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sensing opportunities,[object Object],for mobile health persuasion,[object Object],jonfroehlich@uw.edu,[object Object],phd candidate in computer science,[object Object],university of washington,[object Object],mobile health conference,[object Object],stanford university, 05.24.2010,[object Object],design:,[object Object],use:,[object Object],build:,[object Object],ubicomp lab,[object Object],sustainability research,[object Object],university of washington,[object Object],university of washington,[object Object]
sensing opportunities,[object Object],for mobile health persuasion,[object Object]
sensing opportunities,[object Object],for mobile health persuasion,[object Object],Twin Falls is only 1.4 mi away and you’ll burn an estimated 170 calories round trip.,[object Object],Twin Falls is only 1.4 mi away.,[object Object],Twin Falls!,[object Object],Burn 170    ,[object Object],cal & reach your walking goal for the week!,[object Object]
sensing opportunities,[object Object],for mobile health persuasion,[object Object],Kairostechnology that suggests a behavior at the most opportune moment,[object Object],-fogg, 2003,[object Object],Twin Falls is only 1.4 mi away and you’ll burn an estimated 170 calories round trip.,[object Object],Twin Falls is only 1.4 mi away.,[object Object],Twin Falls!,[object Object],Burn 170    ,[object Object],cal & reach your walking goal for the week!,[object Object]
two things you need,[object Object],a method to passivelymonitor human activity,[object Object],a method to provide feedback about behavior,[object Object]
self-report,[object Object],useful for measuring,[object Object],beliefs, feelings, goals,[object Object],simple,[object Object],low cost,[object Object],[object Object]
people are not good at monitoring their own behaviors:
eating [champagne, 2002]
exercise [lichtman, 1992]
routine activities [klasnja, 2008]
coughing [liu et al., in submission],[object Object]
not just sensor hardware progressions,[object Object],[object Object]
ability to store lots of information
constant connectivity / the cloud,[object Object]
running,[object Object],lester et al., ijcai 2005,[object Object],choudury et al., ieee pervasive 2008,[object Object]
walking,[object Object],lester et al., ijcai 2005,[object Object],choudury et al., ieee pervasive 2008,[object Object]
sitting,[object Object],lester et al., ijcai 2005,[object Object],choudury et al., ieee pervasive 2008,[object Object]
transit modes,[object Object],patterson et al., ubicomp 2003,[object Object],zheng et al., ubicomp 2008,[object Object],reddy et al.,  sensor networks2009,[object Object]
eating,[object Object],jawbone microphone,[object Object],eating,[object Object],microphone in ear detects when a person is eating with 99% accuracy,[object Object],amft  et al., ubicomp 2007,[object Object],cheng et al., pervasive 2010,[object Object]
identifying fluids,[object Object],instrumented cup,[object Object],79% classification accuracy ,[object Object],68 different fluids including sodas, juices, beers, wines,[object Object],lester et al., pervasive health 2010,[object Object]
coughing,[object Object],liu et al., in submission,[object Object]
automatically detecting coughs with a commodity mobile phone,[object Object],microphone,[object Object],liu et al., in submission,[object Object]
collecting and analyzing the cough dataset,[object Object],17 participants,[object Object],72 hours of naturalistic audio recording,[object Object],6 graduate students annotated recordings,[object Object],2542 coughs labeled by annotators,[object Object],84.4% of coughs were correctly classified,[object Object],0.7% false positive rate (3.3/hr),[object Object],liu et al., in submission,[object Object]
19,[object Object],number of coughs,[object Object],measured vs. self-report,[object Object]
inaccuracy of self-report,[object Object],20,[object Object],diff: mean (22.8/hr), std (33/hr),[object Object],number of coughs,[object Object],measured vs. self-report,[object Object],diff: mean (22.8/hr), std (33/hr),[object Object]
two things you need,[object Object],a method to passivelymonitor human activity,[object Object],a method to provide feedback about behavior,[object Object]
speedometer,[object Object],gas gauge,[object Object]
Sensing Opportunities and Zero Effort Applications for Mobile Health Persuasion
zero effort applications,[object Object],for behavior change,[object Object],goal: minimize interaction costs,[object Object],approach: passive sensing + passive display ,[object Object],basically, do the activities that you normally do and the mobile phone will automatically respond,[object Object]
two examples:,[object Object],ubifit,[object Object],ubigreen,[object Object],encouraging fitness behaviors through passive sensing and feedback,[object Object],consolvo et al., chi 2008,[object Object],consolvo  et al., ubicomp2008,[object Object],encouraging proenvironmental behaviors through passive sensing and feedback,[object Object],froehlich et al., chi 2009,[object Object]
ubisystem components,[object Object],collects data about physical activities,[object Object],activity recognition device,[object Object],glanceable display,[object Object],phone wallpaper!,[object Object],+,[object Object],communicates data about physical activities,[object Object]
ubisystem components,[object Object],towards zero effort applications,[object Object],collects data about physical activities,[object Object],activity recognition device,[object Object],interactive application,[object Object],glanceable display,[object Object],+,[object Object],+,[object Object],communicates data about physical activities,[object Object]
ubifit,[object Object],personal ambient display,[object Object],walk,[object Object],cardio,[object Object],strength,[object Object],flexibility,[object Object],primary goal met,[object Object],alternate goal met,[object Object],recent goal met,[object Object]
ubigreentracked 6 transit activities,[object Object],walk,[object Object],bike,[object Object],drive alone,[object Object],train,[object Object],carpool,[object Object],bus,[object Object],“green”,[object Object],“not-green”,[object Object],minimum activity duration: 7 minutes,[object Object],29,[object Object]
ubigreen,[object Object],personal ambient display,[object Object],phone,[object Object],background,[object Object],(wallpaper),[object Object],current activity,[object Object],evolving image,[object Object],value icon bar,[object Object]
sense of anticipation for how story would unfold,[object Object]
ubigreen,[object Object],personal ambient display,[object Object],tree,[object Object],design:,[object Object],03/30/08,[object Object],03/31/08,[object Object],03/31/08,[object Object],03/31/08,[object Object],03/31/08,[object Object],04/01/08,[object Object],04/01/08,[object Object],04/01/08,[object Object],04/01/08,[object Object],04/02/08,[object Object],04/02/08,[object Object],04/03/08,[object Object],04/03/08,[object Object],04/03/08,[object Object],04/03/08,[object Object],04/03/08,[object Object],04/03/08,[object Object],04/03/08,[object Object],04/04/08,[object Object],04/04/08,[object Object],04/04/08,[object Object],04/04/08,[object Object],04/05/08,[object Object],04/05/08,[object Object],04/06/08,[object Object],7:27 PM,[object Object],7:45 AMT-Mobile,[object Object],8:05 AMT-Mobile,[object Object],5:15 PMT-Mobile,[object Object],5:30 PMT-Mobile,[object Object],7:23 AMT-Mobile,[object Object],8:05 AMT-Mobile,[object Object],5:38 PMT-Mobile,[object Object],6:11 PMT-Mobile,[object Object],7:41 AMT-Mobile,[object Object],5:22 PMT-Mobile,[object Object],6:55 AMT-Mobile,[object Object],7:15 AMT-Mobile,[object Object],4:48 PMT-Mobile,[object Object],5:56 PMT-Mobile,[object Object],6:09 PMT-Mobile,[object Object],9:45 PMT-Mobile,[object Object],10:07 PMT-Mobile,[object Object],07:28 AMT-Mobile,[object Object],05:41 PMT-Mobile,[object Object],07:35 PMT-Mobile,[object Object],11:01 PMT-Mobile,[object Object],08:31 AMT-Mobile,[object Object],10:19 AMT-Mobile,[object Object],12:00 AMT-Mobile,[object Object],everything resets on sunday,[object Object]
ubigreen,[object Object],personal ambient display,[object Object],polar bear,[object Object],design:,[object Object],03/30/08,[object Object],7:27 PM,[object Object],03/31/08,[object Object],03/31/08,[object Object],03/31/08,[object Object],03/31/08,[object Object],04/01/08,[object Object],04/01/08,[object Object],04/01/08,[object Object],04/01/08,[object Object],04/02/08,[object Object],04/02/08,[object Object],04/03/08,[object Object],04/03/08,[object Object],04/03/08,[object Object],04/03/08,[object Object],04/03/08,[object Object],04/03/08,[object Object],04/03/08,[object Object],04/04/08,[object Object],04/04/08,[object Object],04/04/08,[object Object],04/04/08,[object Object],7:45 AM,[object Object],8:05 AM,[object Object],5:15 PM,[object Object],5:30 PM,[object Object],7:23 AM,[object Object],8:05 AM,[object Object],5:38 PM,[object Object],6:11 PM,[object Object],7:41 AM,[object Object],5:22 PM,[object Object],6:55 AM,[object Object],7:15 AM,[object Object],4:48 PM,[object Object],5:56 PM,[object Object],6:09 PM,[object Object],9:45 PM,[object Object],10:07 PM,[object Object],07:28 AM,[object Object],05:41 PM,[object Object],07:35 PM,[object Object],11:01 PM,[object Object]
Monday,[object Object],Saturday,[object Object]
personal ambient display,[object Object],impressions of ubifit,[object Object],If you didn’t have a screen [display], I wouldn’t think about it [physical activity] as much… I think about it maybe subconsciously every time I look at my phone. ,[object Object],	- P5UF,[object Object],With a website, it’s so easy to ignore… it’s just out of sight, out of mind. But on the phone, you can’t really ignore it…,[object Object],- P9UF,[object Object]
Sensing Opportunities and Zero Effort Applications for Mobile Health Persuasion
game mechanics,[object Object],measured progress,[object Object],playful,[object Object],collections,[object Object],virtual achievements,[object Object]
loss aversion,[object Object]
need for quantitative data,[object Object],I would like to see some graph or raw data.,[object Object],	- P13UG,[object Object],quantitative data,[object Object],[object Object]
allows for self-comparison
some people like it better,[object Object]
in conclusion,[object Object],imagine that you can sense….,[object Object]
running,[object Object],lester et al., ijcai 2005,[object Object],choudury et al., ieee pervasive 2008,[object Object]
walking,[object Object],lester et al., ijcai 2005,[object Object],choudury et al., ieee pervasive 2008,[object Object]
sitting,[object Object],lester et al., ijcai 2005,[object Object],choudury et al., ieee pervasive 2008,[object Object]
eating,[object Object],jawbone microphone,[object Object],eating,[object Object],amft  et al., ubicomp 2007,[object Object],cheng et al., pervasive 2010,[object Object]
lakefront property,[object Object],phone home screen:,[object Object],most valuable real estate in all of technology,[object Object]
lakefront property,[object Object],phone home/lock screen:,[object Object],most valuable real estate in all of technology,[object Object]
thanks to:,[object Object],sunny consolvo,[object Object],pedjaklasnja,[object Object],jameslanday,[object Object],ericlarson,[object Object],seanliu,[object Object],shwetakpatel,[object Object],thank you,[object Object],@jonfroehlich,[object Object],design:,[object Object],use:,[object Object],build:,[object Object],ubicomp lab,[object Object],university of washington,[object Object],university of washington,[object Object]
extra slides,[object Object]
sink usage,[object Object],froehlich et al., ubicomp 2009,[object Object],larson et al., pervasive & mobile computing 2010,[object Object]

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Sensing Opportunities and Zero Effort Applications for Mobile Health Persuasion

Notas do Editor

  1. Maybe add in social persuasion here?Maybe write on arrow instead?
  2. So, from a technology perspective, there’s two things going on here: (1) we have a sensing system that can track location and infer particular decision moments and (2) we have a navigation application that uses persuasion tactics to motivate behavior.
  3. Thus, for these applications to work, there needs to be some _sensing_ and some _feedback_
  4. one potential opportunity here is to use sensing systems that passively sense and infer human activities---http://www.adajournal.org/article/S0002-8223(02)90316-0/abstractEnergy Intake and Energy Expenditure: A Controlled Study Comparing Dietitians and Non-dietitiansCATHERINE M. CHAMPAGNE, PhD, RD, FADAa, GEORGE A. BRAY, MDa, APRIL A. KURTZ, MS, RDa, JOSEFINA BRESSAN RESENDE MONTEIRO, PhDb,ELIZABETH TUCKER, JULIA VOLAUFOVA, PhDa, JAMES P. DELANY, PhDahttp://content.nejm.org/cgi/content/abstract/327/27/1893Discrepancy between self-reported and actual caloric intake and exercise in obese subjectsSW Lichtman, K Pisarska, ER Berman, M Pestone, H Dowling, E Offenbacher, H Weisel, S Heshka, DE Matthews, and SB HeymsfieldInt J ObesRelatMetabDisord. 1999 Aug;23(8):881-8.Dietary underreporting is prevalent in middle-aged British women and is not related to adiposity (percentage body fat).Samaras K, Kelly PJ, Campbell LV.Twin Research and Genetic Epidemiology Unit, St Thomas' Hospital, London, UKhttp://www.ncbi.nlm.nih.gov/pubmed/10490791?ordinalpos=6&itool=EntrezSystem2.PEntrez.Pubmed.Pubmed_ResultsPanel.Pubmed_DefaultReportPanel.Pubmed_RVDocSum
  5. In the last 20 years, sensing and activity inference has come a very long way—originally much work was looking at instrumenting the environment with sensors like cameras to infer what people were doing in that space; with the costs and sizes of hardware shrinking, the early 2000s were marked by instrumenting the person or clothing with wearable sensorsThese wearable sensors are now making their ways into our cell phones in the form of GPS, accelerometers, proximity sensors and cameras. The mobile phone is, of course the ideal platform because it’s nearly always on and always with us.
  6. It’s a new source of measurement information for behavior change.
  7. The sounds are acquired with a microphone located insidethe ear canal. This is an unobtrusive location widely accepted inother applications (hearing aids, headsets). To validate our method we present experimental results containing 3500 seconds of chewing datafrom four subjects on four different food types typically found in a meal.Up to 99% accuracy is achieved on eating recognition and between 80%to 100% on food type classification.
  8. Sensing system need not be on phone; can also be communicated via the cloud.System used optical, ion selective electrical pH, and conductivity sensors in order to sense and classify liquid in a cup in a practical way. Feedback system can still be phone.Drinks make up a surprisingly large portion of daily caloric intake with some research suggesting that 21% of a person’s daily caloric intake comes from beverages (458 calories) [5]. These tend to be ‘optional’ calories, not consumed exclusively to satiate hunger, and thus potentially easier to eliminate or replace with healthier alternatives Automatic Classification of Daily Fluid Intake by Jonathan Lester, Desney Tan, Shwetak Patel, and A.J. Brush22 March 2010; IEEE Pervasive Health 2010 Proceedings
  9. Coughing is the most frequently cited symptom when people seek medical advice in the united states…
  10. In our lab, we’ve been exploring the use of commodity mobile phones to automatically detect and classify when a person coughs.Sensing system doesn’t have to be complicated; it’s the software algorithms that are smart.
  11. Ratio of about 4 to 1 annotation hours to recording hours
  12. The participants were informed to monitor….
  13. similar findings for people estimating their caloric intake and the amount of exercise they get per week.If you can’t measure it, you can’t change it.http://www.adajournal.org/article/S0002-8223(02)90316-0/abstracthttp://content.nejm.org/cgi/content/abstract/327/27/1893http://www.ncbi.nlm.nih.gov/pubmed/10490791?ordinalpos=6&itool=EntrezSystem2.PEntrez.Pubmed.Pubmed_ResultsPanel.Pubmed_DefaultReportPanel.Pubmed_RVDocSum
  14. One of the best established findings in psychology is the role of feedback on performance.Think about how ingrained feedback is in our environment. For example, driving:this type of feedback is always available, passively given allowing us to sort of pre-attentively recognize it
  15. We want to create these sorts of passive awareness systems.
  16. Passive sensing enables a new type of application space I call “zero-effort applications”Avoid the challenging problem of determining when is the right time to prompt people with information; instead surround the user with persuasive information in a very accessible manner.
  17. The goal is for the primary interactions to be completely passive; for both ubifit and ubigreen
  18. As Jon mentioned, we had real time access to participant’s phone data so we could monitor the state of their phones in real timeThis screen shot was taken on a Monday, towards the beginning of the week, and shows the initial stages of their transit behavior. [next slide] Here, the shot was taken towards the end of the week; you can see how participants’ icons progressed throughout the week. At the bottom left you can see that one participant reached the final state of the progression and saw the Northern Lights.
  19. [The glanceable display] was a constant reminder…whereas if you didn’t have a screen [glanceable display], you probably—I wouldn’t think about it [physical activity] as much, you know, I think about it maybe subconsciously every time I look at my phone. {S5}
  20. Abstractions allowed for playfulnessProgress was visibleAchievements were rewardedCould build collection of achievements
  21. I don’t have time to go through all of the persuasive/influence tactics that we thought about… but it’s worth mentioning that we specifically didn’t use loss aversion as a motivation technique here…We wanted people to enjoy using and feel good about using the applications.
  22. I would like to see some graph or raw data. - Participant 13
  23. Consolvo conducted a 3-month study with a control and experimental group and found that those with the ambient display outperformed those without.
  24. This talk was not meant to be prescriptive but rather to inspire thought and creativity around the ideas of passive sensing for human activities. And secondly, to think creatively about how information can be passively displayed to the user.In the next 3 – 5 years, I believe activity inference will be the key technological innovation in mobile phone technology.* New opportunities in passively sensing activitiesOne of the biggest problems in hospitals is hygiene and hand washing; we
  25. The sounds are acquired with a microphone located insidethe ear canal. This is an unobtrusive location widely accepted inother applications (hearing aids, headsets). To validate our method we present experimental results containing 3500 seconds of chewing datafrom four subjects on four different food types typically found in a meal.Up to 99% accuracy is achieved on eating recognition and between 80%to 100% on food type classification.
  26. ubigreen context-triggered survey
  27. with] a web site, it’s so easy, ‘Oh, I didn’t do anything, I'm not going to click on it.’ It’s so easy to ignore it. But on the phone, you can’t really ignore it as easily…otherwise, it’s just…out of sight, out of mind. {S9}