Tag Archives: Apple

What We Are Reading

Ernesto is in sunny Austin for SXSW, so I’m filling in to gather this week’s articles and links for your reading pleasure.

Articles

Apple ResearchKit concerns, potential, analysis by MobiHealthNews. ResearchKit was a big surprise coming out of Apple’s Special Event this week. It was quite difficult to select just one representative article about the ensuing conversation, so this round-up serves nicely.

#WhatIfResearchKit: What if Research Kit actually, truly, worked… by Christopher Snider. Okay, I failed to keep to one article on ResearchKit. This post chronicles a series of Twitter conversations on the question: if ResearchKit does work, what are the possibilities?

The Electric Mood-Control Acid Test by Kevin Bullis. Thync is a sort of evolved version of a transcranial direct current stimulation (TDCS) device. A technology with a lot of potential and controversy, this article explores why the brain-enhancing effects of the TDCS only work for some people. By the way, if you are a fan of Philip K. Dick, Thync may remind you of the mood organ that was in Do Androids Dream of Electric Sheep?

Automated Learning by Nichole Dobo. Some school classrooms are experimenting with ”Blended learning”, a method of combining classroom teachers and computer-assisted lessons. A detail that stuck with me is the description of three large displays that show where each student is supposed to go that day, based on the results of the previous day’s lesson.

The Mouse Trap: Can One Lab Animal Cure Every Disease? by Daniel Engber. An in-depth how science’s predominant use of lab mice could be limiting our knowledge of disease. Of relevance to self-trackers because many models of optimal health are in part based on mouse studies.

Show&Tell

2014-Average-Sleep-Stages-by-Day-of-Week

Analyzing a Year of My Sleep Tracking Data by Bob Troia. This is a superb exploration of Bob’s sleep data from 2014 as collected by his Basis watch.

report_1

Notes on 416 Days of Treadmill Desk Usage by Neal Stephenson. The author of Snow Crash and The Cryptonomicon is a long time user of a treadmill desk, but when he began having pain in his left leg, he had to reevaluate how he used his favored tool.

Visualizations

 

1*XIujdCx2G0fe7htb1Gk5YQ
Qualities of #QuantifiedSelf by Christina Lidwin. A fascinating analysis of the #quantifiedself hashtag.

Access Links
First medical apps built with Apple’s ResearchKit won’t share data for commercial gain by Fred O’Connor
Talking Next-Gen Diabetes Tools with Dexcom Leaders by Mike Hoskins

From the Forum
Mood Tracking Methods?
Howto track laptop uptime
CCD or CCR conversion tools?
What gets measured, gets managed – Quantified Self in the workplace
Best ECG/EKG Tool for Exercise
Best iOS app to track water/coffee/alcohol intake?

This Week on QuantifiedSelf.com
QS15 Sponsor Highlight: RescueTime
Quantified Self and Apple’s ResearchKit
Better by Default: An Access Conversation with John Wilbanks
QS15 Conference Preview: Jamie Williams on Tracking My Days
Quantified Self Styles

Lastly, I’ll leave you with a lovely little comic with a message that many self-trackers can relate to.

thesecret-web
The Secret by Grant Snider

 

Posted in What We're Reading | Tagged , , , , , , , , , , | Leave a comment

Better by Default: An Access Conversation with John Wilbanks

Photo by Joi Ito

Photo by Joi Ito

John Wilbanks is the Chief Commons Officer for Sage Bionetworks. You may not recognize John’s name or the name of his organization, but after today, you may want to commit it to memory. On March 9, 2014 Tim Cook introduced us to the idea of ResearchKit and then turned it over to Jeff Williams who described the new initiative and the five applications that were launched in collaboration with leading academic labs, advocacy groups, and research organizations. Sage Bionetworks is responsible for two of those apps, and John is responsible for leading design and development of many of the novel research tools and methods used by Sage. The following is an edited transcript of a conversation we had with John after the announcement.


Parkinson mPower App

This is Big

Think about what we’re doing in the context of it being open source. ResearchKit is going to be great for the QS community. They are perfectly suited to take advantage of ResearchKit. Let’s look at the five apps that were released today. They cover complex, but ubiquitious diseases. Plus the diseases are a great fit for the technology and sensor capabilities. But what is going to be amazing is when ResearchKit is released as open source. Anyone will have the ability to reskin these existing five apps to make novel research tools. Our Parkinson’s app might become a Huntington’s app. Our breast cancer app measures cognition really well, maybe it gets reskinned into a focused cognition tool. The app that focuses on diabetes could become a diet research app.

Large research institutions are going to jump all over this, but I’m more excited about the idea that small groups of people who have a bit of technical skill can work together to reskin the apps and turn them into longitudinal studies of 20 or 50 people. There may be five of those small groups, maybe 100. We can then work to stich those groups together and learn even more.

So the rare and chronic disease folks and the tech and QS community are involved. Now we come to everyone else. Everyone who isn’t suffering or presenting with a medical issue. We have to figure out ways to get them to participate.

We have a long tradition of creating incentives to participate. There is no reason we can’t create novel incentive methods to bring people into research. Maybe you receive a federal income tax credit. Maybe you’re allowed to enroll in long term care insurance at a reduced rate. There are a lot of ways to bring people in and that’s not touching the innate altruism of people and their curiosity. We’re already seeing this with the Precision Medicine Initiative. People want to take part, they want to engage.

Once we start getting that engagement, and we begin to see a diverse ecology of applications built on top of ResearchKit, then we’ll start to see success. It may take a bit of time. It won’t happen with this iteration. Maybe not even the second, but when we get enough devices, apps, participants, and improved interoperability between them all we’ll start to see the power of network effects.

You have to remember, there are no “killer apps” without network effects. Email wasn’t a big deal in the late 80′s because you couldn’t reach anyone outside your system. But then the web came, we connected the dots, the nodes, and then there it was, the power of the newtork.

I see QS and our current state of devices, apps, and tools being very similar to all those nerds typing away in the 80′s. They were okay with what they had because they could work with it. Then the net came and you have more control and more interefaces. That leads to the killer apps. That’s why we’re building this, for the third or fourth wave.


Share the Journey app

Everything we’re doing, the whole stack working together, is new. Consenting participants using well-designed and open-source Participant-Centered Consent toolkits. Giving participants direct access to their data. Securely hosting automatically de-identified data in the cloud using our Bridge Server. None of these have been done before at the same time.

We’re a non-profit, so we can be this icebreaker. We can take these risks and experiment and iterate and learn. No one asks us how we’re going to make money. We have a different bottom line — what is best for everyone involved? That outlook gives us the freedom to do this work.

I’m honored to have the opportunity to create a product that pushed my beliefs: participants-centric principles. If you’re a participant, then you decide. You’re in control. You can do cool stuff with the data. You can stop answering questions whenever you want. You can delete the app. We live in a world in which the politics of technology are dicteated by code and they often don’t share those ideas. To get this opportunity is amazing.

These moments don’t happen often. This is IBM going open source in the late 90s. It’s that big. I wasn’t sure I was going to be a piece of something that big. We’re trying to change culture.

In 1998 Lawrence Lessig proposed the pathetic dot theory in his book, Code and Other Laws of CyberspaceHe theorized that four forces control what we do: Law, Architecture, Social Norms, and the Market. He went futher and differentiated west coast law, which was quickly becoming dominated by software code and east coast law, what we normally think of when we think of laws.

I think up until now we’ve failed to properly take up that lever, to use software code, west coast law, to express something better. People often forget that building software means expressing an opinion. We created our apps, our tools, our systems to reflect our opinion, that participants should be at the center of research. And then we’re giving it away. That’s our position, and it’s better by default.

But, we’ve just started. The fun now is that we get to test it. I’ve always said that we can’t screw it up any worse than it already is. This isn’t the end. It’s not finished. We’re going to keep changing and learning.


John can be found online at del-fi.org and @wilbanks.

We invite you to share your data access stories, and this article with the #qsaccess hashtag and follow along on quantifiedself.com@quantifiedself and our Access Matters Medium publication.

Posted in QS Access, QS Access Conversations | Tagged , , , , , , , , , , | 1 Comment

Quantified Self and Apple’s ResearchKit

52325a261b78fbef25d1cb879f294c605b6d9e5c_xlarge

Apple’s announcement of ResearchKit is strong evidence that Quantified Self practices are emerging as a major influence on medical research and other forms of knowledge making.

Apple talked about how their new effort focused on opening up health research is designed to combat five main current issues:

  • Limited Participation
  • Small sample sizes limit our understanding of diseases
  • Reliance on subjective data
  • Infrequent data provide only snapshots through time
  • One-way communication from researcher to participant (and only at the end of the study, if at all)

Furthermore, the design of ResearchKit allows the  participant to decide how data is shared. Apple will not see the data. Participants are allowed to be involved in the data collection in real-time, using the data they’re collecting to understand and inform their own health improvement plans.

In light of today’s announcement we wanted to highlight some of our favorite and most powerful examples of taking the research process into one’s own hands, making their own knowledge through thoughtful data collection and reflection. We invite you watch what’s possible now, and imagine with us what could be accomplished tomorrow.

Mark Drangsholt: Deciphering My Brain Fog

Lindsay Meyer on Tracking Hearing Loss

Thomas Christiansen on Learning from 60,000 Observations

Nan Shellabarger: 26 Years of Weight Tracking

Rob Rothfarb on Tracking My Blood

Last year we gather a fantastic group of researchers, toolmakers, and science leadership at the 2014 Quantified Self Public Health Symposium to discuss how personal data can impact personal and public health. That meeting culminated in a great report that touches on many of the aspects discussed today regarding ResearchKit. We invite you to download, read, and share that report. For a more nuanced look into how ResearchKit may impact the research community, we’re highlighting four great talks from the the meeting.

Susannah Fox shares research from the Pew Internet and Life Project and describes the challenges ahead for promoting self-tracking.

Margaret McKenna explores the issues, challenges, and ideas large scale self-tracking applications have in mind when they consider working with the research community.

Jason Bobe talks about the lessons learned from involving research participants in the data ownership and discovery process.

Doug Kanter describes what he’s learned from tracking and visualizing his diabetes data.

If you’re interested in how ResearchKit will be affecting self-tracking, personal data, and access to information, research and knowledge making, then stay tuned to our Access Channel here on QuantifiedSelf.com and on Medium.

We are sure to have many great talks and sessions that focus on ResearchKit at our QS15 Conference and Actrivate Exposition. We invite you to join us.


We invite you to share your data access stories, and this article with the #qsaccess hashtag and follow along on quantifiedself.com and @quantifiedself.

Posted in QS Access | Tagged , , , , , , | 1 Comment

QS Access App: See your HealthKit Data in a Table

On Wednesday this week we learned that the QS Access app we submitted to the Apple store was approved. This means you can download the QS Access app on iTunes. We hope you’ll find it useful. Our app is a very simple tool for accessing HealthKit data in a table so that you can explore it using Numbers, Excel, R, or any other CSV compatible tool.

It is still early days for HealthKit, but my conversations with toolmakers at Quantified Self events convinces me that there will be many device and software makers that integrate with Apple’s platform for collecting and analyzing personal data. I hope this will allow more people to learn from their own data by reflecting on changes over time and by combining multiple data streams – such as activity, sleep, and nutrition – into a single visualization for comparison.

To give you your HealthKit data in tabular format, we’ve had to simplify it. QS Access shows your data in either “hourly” or “daily” chunks.  These won’t be appropriate for all uses, but many interesting questions can be asked of data that is presented as a time series using hourly and daily values. This is just a starting point, and we’re looking forward to making it do more based on your feedback.

We very much hope that if you learn something from your data using QS Access, you’ll share your project by participating in a Quantified Self Show&Tell meetup and by joining us at QS15 Conference and Exposition next year in San Francisco. Suggestions about the app itself and interesting examples of usage can be shared with us directly by emailing us: labs@quantifiedself.com,

Read a short example of using QS Access to look at my activity data.
Find Support for QS Access in the QS Forum.

The QS Access App was authored by our long time QS Labs friend and collaborator Robin Barooah.

Posted in Lab Notes | Tagged , , , , | 12 Comments