Jetlag and Sleep – Data Visualization with SleepCycle for iPhone

I recently flew to Istanbul, Turkey for part of my book tour on Calm Technology! I always use the SleepCycle app (iPhone and Android) to track my sleep and wake me up in the right sleep cycle. I came back with some great Jetlag graphs this time and wanted to share!


Sleep Cycle App


A Good Night of Sleep

Here is a graph of a solid night of sleep for me. The ups and downs are different stages of sleep. Some are deep, and others are REM sleep where I have dreams!



Jetlag Graphs


Apr 08 – First night at the hotel in Istanbul 

This is a graph of the first night of my trip. I took a melatonin pill 30 minutes before bed and listened to a podcast to fall asleep. I stayed asleep until 3 or 4 in the morning and tried very hard to go back to sleep. Eventually I did, but at a cost to my overall sleep. I can always tell when I have Jetlag when I have very plain sleep graphs without any REM sleep, and this one shows the Jetlag well!



April 11 – Another night of Jetlag 

I slept better through the night this time, but I ended up waking up a few hours before my alarm clock. You can see it at the end of the sleep recording below.



Back in the United States – More Jetlag! 

The first night I got back from the trip I took a melatonin and went to sleep around 9pm. Then I woke up at 5am and tried to go back to sleep I had to be up around 7a for a speech at Design Week Portland! You can see the little dip between 6 and 7am where I managed to kind of fall asleep before being woken up by my alarm clock.



Jetlag without Melatonin 

I had a long and exciting day at Design Week Portland and fell asleep as soon as I got home. I fell asleep so quickly that I forgot to take any Melatonin, so I woke up around 3:30am. I tried to go back to sleep a number of times, but failed. Finally I fell asleep at 6am, only to wake up around 7am (before my alarm clock went off). I got dressed and headed to give a talk at University of Oregon’s What is Media? Conference! I was exhausted, but exhilarated. The conference was absolutely fantastic and kept me very awake!



14.5 hours of sleep (and dreams!) 

After two days of conferences, I was really worn out, but I was also very satisfied. The next day was Sunday, so I planned to sleep in. I set my alarm clock for 1pm so I could sleep as long as I needed. I popped a Melatonin and played a podcast to go to sleep. The result? 14 hours of sleep and a lot of great dreams. This is how I knew I was back to normal. No more flat line sleep!


What do you think? Do you record your sleep? What’s the best night you’ve had? Worst? Do you record your sleep and watch your own Jetlag as well? What’s your best tip for getting over it?

You can also download SleepCycle here!

The History of the Compass Lifelogging Application

In 2012 Chris Dancy went to Amber Case’s CyborgCamp, an unconference on the future of humans and technology. He wanted to show her a project he’d been working on for the last three years, over 600 different datasets of Dancy’s locations, activities, sleep patterns, weight and other data, color coded and synchronized with Google Calendar.

Amber Case & Chris Dancy

Origins of a mindful cyborg: Case and Dancy at CyborgCamp Portland 2012 and in 2015.

With this much data, Dancy was able to gain an entirely new perspective on his life. He was able to correlate sleep with weight, sadness or happiness, or even the effect of air quality on his driving.

For the first time, all of these different data sets were in one place – the ultimate personal perspective. Case was excited to see this and suggested he show it during an unconference session. Though Dancy was nervous – this was his private data after all – Amber didn’t give him a choice. Case switched the projector on to show Dancy’s work to everyone in the room. The work inspired dozens of questions and a long discussion. Klint Finley, a reporter from Wired, was part of the session and wrote an article on Dancy. The rest, as we say, is ‘Christory’.

Chris Dancy's Google Calendar

Chris Dancy’s lifelogging Google Calendar.

The World’s Most Connected Human

One year later Chris made his way into the larger world as “The world’s most connected human”. He’d stopped smoking and completely changed his behavior, but there was one problem – only he could use his system. It allowed him to see activities in a new way, lose over 100 pounds and significantly improve his life, but the system was an expensive undertaking that required a lot of time and effort. Dancy wanted others to be able to see their lives over time. It didn’t seem feasible or fair that we might need 600 applications and devices in order to understand their lives. With so much data, we run the risk of becoming so connected that we don’t have any time to reflect. Dancy wondered what anyone might be able to do with just the sensors on the phone. Case suggested he find a company in the space and seek their support.

Building an Application

Compass Application

Preview of the Compass app for iPhone.

A few years later, Chris found Healthways, a Nashville-based company with success in the wellness industry and recruited Case to work with him. Healthways invested in the project, and this week, the first results of their collaboration, an iPhone app called Compass was born. Tracking behavior is useful only when you can connect to other behavior in your life. Compass surfaces insights from your phone and shows you how you live your life. Too many hours at the office? Eating right? Flu got you down? Too much phone light affecting your sleep? Compass helps you to see what’s affecting you, and how it affects you. Our vision with Compass is for it to be an interface for your life, and to change your future. In a world of non-stop information, we could all use a bit of reflection – followed by action!

Join the Compass Alpha!

Compass is being made available as an alpha to attendees of the Quantified Self Conference on June 18-20, 2015 in San Francisco, CA. Interested? Sign up for the alpha at, or stop by our conference booth during QS15 and say hello! Or check out @mycompassapp on Twitter.

Sign up for the alpha!

Where do we go from here?

We’ve tried to distill the best methods and insights from Dancy’s tracking process, but it will take time to get there. We’re looking for feedback and soliciting people to become alpha testers for the app. There are so many non-connected devices out there. It’s not about what you track – it’s about what happens when you tie what you track together. We’d love to know how we can improve Compass to help you understand your life better.

Device Ecosystems and the Quantified Self

The current state of Quantified Self Devices is the model where every device has an API and a corresponding app with a sharing ecosystem.

Why won’t this work long term? Each device and social ecosystem wants you to completely buy into their entire world. This presents problems with privacy and data ownership. Customers have to to trust that they are handling your data properly, letting you share with who you want to share it with. In addition, if you request that your data and account is deleted, you must trust that the company will delete it. Device APIs are designed not to get data out of them in the best way, but to display content. Furthermore, if the a device-making company is dissolved, you will lose all of your personal data.

Current Quantified Self Device Ecosystem

Current System

Aaron Parecki and I were sitting at the back of an Quantified Self APIs discussion led by Eric Jain when Aaron realized that there was something wrong with the current way quantified self devices are built and marketed. He quickly drew up a series of diagrams and later wrote a post, The Future of Quantified Self Devices. This post attempts to highlight some of the key points of his arguments.

The Ideal Quantified Self Device Ecosystem

Ideal System

In this model, device manufacturers are making tracking devices. Some of them will require a cloud service to get the data off of the device, because its easier to build the hardware that way. The difference here is that the device’s cloud service is not an API. It’s a synching service that ships data from the device to your personal server.

How does this work? You have a personal server, a virtual or physical server that you own that you can selectively grant access to these devices to be able to insert data. Then you can also selectively grant access to aggregator services or analysis services to be able to read the data or give you visualization on it. There’s another added benefit. Device manufactures are freed from the obligation of building an app, website, or social network. Entire companies can be dedicated to software. Hardware providers can focus on what they’re really good at; the hardware. Ditto for software providers.


Read more about The Future of Quantified Self Devices by Aaron Parecki.

Track Your Happiness Survey Results, The Quantified Self, and Emotional Feedback Loops is a research project that investigates what makes life worth living. It was created as part of Matt Killingsworth’s doctoral research at Harvard University. I found the project while browsing the Internet one night and decided to sign up. Here are my results:

Track Your Happiness Results for Amber Case

How does it work?

Once you sign up for TrackYourHappiness, you get asked some preliminary questions for statistical purposes. This takes about 10 minutes. Then you get sent 50 survey requests over the next month or so. Completing them gives you a picture of your happiness levels over time, as well as a number of other pieces of data that relate to happiness. The questions often asked me about how much sleep I had received the night before, or if I was talking with anyone.

I was able decide when and how often I wanted to be notified. I opted for survey prompts to be sent to me at random intervals, three times a day, to report how I was feeling and what I was doing.Because I knew I would never complete the survey if I was sent survey prompts by E-mail, I opted for SMS, eventually switching to Direct Messages from Twitter. The direct messages ended up working out the best. I received direct messages from @trackhappiness on Twitter 3 times a day, and filled them out over a period of 3 months, starting in April and ending today, July 1st.

Even with Twitter notifications, I should’ve finished sooner. 50 samples should only take half a month or so, assuming 3 are sent completed per day. However, the surveys were quite long and rather repetitive, each of them often taking 3-5 minutes to complete. I became rather fatigued of the project at the end of May, which resulted in my skipping 126 survey prompts. I let the prompts run their course on my phone through the entire month of June before I decided to break down and fill out the rest of them. That was two weeks ago. I’m finally done.

Productivity and Happiness

Track Your Happiness - Productivity vs. Happiness

My initial hypothesis was that I would be the happiest while being the most productive.

The results seem to imply, and I also noticed this while filling out survey results, that I am often tired while being very productive. Thus, high levels of productivity don’t always make me completely happy.

Additionally, productivity is tiring, so my happiness is dependent upon how I feel physically. Sometimes I’m happiest while doing everything I can *not* to be productive.

Happiness: Outside vs. Inside

Track Your Happiness - Outside vs. Inside

I found that I’m pretty much the same outside as I am while inside. (Caveat 1: I reported being outside while I was in a vehicle. Caveat 2: This survey was taken in the spring/summer, where being outside is generally awesome).

Happiness vs. Want To, Have To; Don’t Have To; Don’t Want To

Track Your Happiness - Tasks: Want To vs. Don't Want To

These results seemed a bit obvious, thought I expected that I’d be happier when doing things I wanted to do, but didn’t have to do. Instead, I reported being slightly happier doing things I wanted to do and had to do, vs. wanted to do, but didn’t have to do. And of course, I wasn’t as happy to do things I both didn’t want to do as well as didn’t have to do.

One item is missing here – the Don’t Want To, Have To. I guess I never responded with anything I didn’t want to do, but Had to Do.

Focus and Happiness

Track Your Happiness - Focus and Happiness

I’m very unhappy when I’m having a fragmented thought process, and the happiest when I’m fully focused on something. This could also be related to productivity.

Happiness: Amount of Sleep and Sleep Quality

Track Your Happiness - Amount of Sleep, Quality of Sleep

One night I got 18 hours of sleep. I forgot what night that was, but it must have been after waking up at 4 for a early morning flight to San Francisco, and getting back late at night. Who knows? Regardless, I was not very happy after I woke up. Oversleeping is not something I enjoy very much.

Other than that, as long as I get 7-10 hours of sleep, I’m pretty much fine. For some odd reason, I never took the survey after 5 or 4 hours of sleep. Those amounts always make me unhappy. My brain won’t cogitate correctly the next day because it hasn’t had enough REM time to defragment itself to make room for new ideas. Oh well.

Happiness: Being Alone vs. Being With Others

Track Your Happiness - Being Alone, Interacting with Others

I consistently talked to a similar variety of people over time, and my happiness was about the same. The only reason I might not have been as happy when talking with friends might have been due to the context of the conversation.

Often, friends let on more personal information than acquaintances might. An acquaintance, for instance, might be more concerned with keeping a situation upbeat and not diving into complex or potentially unsettling issues, stories, or problems. I don’t think I really encountered any of that, no do I on a normative basis. However, if my level happiness around friends were significantly lower than with the other types of people, I would suspect that this might be the case.

Happiness vs. Activity

Track Your Happiness - Happiness vs. Activity

Most of these responses were given during the time when I was moving into a new place. My favorite activity is, and may always be, writing on a white board. I was the least happy when I was “relaxing”. I typically don’t relax. Rather, my body forces myself to take a break. To me, relaxing is sleep. I try to get a lot of it. When I’m awake, I try to get things done.


Now that the survey is over, it’s nice to have this data. If I were to do this again (and I might in 6 months), I would probably not use this interface. I’d rather build my own, and then run correlative tests in the background to net useful outcomes, not outcomes that were almost completely obvious upon answering the daily questions.

An amusing side-effect of being finished is that I keep getting phantom notifications. I think that I’m getting a direct message from @trackyourhappiness with a request for data. I won’t be getting them anymore.


This survey did one very good thing: it caused me to consider my happiness quite a bit. I was very aware every day of all of my thoughts and actions. I wanted to predict what the results would be, even though it was quite obvious what the were going to be. I found that it was pretty simple to control my happiness. Also, I realized that I’m a generally happy person because I have artificially constructed an automatic feedback loop that reinforces positive environmental conditions.

For instance, sleep quality showed some pretty good results. Of course I was unhappy with a sleep quality of 0 or 30. These results are quite obvious. 100% sleep quality pretty much always meant a pretty high level of happiness.

Which means I’m a pretty simple creature. I’m happy when I’ve had enough sleep and food to eat at regular intervals. Though food was not part of the survey, I’ve been tracking food intake, time, amount and type for the last year. It really matters.

Does this mean that one can architect a feedback loop of good sleep and healthy, regular food intake in order to ensure perfect happiness? Is there a programmatic approach to perfect happiness?

As an avid social experimenter within the game The SIMS, I’ve had a chance to test all of the variables and scenarios that one can have, or be denied, and the effects on one’s happiness due to those things. In the game, one can achieve a 100% happiness level based on a number of factors which include, hunger level, cleanliness, restroom need, social interaction need, surrounding environment (if a SIM is in a messy or badly formed house, they are more likely to be unhappy) and level of rest.

In a way, I would’ve liked this survey to have more of those items. That way, it might have been able to educate people about their dependence on these external effects.

For instance, I moved into a very specific type of living situation because I had programmed it out in the SIMS and saw that it had all of the requisite items for self actualization. It’s more than just sleep quality. One must have an environment that makes quality sleep possible, and a work situation that is not so stressful that it prevents sleep. Elements of the house, commute, food, ect., are all important.

Finally, I thought the project very successful in integrating with Twitter/SMS, because I would never do it if I received an E-mail notification three times a day. SMS/Twitter integration allowed it to meld more smoothly into the processes of my everyday life.


It left out a lot of things, like the last time I ate, what I ate, how tired I felt, how stressed, ect. These have a lot of bearing on happiness. Sometimes it asked me if I was thinking negative thoughts. If I said yes, it asked me if I could control these thoughts if I wanted to. This was as close as the survey got to getting at some sort of psychological effect determining happiness. The only other things it tracked were location, socialization and sleep. For me, it’s obvious that getting a bad night of sleep affects my happiness.

I’d like to know if my eating habits or times affect my happiness. There’s a lot more that can be gathered here that the survey failed to capture and record.


Amber Case, (@caseorganic) is a Cyborg Anthropologist studying the interaction between humans and computers and how our relationship with information is changing the way we think, act, and understand the world around us. She’s obsessed with compressing the space and time it takes to get data from one place to another, especially when the final destination is the mind.