Natalie Melchiorre wanted to work on her upper body strength so she decided to start a 100-pushup challenge. Using a popular iOS app she followed a plan and tracked her progress as she increased her strength. Along the way she encountered some hurdles, but continued on. In this talk, presented at the Phoenix Quantified Self meetup group, Natalie describes her experience with setting this ambitious goal and what she ultimately learned when she failed to complete it. Make sure to stick around to hear Natalie talk about the intersection of goals, performance, and identity.
Amaan Penang was faced with a life change when he moved from Texas to California to start a new job. While preparing for the move he started to examine his financial health and was surprised by what he didn’t understand about his spending and income. Using the popular financial tracking software, Mint, he started to examine his historical spending. In this talk, presented at the Silicon Valley Quantified Self meetup group, Amaaan explains how he tracks his data, crunches the numbers, and finds “interesting patterns” in his data.
Today’s Tidings dispatch comes to us from Phil Goebel, organizer of the QS Melbourne meetup group. Recently, they held their sixth Show&Tell meetup, which focussed on discussing new self-tracking tools. They also announced a new project – The QS Device Library. Read below to learn more about this exciting idea and what transpired at the meetup.
QS Melbourne Show&Tell #6 Recap
by Phil Goebel
Greetings from down under! The Quantified Self community in Melbourne has been active since late 2012 and since then the community has shown enthusiasm for the potential impact that self-tracking technology can have. Earlier this month the Melbourne QS meetup hosted our first set of toolmakers – individuals who are involved in building self-tracking tools. Melbourne has a rich medical and health technology industry and the QS community here is developing into a key contributor to opening the dialogue about the role that self-tracking behaviour, the technology which facilitates it, and the data it generates has within a larger health informatics context.
Our first speaker was Rob Crowder from Smash Wearables. Rob shared his journey from a desire to improve his tennis game to launching a kickstarter campaign. Smash is a wrist worn device packing accelerometer, gyroscope, magnetometer and microcontroller all into a small and aesthetically pleasing form factor. Rob comes from a physics background and the Smash project begun with strapping hacked together hardware onto his wrist and collecting and analysing a whole heap of data. Although Rob has always been and continues to be the driving force behind Smash he stressed the importance of the community which has grown around and is contributing to Smash and has been taken aback by the willingness and generosity of people to lend a hand. Even though Smash did not meet its Kickstarter goals, the Kickstarter campaign did accomplish other objectives which will hopefully lead to Smash being worn by some of Australia’s top tennis player in time for the next Melbourne Open.
Kayla Heffernan a Masters of Information Systems student at Melbourne University discussed and presented her experiences in designing a self-tracking mobile application which delivers complex messaging. The app is currently being used in a randomized controlled trial to better understand the effectiveness of encouraging health behaviours through mobile applications. The objective of the mobile application is to track sun exposure – this is a complex task as too little can mean vitamin D deficiency, too much can put an individual at risk of sun burns and skin cancer, plus factors such as what the app user is wearing needs to be taken into account. Kayla discussed user design techniques such as saving default settings and adding gamification elements to encourage user engagement and to deliver a complex message. It may be a while before the app is available to the broader public, but the results of the RCT will be interesting to follow.
QS Melbourne Announces the Quantified Self Device Library
In addition to the great discussion about the challenges and rewards of building software and hardware for self-tracking, QS Melbourne announced the development of a QS device library. As a result from a research project that happened at the Health and Biomedical Informatics Centre (HaBIC) at the University of Melbourne, there are about 40 self-tracking devices sitting on a shelf gathering dust. In an effort to put these devices to good use HaBIC is working with the QS Melbourne organisers to build a library where devices can be signed out for 1-3 month periods to encourage n=1 activity in the QS community. While still in the logistical planning phases this is a great opportunity to engage the community in QS ideas and concepts and end up with some great show&tell presentations that combine data sources in creative ways. Discussion about how the logistical issues will be handled is ongoing on the Melbourne QS meetup discussion board along with a list of the available devices. Thoughts about how best to setup this library would be appreciated.
We’re always interested in the way individuals with chronic conditions use self-tracking to better understand themselves. A great example of this is our good friend, Sara Riggare. Sara has Parkinson’s Disease and we’ve featured some of her amazing self-tracking work here before. At the 2014 Quantified Self Conference, Sara gave a short talk on what she feels is her most troublesome symptom: freezing of gait. In this talk, she explains why it’s such a big part of her daily life and how she’s using new tools and techniques to track and improve her gait.
Enjoy this week’s list!
The Five Modes of Self-Tracking by Deborah Lupton. One of our favorite sociologists, Deborah Lupton, explores the typologies of self-trackers she’s identified for an upcoming paper. A very nice and clear explanation of the self-tracking practices in regards to different “loci of control.” (Make sure to also read Deborah’s great post, “Beyond the Quantified Self: The Reflexive Monitoring Self“)
In-Depth: How Activity Trackers are Finding Their Way Into the Clinic by MobiHealthNews. An interesting look at the recent influx FDA-cleared activity and movement trackers and how clinicians are looking to use them. Surprising to me is the lack of data access for the patient in these devices (at least on first glance).
The Reluctantly Quantified Parent by Erin Kissane. As a new mother, Erin was hesitant to use what she deemed “anxious technology.” After some hard nights of little sleep she began to slowly incorporate some self-tracking technology into her routine with her newborn daughter. A great read about using tools then putting them away once they’ve served their purpose. (Reminded me of this great talk by Yasmin Lucero.)
Returns to Leisure by Tom VanAntwerp. Tom was interested in his return on investment from his leisure time actives. He tracked his time spent in different non-work activities for two weeks and calculated the cost of participating in those activities.
The Quantified Microbiome Self By Carl Zimmer. The great science writer, Carl Zimmer, writes about a recent experiment and journal article by two MIT researchers who tracked their microbiome every day for a year. Fascinating findings, including a successful self-diagnosis of salmonella poisoning. You can also read the original research paper here.
Better Living Through Data by James Davenport. We recently highlighted one of James’ posts on how his laptop battery tracking led him to understand his computer use habits. In this post he dives deeper into the data.
A Personal Analysis of 1 Year of Using Citibike by Miles Grimshaw. Miles was interested in understanding more about his use of the Citibike bike share system in New York City. Using some ingenious methods he was able to download, visualize, and analyze his 268 total trips. I especially appreciate his addition of a simple “how-to” so other Citibike users can make the same visualizations.
Visualizing Runkeeper Data in R by Dan Goldin. In 2013 Dan ran 1000 miles and tracked them using the popular Runkeeper app. Runkeeper has a quick and easy data export function and Dan was able to download his data and use R to visualize and analyze his runs. (Bonus Link: If you’re a Runkeeper user you might be interested in this fantastic how-to for making a heatmap of your runs.)
This Week on Quantifiedself.com
Natty Hoffman: The Enlightened Consumer
QSEU14 Breakout: Passive Sensing With Smartphones
Jenny Tillotson: Science, Smell, and Fashion
Paul LaFontaine: We Never Fight on Wednesdays
Vanessa Sabino on Tracking a Year of Sleep
Vanessa Sabino was curious about how well she was sleeping. By using the Sleep as Android app, she was able to track a year of sleep data. Before she was able to dig into the data she ran into a problem with the data export format and had to write her own custom data parser to create usable CSV files. Vanessa was then able to use the data to explore her question, “When do I get the most amount of deep sleep?” In this talk, presented at the Toronto QS meetup group, Vanessa explains her process and what she learned from analyzing 340 days of sleep data.
Paul LaFontaine was interested in understanding his anxiety and negative emotional states. What was causing them? When were they happening? What could he do to combat them? Using TapLog, a simple Android-based tracking app (with easy data export), Paul tracked these mental events for six months as well as the triggers associated with each one. In this talk, presented at the 2014 Quantified Self Europe Conference, Paul dives deep in to the data to show how he was able to learn how different triggers were related to his anxiety and stress. While exploring his data, he also discovered a few surprising and profound insights. Watch his great talk below to learn more!
Jenny Tillotson is a researcher and fashion designer who is currently exploring how scent plays a role in emotion and psychological states. As someone living with bipolar disorder, she’s been acutely aware of what affects her own emotions states and has been exploring different methods to track them. In this talk, presented at the 2014 Quantified Self Europe Conference, Jenny discusses her new project, Sensory Fashion, that uses wearable tracking technology and scent and sensory science to improve wellbeing. Be sure to read her description below when you finish watching her excellent talk.
You can also view the slides here.
What did you do?
I established a new QS project called ‘SENSORY FASHION’, funded by a Winston Churchill Fellowship that combines biology with wearable technology to benefit people with chronic mental health conditions. This allowed me to travel to the USA and meet leading psychiatrists, psychologists and mindfulness experts and find new ways to build monitoring tools that SENSE and balance the physiological, psychological and emotional states through the sense of smell. My objective was to manage stress and sleep disturbance using olfactory diagnostic biosensing tools and micro delivery systems that dispense aromas on-demand. The purpose was to tap into the limbic system (the emotional centre of our brain) with aromas that reduce sleep and stress triggers and therefore prevent a major relapse for people like myself who live with bipolar disorder on a day to day basis. I designed my own personalized mood-enhancing ‘aroma rainbow’ that dispenses a spectrum of wellbeing fragrances to complement orthodox medication regimes such as taking mood stabilizers.
How did you do it?
Initially by experimenting with different evidence-based essential oils with accessible clinical data, such as inhaling lavender to aid relaxation and help sleep, sweet orange to reduce anxiety and peppermint to stimulate the brain. I developed a technology platform called ‘eScent’ which is a wearable device that distributes scent directly into the immediate vicinity of the wearer upon a biometric sensed stimuli (body odor, ECG, cognitive response, skin conductivity etc). The scent forms a localized and personalized ‘scent bubble’ around the user which is unique to the invention, creating real-time biofeedback scent interventions. The result promotes sleep hygiene and can treat a range of mood disorders with counter-active calming aromas when high stress levels reach a pre-set threshold.
What did you learn?
I learnt it is possible to track emotional states through body smells, for example by detecting scent signals that are specific to individual humans. In my case this was body odor caused by chronic social anxiety from increased cortisol levels found in sweat and this could be treated with anxiolytic aromas such as sweet orange that create an immediate calming effect. In addition, building olfactory tools can boost self-confidence and communication skills, or identify ‘prodromal symptoms’ in mood disorders; they learn your typical patterns and act as a warning signal by monitoring minor cognitive shifts before the bigger shifts appear. This can easily be integrated into ‘Sensory Fashion’ and jewelry in a ‘de-stigmatizing’ manner, giving the user the prospect of attempting to offer them some further control of their emotional state through smell, whether by conscious control or bio-feedback. The next step is to miniaturize the eScent technology and further explore the untapped research data on the science of body (emotional) odor.
Today’s post comes to use from Freek Van Polen. Freek works at Sense Observations Systems, where they develop passive sensing applications and tools for smartphones. At the 2014 Quantified Self Europe Conference Freek led a breakout session where attendees discussed the opportunities, pitfalls, and ethical challenges associated with the increasing amount of passive data collection that is possible through the many different sensors we’re already carrying around in our pockets. We invite you to read his short description of the breakout below and continue the conversation on our forum.
Passive Sensing with Smartphones
by Freek van Polen
The session started out by using Google Now as an example of what passive sensing is, and finding out what people think about usage of sensor data in such a way. It quickly became apparent that people tend to be creeped out when Google Now suddenly appears to know where they live and where their work is, and especially dislike it when it starts giving them unsolicited advice. Following this discussion we arrived at a distinction between explicit and implicit sensing, where it is not so much about whether the user has to actively switch on sensing or enter information, but rather about whether the user is aware that sensing is going on.
From there the “uncanny valley” with respect to sensing on smartphones was discussed, as well as what would people be willing to allow an app to sense for. An idea for a BBC-app that would keep track of how much attention you pay to what you’re watching on television, and that would subsequently try to get you more engaged, was met with a lot of frowning. It was furthermore pointed out that passive sensing might be risky in the vicinity of children, as they are easily impressionable, are not capable of assessing whether it is desirable to have passive sensing going, and can be tricked into giving up a lot of information.
Natty Hoffman was interested in learning more about how she spent her money. Not satisfied with just categorizing expenses, she dove deeper into two years of transaction data to understand where here money was going and how well her spending habits reflected her ideals. In this talk, presented at the Boston QS Meetup group, Natty explains how she examined her spending data to see if she was supporting ethical, healthy, and local businesses.