take time lapse photos at specified intervals. After a few attempts I finally found an app that I thought would work. After 3-4 attempts I finally got all the settings correct. I can open up the app and start taking pictures then press the power button and turn off the screen. At first I took pictures every 15 seconds, but this produced too many photos and would cause the app to take more photos than it could process. It had to change it to take a photo every 30 seconds. The main challenge that arose was battery life I could only take photos for 6 hours or so. So obviously the next prototype needs to use a different platform or android device
When to document – I am going to use the camera around the thanksgiving holiday. As I have been planning Re:View it has become apparent that the output will be very personal. I will be the best subject to test with for now. It seems like a lot to ask someone. “Let me use your life as a project”. Also the output of wearing the device is intended for personal use. Though there could certainly be instances where a user might want to share individual or series of pictures. The pictures I have taken during early testing have acted as strong personal reminders as I look back hours and days later.
Displaying the Output – I wanted users to be able to “play” through the pictures like a movie, and have some kind of timeline or processing the images to determine pre-identify when I go from one place to another. Geo-tagging also provided a means of sorting the photos by location. But turning on geo-tagging shortened my battery life too drastically so I had to keep it turned of at this stage of development.
The Picture included is of the first order and second order feedback loops for my self-care system. Review has the opportunity to interact with different kinds of behaviors. The sub goal diagramed in this set of loops is the first phase of wearing the camera and interacting with the photos the second loop is a specific reaction and goal. In this drawing my sub goal was to eat smaller portions. Some of my other sub goals are -eating smaller portions, walking more, spending more time outside, and reading longer. There are two phases of triggers. The first phase is looking at the image. Seeing the image will act as a trigger, once seeing the image triggers the opportunity for change. The reminders that you set for yourself delivered to your phone will trigger you to change your behavior.
For eating smaller portions, Re:View help you work your way down the purple path of increasing a behavior from now on.
The broader element I am becoming interested in is memory. How will our memories be affected if we have the ability to flip back through first person views of our past experience. This falls outside the typical design process we have outlined in class, but I will continue to think about it as my project develops.
I have begun experimenting with a possible proto type to take photos of my own experiences. I included the feedback loop for taking the stairs because I have chosen that as my action/goal. single loop could replace eating smaller portions in the feedback loop above, or both could be concurrent goals with separate reminders.
Final Project Brief –
My goal is to create a system that will provide photographic video feedback to help change behavior. Users will wear a camera on their chest. The Camera will take a photo every 30 seconds. The output will then be viewable as a video. The user will be able to look at their video and easily sort through the elements of their day. There are a few different elements of the project.
I am focusing on photography as the data. My intention is to have users better connect with their actions and goals. They will be able to see a visual feedback of their behavior. Seeing visual feedback will help users to identify behaviors they wish to modify in their lives. The first this I want users to gain is a better general awareness of themselves and their actions.
It is easy to say I want to be healthier but to visually identify opportunities to actually be more healthy will be a powerful tool to help people live healthier lives.
There are a wide range of behaviors that the interface could be used to target;
smoking cesation, drinking less frequently, get more exercise, go to bed earlier, eat healthier, ect.
All of these are broad and general. Through watching your footage you could say things like “Do not smoke on my lunch break”, “Get iced tea with dinner on week nights”, “Walk home from work on wednesdays and fridays instead of taking the train”, “Read in the evening instead of watching an entire movie”, “Do not go to shake shack for lunch”.
When users have an opportunity to see first hand their actions and identify them
Below are some of my notes and sketches about the early stages of my final project
These are three 1st order feedback loops. The first two are for Stretching in the morning and taking the stairs at ITP when I go to class. The third diagram is for anti-lock braking systems.
For the stretching loop I focused on setting my alarm 10 minutes early to allow myself extra time to stretch when I first wake up. My Goal was to stretch when I wake up. My comparator was whether I stretched or not when I woke up. My action was to set my alarm early and stretch when I wake up. The environment is me stretching. Disturbances that I identified were forgetting to stretch, being tired or lazy, and sleeping through my alarm. I am the only sensor that determines if I did stretch or not.
The second loop I diagrammed was to remind myself to take the stairs at ITP when I have class. My goal was to take the stairs at ITP, not the elevator. My comparator was did I take the stairs when coming and going from the floor. My action was to remind myself to take the stairs by sending to myself a text based on when I have class. The environment is me taking the stairs. Disturbances to the system are me being lazy, forgetting my phone, not having service. I am the sensor in the system.
For the third diagram we were assigned to diagram something totally outside our interest. I choose to diagram anti-lock brakes. I was inspired by Steve’s example of a carburetor. The goal is to keep traction on the road surface while braking. The comparator is weather all of the tires have traction or not. The action of ABS is to pulse each brake to maintain traction on each wheel. The environment is the wheel and contact surface on the road. Disturbances are things like road conditions, speed, and hazards. For sensing ABS systems use a controller and a magnetic wire to determine if each wheel individually has traction.
I used the Fogg behavioral grid to assess my approach of the issue of trash in my lobby. When I initially concerned myself with the issue I saw it as a black path. It was something that thought of as a stopping behavior. All of my previous attempts at modifying my neighbors behavior had been negative feed back. And with and ultimately response. So It started to become more clear to me that I would need to restructure my approach to a blue path “Do familiar behavior from now on.” That seems easy enough, Keep the lobby clean from now on. So I added signage, that read “A clean lobby looks and smells better for us all, Have a great day”. This was combined with the specific location associated with the greatest collection of trash and just a little bit of positive feedback. Both rounds of directed changes to my approach have seen measurable improvement. There was only trash in my lobby on one occasion last week. My building got a new trash man. Which might have impacted my outcomes. He comes more frequently and is here for longer, So I think people see him more frequently. As a subsequent observation I think seeing him in person affects weather people make a mess more than any of my signs.
Not sure about the taxonomy of behaviors. I want people to feel good that they are keeping the lobby clean. Not attacked for making it dirty. But I am not sure what behavior other than taking everything you bring into the lobby out is involved.
Each pic is a slide right. 2 slides. I tried to keep them simple. It kept rotating my pictures and not letting me save changes, sorry. Download and rotate.
Acceleration of Addictiveness
This article reminded me of a speaker from Applications last year. (eeek I do not remember her name…the internet tells me it is Linda Stone http://radar.oreilly.com/2010/06/glenn-fisher-recently-posted-o.html). She talked about how we live a “post productivity era.” There are elements of life that are changing due to the growth and abundance in society. Affecting so many areas of society. The discussion of addiction seems like a consequence of a post-productivity era.
A Behavioral Model for Persuasive Design
I liked this article a lot. My biggest issue was that it said ALMOST EVERYTHING I usually say when I talk about an article in its last few paragraphs. “By using this framework, we can look at our own persuasive designs.” This was the most helpful element to me. The FBM uses a good system to breakdown the various elements that come in to play when persuading. It seems like you could use it as a checklist to assess nearly anything. As we see more and more interactivity these thresholds will require designers attention. Accurately assessing ability, motivation, triggers, and timing while people are constantly interacting with changing technologies will continue to create unique design challenges.
Self-Experimentation: A Call For Change
Self-experimentation is awesome. Is is super relevant to our discussions surrounding health as it pertains to this class. For me it creates a huge opportunity to learn. I think our brains interpret data and experience differently when we go through it. Self-experimentation is one of the easiest and most accessible sources of information we have. As designers and thinkers if we can integrate self-experimentation into our processes our ability to learn is expanded greatly. The article mentioned learning curves, the idea of time as a design element is very important to me, learning curve has always connected greatly with successful process design. The supply of self data can dramatically shorten learning curves.
I liked her talk, it was brief but the questions were good too. There was even a NYU shout out. I enjoyed when she said there is a point when you should burn your note book (or stop looking at the data if you possess the strength). The word needful was powerful. For many people QS can serve a very needful purpose and can lead to targeted and powerful results. But Quinn makes a distinction between tracking and action.
I randomly clicked this one which, sounded interesting. BOOM. Itp. jeopardy. Awesome. I am an avid Jeopardy watcher. I have also made out a bunch a strategies based on that experience. Must know categories, common mistakes, go-to answers, and general answer snipe-age. I have forced this love on many people, which provides even more data. People seem to easily get hooked on group jeopardy watching (not the ideal conditions for tracking though).
The part I connected with most is the predicted self. I think i can predict a rough likelihood of getting a question right based on category and question value. Isn’t that the premise of a daily double?
PS. OMG I was going crazy about how familiar Roger Craig looked. THAT guy. I was BLOWN AWAY by his skills. Zaq (some of you may know him) has been my constant jeopardy cohort for 3+ years (borderline unhealthy). But as we were watching Roger play we discussed multiple times his strategy. Particularly his wagers on daily doubles and on his buzz-in selectivity (mostly he rarely missed a question). Kudos Roger. Game/Learning Optimization.
General: Quantifying behaviors can make a lot of things easier. But obviously there are cases where it may not be helpful or could actually stifle your ability to accomplish a goal. Most of these issues are design problems and can probably be worked around. I would say QS is a discrete way we can understand information about ourselves and our bodies, this understanding should aid our decision making process if applied well. A shared language or vocabulary is very important to collective growth of a field. More people working communicating and collaborating will lead to much more learning.
I am not really sure where this is all headed. I like the movie Gattica, but I do not want everything to turn out like that. I would cite the movie the island. Aside from the human clones as insurance policies