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New York QS Show and Tell #18 Recap

We had a great turnout at our last meetup in New York hosted at startup accelerator program Blueprint Health in Soho. Thank you to my co-organizers, Patrick Whitaker and Andrew Paulus , who helped pull together this recap. And thank you to the rest of my co-organizers Brian Gallegos, Mark Brooks and Konstantin Augemberg for helping out with another fascinating evening of demo and show&tell talks.

Demo Hour
Our latest demo hour included five presenters with concepts ranging from behavior change to respiratory training. QS attendees mingled around tables and engaged in interactive discussions with five demonstrators, who had come to present some interesting and diverse initiatives.

Susan Alexander from app4Mind presented a mental model she created for behavior modification. Susan was inspired by her own experience, those of others, and the world’s wealth of research on change, growth, and how to change behavior. The model distills all of this down to four memorable principles, each word beginning with the letter M. Together, they serve as a “mind app” which she presented in illustrated form. Susan is planning to launch a new website by year’s end to serve as a platform for app4Mind.

Matt Stanfield demonstrated BagIQ, a platform he is developing to give people product-level purchase data and insight into spending habits. BagIQ renders detailed product-by-product, dollar-by-dollar analysis, and presents them in simple, digestible ways. The power is in taking that product level data and connecting it to personally relevant 3rd party data specific to each user’s health, diet, ethics, shopping. Matt’s demo culminated with sweeping discussions about potential applications and insights that could be derived from the data and it will be interesting to see how BagIQ develops.

Melody Wilding presented eCaring, a care management system that seeks to generate comprehensive, real-time behavioral & clinical data from a patient’s home. eCaring was developed to enable hospitals, healthcare providers & families to track & respond to conditions, making early intervention possible, reducing hospital readmissions, lowering care costs, & improving care quality for seniors & people with chronic conditions. eCaring currently has several programs underway with hospitals & for long term care management.

Anthony Ina demonstrated a prototype of HealthBoard, which was developed to allow active duty military personnel the ability to interact with their own personal health information and electronic medical records, and to offer healthcare providers better access to patients and their decisions. By integrating information design principles, HealthBoard seeks provides users with enhanced and streamlined access to information, making it less intimidating and easier to understand the impacts of decisions on health outcomes.

Bez Arkush demonstrated a device that can measure inspiratory and expiratory breathing. Different resistance levels support breathing measurements and exercises to be used in respiratory therapy and respiratory sport training. The device connects with iPads and creates a game-like environment while keeping track of your activity.

Show&Tell Talks

Following demo hour, we had six show&tell talks on guitar playing, lucid dreaming, salt sensitivity, exercise, headaches and the unconscious.

Exploring the Sleep Frontier – Lucid Dreaming with the Zeo
The evening started with Dave Comeau, a lucid dreaming enthusiast who described his experiments hacking the Zeo to help trigger lucid dreams. Although Dave had been experimenting with lucid dreaming for many years, the launch of the Zeo Sleep Manager gave him fresh insight into his sleeping patterns, specifically about when he entered the REM sleep states most conducive to lucid dreaming. Dave introduced resources like Zeoscope and Sleep Stream Online and told of his experiments using the Zeo extensions to trigger visual and auditory cues with hopes of inducing lucid dreaming, although they often backfired by waking him up. Following the presentation, there was an interactive Q&A in which the potential of other sensory cues was discussed (e.g. olfactory or gustatory cues like using X10 to trigger a Glade PlugIn). When asked what drew him to lucid dreaming, Dave said “I don’t know what the benefits of those are — except being awesome!”

Exercise and Consumption
The next talk was by Emily Chambliss, who had completed several months of tracking her consumption and exercise in a comprehensive, color-coded spreadsheet. When asked about the motivation behind this effort, Emily noted that she didn’t trust her own perceptions, which is why she needed to start tracking. Informed by her nutrition and activity tracking, Emily was able to strategize, set goals, and implement greater levels of self discipline into her daily life. Over time she learned that her behavior was surprisingly predictable, and clear insights emerged about her self-described “lack of discipline on weekends.” In response to audience questions about the scope and challenges of her tracking project, Emily clarified that she tracked “everything — including booze, which was painful” and was quick to note that “a shot of whiskey has 64 Calories, according to most sources.”

Salt Sensitivity
Midway through the evening, we heard from Greg Pomerantz on a self experiment he had conducted on salt sensitivity. Greg noted that health authorities generally recommend salt restriction, which is controversial since people have varying levels of sensitivity to salt that cannot be addressed by blanket advice. Greg raised one of the challenges that “you need IRB approval when you do experiments on humans — except, you know, when you do it on yourself.” Thus empowered with the administrative freedom of n=1 self-experimentation, Greg weighed himself every morning and deliberately varied his salt intake through three phases over a period of several weeks. Although Greg had conceived this experiment since his blood pressure was at the higher end of the normal range, he was surprised by his findings that he was not particularly sensitive to salt, and moreover that the only adverse consequences he experienced (e.g., impair thermoregulation) seemed to be caused by insufficient salt consumption. Since his experiment, Greg has made a point to add more salt to his meals to ensure sufficient levels of consumption. When asked if he had talked to his primary care physician about this, Greg smiled and said, “not yet, but I’m sure he would be interested.”

200 Hours of Guitar Practice in a Year
Jake Jenkins had always wanted to play the guitar, and he told an impressive story of pursuing this goal with the help of commitment devices and Beeminder. Based on his prior experiences learning kite surfing, indoor rock climbing, and downhill skiing, Jake estimated he would need to spend 400 hours deliberately practicing the guitar to be “good enough” and set a goal of practicing for 35 minutes every day for two years. After mixed results and missed practice sessions at the beginning, Jake grew interested in commitment devices and discovered the website Beeminder.com, which helped hold him accountable on a daily basis and achieve remarkable consistency with his guitar practice. Although Jake said at the outset that “[he] would classify[himself] as without rhythm,” he has been continuously improving through one year and 200 hours of guitar practice, which is evident by the videos he posts on YouTube every few months to show himself playing. Although Jake found self-tracking to be a powerful motivator, he learned that it isn’t always enough and can sometimes use the assistance of external commitment devices to stay on track. Jake’s talk was a compelling example of using QS concepts to motivate and manage his efforts to develop a challenging new skill.

Figuring out a Headache’s Source
The next presenter was Michael Wenger, who implemented a series of lifestyle experiments in response to some startlingly vague advice from a doctor. Prompted by chronic headaches, Michael had undergone an MRI which revealed a benign brain tumor. Extreme risks ruled out surgery as a viable option, so a physical simply recommended that Michael “make some lifestyle changes” to try to reduce the frequency and intensity of his headaches. With this sudden burst of motivation, Michael made some critical lifestyle changes including easing the pressure of academic overachieving by electing some pass/fail courses, improving his sleeping habits and eliminating all consumption of alcohol. Michael used various mobile apps to track relevant activities, and over the short term, Michael learned that the best remedy for an excruciating headache was “driving a car with the windows down while having a milkshake.” More importantly, Michael learned that “you can fix things” over the long term by tracking relevant measure to increase awareness of lifestyle choices and making changes to improve your condition.

Storyboarding the Psyche
The final talk of the night was delivered by Cliff Atkinson, who started with the question of “how do you quantify the unconscious?” Interested in exploring such tendencies as procrastination in the context of knowledge about the unconscious developed by the early psychoanalysts, Cliff took a remarkably visual approach to his self tracking by tracking his body, emotions, and thinking through the creative use of iPhone apps, including Insight Timer and Penultimate. By importing clip art in the shape of a body and a head, Cliff created a template where he would visually annotate his feelings and observations each day, and he could zoom out in Penultimate to see many days at once and reflect on the visual storyboard of his tracking activities over time.

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New York QS Show&Tell #17 Recap

At our last meetup in New York, we had a packed house at NYU’s ITP, one of our great supporters of QS here in NY. Thank you to my co-organizers, Ben Ahrens and Brian Gallegos, who helped pull together this recap for the blog.

DEMO HOUR

Brad Hammonds and Stan Berkow gave a large-scale, real time demonstration of their web app StudyCure – an online platform that allows its users to create and run interactive experiments geared toward understanding their health in the best possible way. Each experiment is set up in an if…then… fashion (eg. IF I focus on breathing during the day, THEN I will be less stressed). This keeps experiments clean and simple and helps participants make meaningful use of their data that leads to positive change. StudyCure will eventually be able to compare your data with a range of population norms within a given experiment, giving you the ability to benchmark your results against the larger community.

Lead by Lisa and Dr. Mike Gerstenfeld, MD, along with their team of developers, Cloud2Health solves the problem of decentralized and disconnected health data from health & fitness apps and medical records. It does this by providing its customers with one centralized site which serves as “a single source of truth.” In an age of ever-increasing data streams, wouldn’t that be nice? A video presentation was given in a private demo room and projected on the wall while QS experts and enthusiasts crowded around. View their comprehensive video demonstration on the site!

Back in the main demo room, Kuan Huang and partners gave QS members a trial run on Feelytics.me – their iPhone app that allows you to log your ever changing emotional state and associate with your peers based on how they are feeling. The app is characterized by cute and expressive faces ascribed to each emotion and the ability to connect with others, centered on the feelings the faces portray.

Another and very different emotional state tracking platform was being demonstrated across the table by Dan Bretl. Emotish allows you to take a photo of yourself in a particular state (e.g., blissful, serene, calm, excited, etc.) and tag it accordingly. These labels then function a lot like hash tags on twitter and allow you to filter and search for photos of other users in a particular mood or mind state. This app offers a lot of potential and creative leeway for it’s users to search, follow, filter, crowd-source, and of course track their own patterns of emotional change as depicted by a photo journal.

Smart Diaper – this demo was just as cool as it is practical – one of those, “why didn’t I think of that” product ideas. Conceived and created by Yaroslav Fabishenko while taking a 4-hour car ride with his two kids in the back, the Smart Diaper harbors an embedded urinalysis patch that measures ketone bodies, ph balance, presence of certain proteins, and a host of other useful information for keeping on top of your babies health every time they… do their business. The diaper is linked with a phone app that lets you snap a picture of the test patch for the data to be logged and analyzed. Based on the analysis, parents may then, for instance, receive a message suggesting that their child be sent for a checkup or even a particular screening.

SHOW&TELL TALKS

Following the demo hour, we had four inspiring show&tell talks.

Autobiography Through Quantification

Christian Monterroza was inspired by On Kawara, an artist that self tracked each day of the year through paintings and newspaper headlines. He wanted to do something similar with his life and asked himself the question, “How can I know if what I’m doing is wrong if I never track what I do?” So he started a regimen of tracking. He found himself using several tools but soon became fed up and created his own tool. He used On Kawara’s work as an example of changing the power of a simple time stamp. He started calling his own self tracking time stamps “self portraits.”

His tracking consisted of sending postcards to friends of the city he was in and recorded everywhere he went in that city. He took this concept and gave it a name, Wrkstrm. To help with this, he built a tool that did the monitoring for him. It’s an application on his phone that automatically tags when he’s in certain regions.

Christian gained a lot of value from his tracking. He learned that it’s not all about numbers. It’s about the perspectives his experiences provided. He learned that sometimes we record the wrong things. For example, we spend a lot of time tracking obvious moments but serendipitous moments are getting lost. He also learned that passive tracking is better than active tracking and that gamification doesn’t really help. In the end, he succeeded in optimizing his day.

I Shot Myself: 365 Days of Self-Portraits

Next up was Sharla Sava with her photo project. Her project was to take a photo every day. But the rules were that a) she could never miss a day and b) she had to appear somewhere in the photo. She added the photos to a group pool on Flickr and collected feedback from the members. She found that having an immediate and responsive audience is addictive. She wondered if her self portraits were just for her and not really for anyone else. But she learned that self portraits, while not very practical, are also not trivial. They can be a site for public dialog.

For example, she explored how the body functions in journalism to send a message. She discovered how certain gestures communicating different messages based on the reactions from the Flickr group. She began to explore and capture a state of mind that’s difficult to convey.

While self portraits may not be meaningless, a question she set out to answer is how do we quantify the meaning? She found that the numbers are related to external factors. For example, Flickr tracks views, etc. She was able to draw conclusions from this data, but it didn’t really allow her to measure meaning. This project ultimately taught her something meaningful about her connection to the world.

Audio Jack Sensor Hack

This was Joel Murphy’s second time presenting at QS New York and this time, along with Leif Percifield, they showed everyone a project to find a better way of getting sensor data into a smart phone or tablet. The basis for their project is that once the data is in there, you can do anything with it. But getting the data into these devices is sometimes difficult. In fact, it’s fairly easy if you have a large processor, but an 8bit processor like the Arduino doesn’t work very well.

Their goal is to create a cheap way to develop hardware that gets data to a phone or tablet easily. So they figured out a way to essentially turn speaker outputs into digital outputs (analog waves to digital). They created a mini-IDE on the phone where you can type in calculations and mine the raw data.

Joel and Lief are hardware hackers trying to get more powerful data transfer from sensors and other devices in a cheaper way. In the end, they showed a quick and dirty etch-a-sketch that displayed the power of their new device. Joel’s notes from the talk are at Phone Jack Hack.

Spaced Repetition: A Cognitive QS Method for Knowledge Acquisition

The final presenter of the night was another veteran of the Quantified Self circuit, Roger Craig. Roger presented on the concept of spaced repetition. Spaced repetition is not about how fast we learn, but how fast we forget. Roger described how Hermann Ebbinghaus, a quantified self pioneer, spent decades of time on memory experiments with himself and discovered what he called the “forgetting curve.” The forgetting curve says that when you remember something, you will forget it, but the decay gets flatter and flatter the more often you are exposed to it.

In the 1930′s, Cecil Mace developed the concept of spaced repetition. With this, you take the forgetting curve and create essentially an algorithm to ping yourself with a piece of information you’d like to remember. You then optimize this process of review. So some information is reviewed more frequently when you first learn it, but then it’s refreshed less often later on as you are able to show fast recall. The advantage of this process is that you learn where to ‘aim’ your learning based on the speed at which you can recall.

Roger has tried many applications to practice spaced repetition and currently uses Anki. He learned that it’s a great way for self trackers to optimize learning.

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New York QS Show&Tell #16 Recap

Last week we had over a 100 folks attend our 16th NY Show&Tell with a Demo Hour held on Tuesday, May 8th at an incredible space that was generously provided by Digitas, a digital brand agency that has watched and supported QS closely over the years.

Thank you to my co-organizers, Ben Ahrens and Brian Gallegos, who helped pull together this recap for the blog.

DIGITAS LABS DEMO HOUR

Digitas Labs and Ben Ahrens assembled a fascinating group of QS members to share their stories, innovations and experiences in our first demo hour that had a real science fair feel. Some of the demos ran on some awesome touch screen devices provided by Digitas Labs. It started at 6pm with the following demonstrations:


Zack Freedman demos Optigon

Sandy Santra gave a lively demonstration of a truly unique DIY self-tracking system built for the iPad that not only charts psychological changes and their effects, but also provides users with full editorial control over data fields and allows them to customize their own personal experiments.

Kat Houghton, founder of ilumivu, displayed a wearable emotional state detector designed to empower people with the ability to tap into their own behavior and the behavioral responses of children with autism to help facilitate positive health and lifestyle changes.

Folks gathered in the Innovation Room as Alex Smith demonstrated his software called “Timebinder” which he designed to create visual timelines out of timestamped data — particularly useful for bringing asynchronous time series data from multiple sources into a single view for analysis.

Craig Dunuloff took spectators through a virtual blast into the past with his app Rewind.me. Where was that restaurant? How may friends were there? What did the gang do last night? This app allows users to get more value out of what they’ve done in their lives by aggregating data from other services such as Facebook, Foursquare, Tripit, Runkeeper, and more. It also lets you see and compare your activities to those of your friends and the world at large.

Amelia Rocchi gave QS members a behind the scenes look at InsideTracker – a web-based service that helps individuals optimize their overall health and performance by giving them a unique view into their personal biochemistry.

Christian Monterroza unveiled his time-tracking project that uses geo-fencing to passively track and organize daily activity. One of the most fascinating and helpful aspects of Christian’s app is that it allows the user to easily and personally allocate different regions of spaces for different activities, i.e., the park is for running; the freeway for driving; the living room for sitting; the grocery store for food shopping, etc. The app then takes over and auto-logs the activities based on its users geography. Fully customizable – NO LOGGING REQUIRED!

Zack Freedman (@ZackFreedman) was quick to draw a crowd with “Optigon” – a wearable wireless cyborg system that integrates with the user’s smartphone allowing him or her to access all data and keep it in plain site – even view nearby mobile user’s text messages, or as Zack puts it, “read people’s minds”! This awesome demo was every bit as impressive as it looked. Zack is currently seeking partners and investment to turn his devious device into the Arduino of wearables.

SHOW&TELL TALKS

Following the demo hour, we had four inspiring talks from QS members of the NY community.

How analytics improved my personal life and helped a losing soccer team

Stefan Heeke has a background in analytics and wanted to start using this skill for three self-improvement projects.

The first project was measuring his physical health. He was using the Fitbit to track his activity. He discovered that it takes some time at the beginning but then eventually he discovered what works for him. Specifically, he identified three areas: don’t eat fried food, cut out snacks, and cut out alcohol.

The next project was a daily journal. He decided to write down numbers to better understand how he feels each day. He found that he could gather some very actionable data by correlating the right metrics with each other. His approach is to identify both a positive and negative correlation to the activity. For example, he would correlate stress, whether he had a successful day, or general feelings of satisfaction. He also tracked his commuting time. He wanted to figure out how his daily commute impacts his mood. He found that as his personal time available decreased, his food quality decreased and his television time increased. Overall, he found that a) social days are good days, b) proximity to work is important, c) stuff in general has no impact, and d) TV is a time killer.

The third thing he tracked is how to apply personal metrics to a soccer team. He tried to model the most probable outcomes for certain soccer scenarios in terms of likelihood of success. As a result of the tracking, the team made it to the finals of the soccer league.

Ultimately, Stefan learned that whenever you apply data, it has a transformative impact and if you want to improve your life, data can help. He was also surprised at the number of distractions he ran into and how much that had an impact on his life.

Quantifying Diabetes

Jana Beck started her self-tracking journey with the goal of better understanding the impact of her diabetes. She was diagnosed with type 1 diabetes at age 19 and has been dependent on synthetic insulin for survival since. Her problem is that dosing insulin is not easy and is not a one-size-fits-all thing. It requires a lot of adjustment and impacts people differently. She set out to better understand her diabetes and better optimize her glucose management.

She started using a continuous glucose monitor on the back of her arm last year. This device transmits blood readings every 5 minutes and she gets trend and rate of change information. She has a target goal of keeping her readings between 70 and 130 mg/DL.

Her first experience was shock and her next was frustration. She found it hard to change her patterns. So she developed a hypothesis and set out to test it. Her hypothesis is that she needs to restructure her carbohydrate intake. The first step was to read a book on the topic (Good Calories / Bad Calories by Gary Taubes). The next was to use her monitoring device to track how her glucose changed based on her changes in carbohydrate intake. Her conclusion is that a low carbohydrate diet had a significant impact on her readings.

To run her analytics, Jana built her own statistical analysis program using R that tracks daily percentages over time for each type of blood sugar reading (carb-restricted vs. regular diet) against a target. Her program is called iPancreas and is available on Github.

Her next step is to try and start pulling in other variables (exercise, mood, etc.) to see how this changes her patterns. Ultimately, Jana’s self tracking project taught her how to best eat so that she can control her diabetes.

Walk all of Manhattan

Alastair Tse recently moved to NYC six months ago to work at Google. He hadn’t spent much time in NYC previous to moving here and wanted to better discover his new home city. Each day he commutes from 27th St. to 14th St. in Manhattan. One day he was trying to figure out the optimal route to work and wondered how many patterns are there to get from point A (home) to point B (work). He further extrapolated on this idea to see if it’s possible to walk all of Manhattan, and track it.

He started by writing down his walking experience in a notebook and just using general Google Maps. This turned out to be a bad idea because it wasn’t scalable and Google Maps can be buggy. So he built his own mapping app that uses Google Maps but allows him to map his own routes. The app tracks the streets he goes down and allows him to edit each route. It then tracks the routes he takes and shows his walking history.

He learned that it was possible to track something like where in a city a person walks and it’s very useful. In fact, he found that he hadn’t walked one square block north and one square block south of his apartment, much to his surprise. It got him to wonder, what other areas of the city is he often near, but never explored. The app helped Alastair adjust to living in a brand new city and has given him some ideas for places he wants to eventually explore.

How visualizing health problems could help solve medical mysteries

Katie McCurdy is an interaction designer with Myasthenia gravis, an auto-immune disease that causes muscle weakness in voluntary muscles She’s had it for 20 years and has been taking a drug to help the disease. She decided to take an alternate route and consult a holistic doctor. This was a new doctor so she was very motivated to make sure this new doctor understood her entire 20 year history with the disease. So she decided to make a timeline, from memory. She drew a timeline that included when she was feeling good and when she was feeling bad. She annotated the timeline for when she took certain drugs.


Initially, this was all drawn by hand. But as she worked on it, she decided to digitize it. So she next built the timeline into Adobe Illustrator so the graphs can be more accurately represented.

But it wasn’t enough to see all of her mood timelines separately. She wanted to overlay them so when symptoms go up and down, she can see how they are associated with each other.

Two variables she tracked were gut feelings (physical) and voice strength. These are two areas in which the muscle constriction has a high and very noticeable impact. This experience has helped her tell her story in a structured and coherent way and for that reason, this entire project has been helpful.

She learned that antibiotics were probably making her sicker, that docs are busy and probably skeptical of yet another patient created graph, that better health visualizations can be a great storytelling tool, and that memories are data too. Ultimately, she ended up being inspired and is currently doing more focused tracking in other areas of her life.

See our interview with Katie in an earlier QS post here.

Thanks to everyone who came out. We’ll get the videos up soon. See you this summer at the next NY QS Show&Tell.

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Marie Dupuch on Mood Tracking

-This review was written by Craig Protzel for my class DIY Health at NYU ITP (Tisch School of the Arts). In this class, students design systems of self-care that help people take stock of themselves by exploring ways to measure, reflect and act upon their health and lifestyle.-

Marie Dapuch’s “Mood Tracking” is very much focused on the qualified self and how the user feels.  Dapuch created a rating scale based on colors as a visual metric, and a self-reported quantifiable metric, to gauge her mood over periods of time.  While her process of assigning values is entirely subjective, and one might argue lacking in “scientific rigor,” Dapuch’s project is extremely relevant, highly impactful, and overwhelmingly touching.

Overall, she was able to design and develop a system of enormous significance in the improvement of her own life.  By implementing it on a mobile device, she successfully integrated the tracking process into her daily routine, allowing for even more in depth analysis.  All of this effort gave her the awareness and information to make confident choices in her own life, particularly to pursue a career path in advertising, to not spend so much time with her sister, and, most recently, to avoid the A train.  Her presentation is inspiring in that you clearly see how a simple yet effective system of self-monitoring can have such a positive effect on a person’s life. (Filmed at the NY Quantified Self Show&Tell #13 at NYU ITP.)

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Neema Moraveji on Perfect Self-Awareness

–This review was written by Ryan Viglizzo for my class DIY Health at NYU ITP (Tisch School of the Arts). In this class, students design systems of self-care that help people take stock of themselves by exploring ways to measure, reflect and act upon their health and lifestyle.–

Moraveji asks, “What would it be like to have perfect self awareness?” His talk suggests that having perfect self-awareness means having an optimized mind. He describes an optimized mind as one that is calm, aware, and emotional but not driven by emotions.  Moraveji points out that we can achieve this state of mind by changing and self-tracking our breath.  Moraveji focused on social influence and staring at a computer screen to test change in breath rate. I would like to relate his talk to exercise.

As a runner, it took me years of doing the sport to start understanding the importance of breath.  As we run we get better—run longer distances, feel better, and increase our speed. I realized that when I trained I trained my breath. I controlled my breath; which inadvertently taught me how to manage my body. This poses the question—Can we teach our body to regulate or does our body teach us to regulate?

Moraveji explains that breath connects all of the body’s major and vital nervous systems. If we use our mind self to regulate our breath, our body follows.  I would say agree with this notion. When I run I think about relaxation. I think about my breath being steady, calm and rhythmic. As I think about that I fall into my pace with my breath and my body’s nervous system follows. It all starts with my mind.

This process can be described in a first order feedback loop. Goal: become relaxed, efficient and calm during the run. Action: Thinking about and making breath rhythmic, calm and steady. Environmental distractions: increasing pace, other runners, weather, change of terrain, etc. Sensing/monitoring: BMP (breaths per min.) Comparing my states: Am I breathing slower and feeling calmer as I run? If so I achieved my goal. If not I go back to Action (to start loop over).

I see the breath as a function that is controlled by our mental intention. As we calm our breath it triggers the body’s nervous system to sit at a certain resting state. I think Moraveji is trying to make people aware of the fact that if we are conscious of our breath we can improve our self-awareness and in turn be more productive, happy, and clear.

One issue I had was that Moraveji only measures breath solely on breath rate. I feel like there are other parameters of breath that needed to be included in his study. The study also touched on social motivation. I think that the social motivation piece is not a constant in its ability to keep people self-monitoring.

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Ari Meisel on Curing the Incurable Through Self-Experimentation

Ari cured himself of Crohn’s disease by experimenting with some unusual supplements, nutrition and fitness regimens, and tracking every bit of it.

Four years ago, Ari was diagnosed with Crohn’s disease. After a couple of years of intense pain, sixteen pills a day, and yet another visit to the hospital, he decided to take control of his pain. So he started to track everything. His tracking regimen included exercise, supplements, sleep, food, etc. He used some popular tracking tools such as the FitBit, Zeo, and 23andMe. He correlated these metrics with how much pain he was in and his mood. The difficult part was trying to quantify the psychological component.

Ari learned to control the pain from Crohn’s. It took a certain combination of food, supplements, exercise and sleep, but the key was collecting enough data through experimentation. The other key learning from Ari’s work was that sharing the data is very important. Sharing included his friends, family, doctor, and others with Crohn’s. This sharing of data helped him analyze the data better and made him feel better about the task. (Filmed at the NY Quantified Self Show&Tell #13 at NYU ITP.)

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New York QS Show&Tell #13 Recap

Last month 75 QSers attended the New York Show&Tell #13 that was held on Wednesday, August 24th at NYU ITP, one of our regular sponsors in New York. Thank you to my co-organizer, Brian Gallegos, who helped pull together this recap for the blog.

Ari Meisel

Ari cured himself of Crohn’s disease by experimenting with some unusual supplements, nutrition and fitness regimens and tracked every bit of it.

Four years ago, Ari was diagnosed with Crohn’s disease. After a couple of years of intense pain, sixteen pills a day, and yet another visit to the hospital, he decided to take control of his pain. So, he started to track everything. His tracking regimen included exercise, supplements, sleep, food, etc. He used some popular tracking tools such as the FitBit, Zeo, and 23andMe. He correlated these metrics with how much pain he was in and his mood. The difficult part was trying to quantify the psychological component.

Ari learned to control the pain from Crohn’s, it took a certain combination of food, supplements, exercise and sleep but the key was collecting enough data through experimentation. The other key learning from Ari’s work was that sharing the data is very important. Sharing included his friends, family, doctor, and others with Crohn’s. This sharing of data helped him analyze the data better and made him feel better about the task. Watch Ari’s talk.

Marie Dupuch

Marie has fairly popular issue that many deal with everyday but she decided that it was important enough to start analyzing and understanding it better. The issue is mood and her solution was to track her mood three times a day. She created a scaling system from 1 – 5 with 1 being extremely low and 5 being extremely high.

Although she started with post-it notes, Marie created an iPhone app so she could track her mood on the go and started to notice patterns in her life that greatly contributed to her mood.

Marie learned that the best way to analyze her mood data was through visual representation. Her iPhone app gives her a visual way to understand her mood patterns in a quick way and enables her to correlate different mood data points on the fly. Her goal is to continue tracking her mood for self experimentation and share her application with others. Watch Marie’s talk.

Roger Craig

Roger Craig is a Jeopardy champion. But he’s not *just* a Jeopardy champion. He’s the record holder for the most money won in a single game in the history of the show.

But Roger isn’t some savant with perfect quiz show memory. Instead, he set out to find a way to look at the show from a historical perspective and try to understand what types of questions are asked, at what frequency, and for what value. He started by taking a database of all of the questions ever asked in the history of the game and creating a taxonomy to label the question types. He then mapped out the question types, values, and frequency on a plot and identified the highest value question types. Next, Roger built an application that gave him actual questions based on his desired type and value along with a timer to train himself to answer questions in a quicker fashion.

Roger learned that it’s more important to ask the right questions of your data than it is to just have the right data. Watch Roger’s talk.

Yury Gitman and Joel Murphy

We were thrilled to have Yury and Joel come out and demo their open hardware project called Pulse Sensor with the local QS community. The project tagline is “heart rate beats per minute for Arduino, lickety split.” and QS contributed to helping them reach the goal of raising $3,000 on Kickstarter. Read the QS post on Pulse Sensor. Watch Yury & Joel’s talk.

Tereza Nemessanyi

Already a successful businesswoman, Tereza had a couple big events in her life that resulted in major life changes. The biggest of these changes was the loss of a family member that was a primary support mechanism and life confidant. She didn’t know where to turn for advice going forward and had an idea. The idea was to go out and just ask people what they think, collect their feedback, analyze the feedback data, and give it back to the people that she asked. The result is her Web tool called Honestly Now, which is available for general use. All you have to do is create an account, setup a profile and start a conversation!

Tereza learned that collecting feedback from the crowd can help her make daily decisions and there is high value to just asking people what they think. Watch Tereza’s talk.

Adam Leibsohn

Adam was a successful marketing manager in the online advertising industry but he felt like there was something missing. As more and more online tools are collecting browsing behavior of people in an effort to offer more targeted ads, there is more information to filter through and a lot of data that just didn’t have value. He also realized that people have very unique needs and corresponding browsing behavior. How can I track my Web usage?

So he created his own application. voyurl is a browser-based tool that collects browser history and gives you a rich set of reports to help you better understand how, when, where, and how long you surf the Web. Some of the questions he set out to answer was:

* What kinds of sites to I spend my time on?
* How do I break my personal information filter bubble?
* How can I adjust my behavior to balance my browsing in more impactful ways?

Adam learned that by collecting Web browsing data, you can identify patterns to help you optimize your browsing experience and expand your exposure to different content on the Web. He also learned that the visual aspect of representing data and patterns is a very important catalyst for affecting change in a way that data in a spreadsheet just can’t accomplish. Watch Adam’s talk.

Thanks everyone for coming out. Planning is underway for our next event in October. Join the New York group on Meetup.

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Personal Data Visualization

In 2007, while training for an Ironman triathlon, one of the many daily QS rituals I did included waking up in the morning and strapping on my heart rate monitor before I got out of bed to measure my resting heart rate (HR). My coach had made it one of the mandatory data points I had to capture during the 10-month training period. If my morning resting heart rate was just 2-3 beats higher than the previous days, then that most likely indicated my body was fighting an infection and I needed to pull back on my training volume no matter how good I felt. I didn’t always follow the advice and in the graph above you can see 3 times when I did not heed the advice of my coach, kept training and then within a few days I got sick (resting HR spikes). I also like seeing how, over time, my resting heart rate decreased to around 50 beats per minute and was a reflection of my improved fitness level.

In the Reflection stage of Ian Li’s stage-based model of personal informatics, he makes a distinction between reflecting in the short-term (right now) and the long-term (later on). In the morning when I read my HR, I could act upon it that day and then over time I could review the data and look for trends and patterns with my coach and modify my training as needed. Visualizing a single variable is pretty straightforward, but add multiple variables and we see how giving visual form to all this data gets tricky. What are the methods and tools that help us visualize our data so that, in turn, we can create actionable knowledge?

At our upcoming first Quantified Self Conference we have created a breakout session specifically focused on how members of the QS community are using visualization tools and methods to make meaning out of their personal data. This is going to be a hands-on session and we want you to bring your data and visualizations and share what has worked for you and the kinds of challenges you face in interpreting the data. I’ll be joined by visual artist, Laurie Frick, who has used QS data of her own and data from Ben Lipkowitz to build really beautiful analog work. Also helping out will be fellow NY QS member, Paul Marcum, who runs the New York Data Visualization and Infographics meetup.

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Sleep Patterns by Artist Laurie Frick @ Edward Cella in LA

Over the summer at NYU’s ITP Camp for adults, I met the artist Laurie Frick who was making some breathtakingly beautiful sculptures and installations that looked a lot like our QS charts and spreadsheets. I encouraged Laurie to take a look at the data our community was producing.
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In Laurie’s words, “I genuinely think there is something inherently comforting in the visual pattern of daily activities both, sleeping and waking.  I started using Ben Lipkowitz‘s daily activity charts, and then got hooked on tracking my sleep data as well.” She draws from neuroscience to construct intricately hand-built works and installations to explore the nature of pattern and the mind.
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If you’re in LA, make plans to attend the opening reception on Saturday, February 12 from 6-8 at Edward Cella Art + Architecture or check out the work through April 2nd.
Laurie will also join us in May at our first Quantified Self Conference and will have lots of stories to share with us.
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New York QS Show&Tell #9 Recap

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Last night self-quantifying New Yorkers came out in the rain to witness another fascinating round of QS talks. A special thanks to our hosts Briana, Daniel and the crew at the digital innovation agency Zemoga. They’re doing some great work and be sure to check out their Follow Me app concept that they presented at our last Show&Tell.

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We started off the evening with designer Chris Woebken who critiques and interrogates raw-data driven transactions to uncover what it is that we’ve designed out of these experiences. His talk focused on our relationship to digital money where he melted an Oyster card (London’s electronic transport ticket) down to its RFID reader. It still worked. What do we lose as we move to cashless form factors? Can we design sensual experiences back into data-driven ones?
 
Then Kenneth Wright shared with the group his personal tracking experience using StickK to moderate his alcohol consumption. He’s had great success even though his referee won’t log in to StickK to support him but the group agreed that StickK could be used to trigger the referee to participate.

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Andrew Schaaf walked us through his very simple Mac app that logs data about how you’re using your Mac over time. Get Andrew’s MacLogger now on GitHub
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Robert Rabinovitz, a designer and educator, captivated the audience with his talk on mind mapping his own design process to a brain seizure he had in 2007 and the minutes leading up to the life-changing event.

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Colin Schiller an entrepreneur who, with the arrival of his new baby, saw a decrease in the elasticity of his own time. He undertook some very rigorous time management and productivity experiments using the Pomodoro Technique to discover that he netted out at about 85% efficiency.

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To cap off the evening, we had the pleasure of a visit from John de Souza, the CEO of MedHelp, the world’s largest online health community and a sponsor of the Bay Area QS meetups, to share with us his own personal self-tracking experiments and some of the incredibly detailed things that folks are tracking on MedHelp.
Thanks to everyone who made the evening possible. We’ll get videos up soon. See you again in December.
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