Self tracking and digital health

1,358 views

Published on

Lecture for HCI 4 students at University of Glasgow - November 2015.

Published in: Technology
0 Comments
0 Likes
Statistics
Notes
  • Be the first to comment

  • Be the first to like this

No Downloads
Views
Total views
1,358
On SlideShare
0
From Embeds
0
Number of Embeds
509
Actions
Shares
0
Downloads
18
Comments
0
Likes
0
Embeds 0
No embeds

No notes for slide

Self tracking and digital health

  1. 1. Self  Tracking  and  Digital  Health   John  Rooksby   john.rooksby@glasgow.ac.uk  
  2. 2. In  this  lecture   •  Self  tracking       – examples   •  A  brief  history  of  self  tracking     •  Self  tracking  and     – Mobile  health   – Health  behaviour  change   •  HCI  research  on  self  tracking  
  3. 3. Tracking  Physical  AcGvity   Tracking  light  acGvity   •  Pedometers     Tracking  exercise     •  Run  trackers   •  Cycling  trackers   •  Swimming  trackers   Tracking  (non)  sedentary  Gme   •  Standing  Gme  
  4. 4. Tracking  Weight  and  Diet   Food  tracking   •  Calorie  counGng   •  NutriGon  apps   Weight  tracking  
  5. 5. Tracking  Mental  Wellbeing   Tracking  mood,  stress  and  anxiety     Symptom  tracking  to  understand  and   manage  disorders   •  Post  traumaGc  stress  disorder   •  Bi-­‐polar  disorder    
  6. 6. Tracking  Health  CondiGons   Managing  chronic  condiGons  such  as   Diabetes,  Asthma,  and  Chronic  pain   MedicaGon  tracking   •  Compliance     •  Keeping  records      
  7. 7. Much,  much  more   •  Sleep     •  FerGlity   •  Periods   •  Bad  habits   –  e.g.  smoking  cessaGon,  snacking   •  Achievements   –  e.g.  books  read,  places  visited   •  Much,  much  more    
  8. 8. Self  tracking  technology   Self  tracking  can  be  done  with  a  range  of   technologies   •  Mobile  apps   •  Web  apps   •  Wearables   •  Smart  devices   New  technology  is  not  essenGal,  it  is   usually  just  more  convenient  than   mechanical  technology  and  pen  +  paper.  
  9. 9. Self  tracking  is  not  new   1960s  The  "manpo-­‐kei"  or   "manpo-­‐meter"     The  first:     •  To  count  steps  rather   than  distance   •  To  be  marketed  on   health  grounds   •  Origin  of  10,000  steps   Today,  step  counGng  is  very   common  
  10. 10. Self  tracking  is  not  new   Scales   •  Doctors  scales  first  produced  in   1865.   •  Public  "penny  scales"  in  1885.   –  By  1937  the  US  Department  of   commerce  reported  130,000,000   people  using  public  scales.   •  Household  scale  in  mid  20th  C.     Today  weight  is  a  common  health   measure.          
  11. 11. Self  tracking  is  not  new   So  what  is  new?   •  Ubiquity  of  smartphones  and  devices     •  New  forms  of  sensor  (e.g.  locaGon  tracking),  mulGple  sensors     •  Increasing  computaGonal  power  (e.g.  enabling  acGvity   recogniGon)     •  Detailed  visual  and  hapGc  feedback   •  ConnecGvity   –  IntegraGon  of  data  between  applicaGons   –  Sharing  of  data  with  peers   –  Sharing  data  with  health  providers  
  12. 12. Self  tracking  and  digital  health   Self  tracking   Digital  health  
  13. 13. Digital  health   Self  tracking  is  related  to  several  areas  of  digital  health,   including:       •  Mobile  health  -­‐  Using  mobile  devices  to  collect,  analyse  and  communicate   informaGon   •  Health  Behaviour  change  -­‐  Encouraging  people  to  make  posiGve  changes   in  order  to  reduce  their  risks  of  developing  preventable  diseases      
  14. 14. Mobile  Health   Olla  and  Shimskey's   Taxonomy  of  mHealth   applicaGons  for   smartphones    
  15. 15. Mobile  Health   Olla  and  Shimskey's   Taxonomy  of  mHealth   applicaGons  for   smartphones     More  to  the  area  than   tracking   •  DiagnoGcs   •  EducaGon  and   reference   •  Efficiency   •  Environmental   monitoring      
  16. 16. Health  behaviour  change   Many  people  can  become  more  healthy  and  reduce  the  risk  of   developing  many  illnesses  and  dying  early,  by  changing  their   behaviours:   •  Standing  more,  walking  more,  taking  more  exercise     •  Quifng  smoking     •  Healthy  eaGng     Self  tracking  is  of  importance  in  health-­‐behaviour  change.     •  To  change  a  behaviour  it  is  important  to  measure  it    
  17. 17. Health  behaviour  change   However     •  Not  all  self  tracking  is  for  the  purpose  of  changing  behaviour.   •  Behaviour  change  is  a  long  term  process,  because  it  requires   maintenance  to  be  effecGve.   –  Aher  one  year  of  absGnence  47%  of  smokers  will  relapse,  aher  5  years   it  is  7%.     –  Trackers  are  ohen  used  for  shorter  periods,  just  a  few  weeks  or   months  before  moving  to  something  else.     –  Trackers  can  act  as  'extrinsic'  moGvators,  but  change  is  easier  to   maintain  when  people  become  'intrinsically'  moGvated.  
  18. 18. HCI   Self  tracking  and  digital  health  are  large,  interdisciplinary  areas   So  what  is  the  role  of  HCI?    
  19. 19. HCI   Self  tracking  and  digital  health  are  large,  interdisciplinary  areas   So  what  is  the  role  of  HCI?     HCI  papers  ohen  focus  on:     1.  InnovaGng  new  systems  and  applicaGons   2.  Improving/exploring  interface  and  interacGon  design   3.  Understanding  real-­‐world  user  pracGces   4.  Taking  criGcal  perspecGves    
  20. 20. Activity Sensing in the Wild: A Field Trial of UbiFit Garden Sunny Consolvo1, 2 , David W. McDonald2 , Tammy Toscos1 , Mike Y. Chen1 , Jon Froehlich3 , Beverly Harrison1 , Predrag Klasnja1, 2 , Anthony LaMarca1 , Louis LeGrand1 , Ryan Libby3 , Ian Smith1 , & James A. Landay1, 3 1 Intel Research Seattle Seattle, WA 98105 USA [sunny.consolvo, beverly.harrison, anthony.lamarca, louis.l.legrand] @intel.com, ttoscos@indiana.edu, mike@ludic-labs.com, iansmith@acm.org 2 The Information School DUB Group University of Washington Seattle, WA 98195 USA [consolvo, dwmc, klasnja] @u.washington.edu 3 Computer Science & Engineering DUB Group University of Washington Seattle, WA 98195 USA [landay, jfroehli, libby] @cs.washington.edu ABSTRACT Recent advances in small inexpensive sensors, low-power processing, and activity modeling have enabled applications that use on-body sensing and machine learning to infer people’s activities throughout everyday life. To address the growing rate of sedentary lifestyles, we have developed a system, UbiFit Garden, which uses these technologies and a personal, mobile display to encourage physical activity. We conducted a 3-week field trial in which 12 participants used the system and report findings focusing on their experiences with the sensing and activity inference. We discuss key implications for systems that use on-body sensing and activity inference to encourage physical activity. Author Keywords persuasive technology, sensing, activity inference, mobile phone, ambient display, fitness, activity-based applications. ACM Classification Keywords H.5.2 User Interfaces, H.5.m Miscellaneous. INTRODUCTION Recent advances in small inexpensive sensors, low-power processing, and activity modeling have enabled new classes of technologies that use on-body sensing and machine learning to automatically infer people’s activities throughout the day. These emerging technologies have seen success with participants in controlled and “living” lab settings [11] and with researchers in situ [18]. The next step is to conduct in situ studies with the target user population. Such studies expose important issues, for example, how the systems are used as part of everyday experiences, where the technology is brittle, and user reactions to activity inference and the presentation of those inferences. One application domain for on-body sensing and activity inference is addressing the growing rate of sedentary lifestyles. Regular physical activity is critical to everyone’s physical and psychological health, regardless of their being normal weight, overweight, or obese [6,16]. Physical activity reduces risk of premature mortality, coronary heart disease, type II diabetes, colon cancer, and osteoporosis, and has also been shown to improve symptoms associated with mental health conditions such as depression and anxiety. Yet despite the importance of physical activity, many adults in the U.S. do not get enough exercise [1]. Technologies that apply on-body sensing and activity inference to the fitness domain are faced with a challenge regarding which physical activities should be detected. The American College of Sports Medicine (ACSM) recommends that physical activity be regular and include cardiorespiratory training (or “cardio”) where large muscle groups are involved in dynamic activity such as running or cycling; resistance training, that is weight training that builds muscular strength and endurance; and flexibility training where muscles are slowly elongated to improve or maintain range of motion [22]. Technologies that attempt to encourage physical activity should support the range of activities that contribute to a physically active lifestyle, rather than focus on a single activity such as walking. Our goal in this work is to investigate users’ experiences with a system that we have developed, UbiFit Garden, which uses on-body sensing, activity inference, and a novel personal, mobile display to encourage physical activity. While our future work will focus on how the system affects awareness and sustained behavior change, at this stage, we are exploring how the system affects individuals’ everyday lives, how they interpret and reflect on the data about their physical activities, and how they interact with that data. We conducted a three- week field trial (n=12) with participants who were representative of UbiFit Garden’s target audience. In this paper, we discuss the types of physical activities participants performed, how those activities were recorded and manipulated, and participants’ qualitative reactions to activity inference and manual journaling. We also discuss participants’ general reactions to the system. Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. CHI 2008, April 5–10, 2008, Florence, Italy. Copyright 2008 ACM 978-1-60558-011-1/08/04…$5.00. AcGvity  sensing  in  the  wild:  A  field   trial  of  UbiFit  Garden       Sunny  Consolvo  et  al  (CHI2008)     This  paper   •  Describes  a  novel  (in  2008)  mobile   acGvity  tracking  system   •  Presents  results  from  a  field  trial   of  the  system   •  Discusses  the  use  of  acGvity   trackers  for  encouraging  physical   acGvity     InnovaGon  
  21. 21. Jogging with a Quadcopter Florian ‘Floyd’ Mueller, Matthew Muirhead Exertion Games Lab RMIT University Melbourne, Australia {floyd, matt}@exertiongameslab.org ABSTRACT Jogging is a popular exertion activity. The abundance of jogging apps suggests to us that joggers can appreciate the opportunity for technology to support the jogging experience. We want to take this investigation a step further by exploring if, and how, robotic systems can support the jogging experience. We designed and built a flying robotic system, a quadcopter, as a jogging companion and studied its use with 13 individual joggers. By analyzing their experiences, we derived three design dimensions that describe a design space for flying robotic jogging companions: Perceived Control, Focus and Bodily Interaction. Additionally, we articulate a series of design tactics, described by these dimensions, to guide the design of future systems. With this work we hope to inspire and guide designers interested in creating robotic systems to support exertion experiences. Author Keywords Jogging; running; movement-based play; whole-body interaction; sports; quadcopter; robot; exertion ACM Classification Keywords H.5.2. [Information Interfaces and Presentation]: User Interfaces - Miscellaneous. INTRODUCTION Understanding the role of interactive technology to support physical exertion is a thriving field in HCI. By exertion interactions we mean interactions with technology that require intense physical effort from the user [20]. Supporting exertion is important, as exertion activity can facilitate social, mental and physical health benefits. One popular exertion activity is jogging, i.e. running at a leisurely pace. The abundance of jogging apps, sports watches and wearable sensors (for example embedded in Figure 1. What is it like to jog with a quadcopter? shirts and socks [3]) suggests to us that joggers appreciate the opportunity for technology to support their jogging experience. This trend has been recognized and investigated by research [39] while special interest groups (SIGs) at CHI have also been formed to encourage further developments in this area [23, 24]. We believe that the current range of systems to support jogging is only the beginning of a trend. With sensor advancements, improvement in battery performance and miniaturization, more opportunities will emerge for designers to support people’s exertion experiences. Along with technology advancements, there have also been advances in our understanding of the role of bodily aspects from a system’s design perspective, most often under the name of embodiment [10, 36]. We take this investigation a step further and wonder if exertion activities like jogging that are so embodiment-focused might benefit from designs with a similar embodiment focus. We see robots as having the potential for such an embodiment focus, and therefore begin by exploring if, and how, robotic systems can support Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from permissions@acm.org. CHI 2015, April 18 - 23 2015, Seoul, Republic of Korea. Copyright is held by the owner/author(s). Publication rights licensed to ACM. ACM 978-1-4503-3145-6/15/04…$15.00 http://dx.doi.org/10.1145/2702123.2702472 Jogging  with  a  quadcopter   Florian  'Floyd'  Mueller  et  al  (CHI2015)     This  paper:   •  Explores  if  and  how  roboGc   systems  can  support  the  jogging   experience   •  Presents  a  roboGc  quadcopter   based  system  for  joggers   •  Uses  of  robots  include  keeping   pace,  sefng  routes,  making  a   distracGon,  and  making  jogging   playful           InnovaGon  
  22. 22. TastyBeats: Designing Palatable Representations of Physical Activity Rohit Ashok Khot1 , Jeewon Lee1 , Deepti Aggarwal2 , Larissa Hjorth3 , Florian ‘Floyd’ Mueller1 1 Exertion Games Lab RMIT University, Australia { rohit, jeewon, floyd }@ exertiongameslab.org 2 Microsoft Centre for Social NUI, University of Melbourne, Australia daggarwal@student.unimelb.edu.au 3 RMIT University, Australia larissa.hjorth@rmit.edu.au Figure 1: TastyBeats is a fountain-based interactive system that creates a fluidic spectacle of mixing sport drinks based on heart rate data of physical activity. ABSTRACT In this paper, we introduce palatable representations that besides improving the understanding of physical activity through abstract visualization also provide an appetizing drink to celebrate the experience of being physically active. By designing such palatable representations, our aim is to offer novel opportunities for reflection on one’s physical activities. We present TastyBeats, a fountain-based interactive system that creates a fluidic spectacle of mixing sport drinks based on heart rate data of physical activity, which the user can later consume to replenish the loss of body fluids due to the physical activity. We articulate our experiences in designing the system as well as learning gained through field deployments of the system in participants’ homes for a period of two weeks. We found that our system increased participants’ awareness of physical activity and facilitated a shared social experience, while the prepared drink was treated as a hedonic reward that motivated participants to exercise more. Ultimately, with this work, we aim to inspire and guide design thinking on palatable representations, which we believe opens up new interaction possibilities to support physical activity experience. Author Keywords Palatable representation; fluidic interfaces; physical activity; quantified self; personal informatics; Human-Food Interaction (HFI). ACM Classification Keywords H.5.m. Information interfaces and presentation (e.g., HCI): Miscellaneous. INTRODUCTION Activity trackers like pedometers and heart rate monitors are becoming increasingly popular to support physical activity experiences [41]. These devices collect personally relevant data such as bodily responses to physical activity and provide opportunities to reflect on the collected data through self-monitoring [22]. For example, pedometers count the number of steps taken in a day, while heart rate monitors inform about exercise intensity. Research suggests that regular use of these devices can increase user motivation for physical activity [35, 43]. One key aspect of tracking physical activity is visualization, which improves understanding of the data [22, 35]. “Seeing” makes knowledge credible [4] and “greater visibility of information puts an added responsibility to act on” as pointed out by Viseu and Suchman [45]. For example, by visualizing physical activity data, users can gain a better understanding of their physical activity levels and can make this gained knowledge actionable towards Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from permissions@acm.org. CHI 2015, April 18 - 23 2015, Seoul, Republic of Korea. Copyright is held by the owner/author(s). Publication rights licensed to ACM. ACM 978-1-4503-3145-6/15/04...$15.00. http://dx.doi.org/10.1145/2702123.2702197 TastyBeats:  Designing  palatable   representaGons  of  physical  acGvity   Rohit  Ashok  Khot  et  al  (CHI  2015)     This  paper   •  Introduces  'palatable'   representaGons  of  data  as  an   alternaGve  to  visualisaGon   •  Presents  a  fountain  based  system   that  creates  a  'fluidic  spectacle'  of   mixing  sports  drinks  based  on   heart  rate  data     •  Presents  a  field  study  of  the   system  in  three  households     InnovaGon  
  23. 23. Design Requirements for Technologies that Encourage Physical Activity Sunny Consolvo1, 2 , Katherine Everitt3 , Ian Smith1 , & James A. Landay1, 3 1 Intel Research Seattle 1100 NE 45th Street, 6th Floor Seattle, WA 98105 USA [sunny.consolvo,ian.e.smith, james.a.landay]@intel.com 2 University of Washington The Information School Box 352840 Seattle, WA 98195-2840 USA consolvo@u.washington.edu 3 University of Washington Computer Science & Engineering Box 352350 Seattle, WA 98195-2350 USA [everitt,landay]@cs.washington.edu ABSTRACT Overweight and obesity are a global epidemic, with over one billion overweight adults worldwide (300+ million of whom are obese). Obesity is linked to several serious health problems and medical conditions. Medical experts agree that physical activity is critical to maintaining fitness, reducing weight, and improving health, yet many people have difficulty increasing and maintaining physical activity in everyday life. Clinical studies have shown that health benefits can occur from simply increasing the number of steps one takes each day and that social support can motivate people to stay active. In this paper, we describe Houston, a prototype mobile phone application for encouraging activity by sharing step count with friends. We also present four design requirements for technologies that encourage physical activity that we derived from a three- week long in situ pilot study that was conducted with women who wanted to increase their physical activity. Author Keywords design requirements, fitness, physical activity, pedometer, mobile phone, obesity, overweight, social support. ACM Classification Keywords H.5.2 [User Interfaces]: User-centered design; H.5.3 [Group and Organization Interfaces]: Evaluation/methodology, Asynchronous interaction. INTRODUCTION To help address the global epidemic of overweight and obesity, we are investigating how technology could help encourage people to sustain an increased level of physical activity, which medical experts agree is critical to maintaining fitness, reducing weight, and improving health. We are specifically interested in encouraging opportunistic physical activities. These are where a person incorporates activities into her normal, everyday life to increase her overall level of physical activity (e.g., walking instead of driving to work, taking the stairs, or parking further away from her destination). We are also interested in encouraging structured exercise, where a person elevates her heart rate for an extended period (e.g., going for a run or swim). In our first investigation, we focus on encouraging people to add opportunistic physical activities to their lives, without discouraging structured exercise. Studies have shown that people can achieve health benefits by merely increasing the number of steps they take each day and that support from friends and family has consistently been related to an increase in physical activity [3, 4, 17, 19]. However, with today’s hectic lifestyles, many people have difficulty fitting exercise into their lives and spending quality time with their friends. A mobile device such as a mobile phone can provide relevant information at the right time and place, and may help encourage opportunistic activities [6]. Based on these findings, we investigate if technology could encourage physical activity by providing personal awareness of activity level and mediating physical activity-related social interaction among friends. We use daily step count as a measure of physical activity and a mobile phone-based fitness journal we developed to track and share progress toward a daily step count goal within a small group of friends. We realize that investigating the effect of the technology on sustained behavior change will require a longitudinal study and thus have taken a user-centered design approach starting with a three-week long in situ pilot study. We evaluated an early- stage prototype of the mobile phone application with three groups of women who wanted to increase their levels of physical activity, were interested in preventing weight gain, and in many cases, had a goal of losing some weight. The results of the pilot study are being used to inform the design of a new application we are building to enable a longitudinal study to examine effects on behavior. In this paper, we focus our discussion on the four key design requirements for technologies that encourage physical activity that we derived from our analysis of the Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. CHI 2006, April 22–27, 2006, Montréal, Québec, Canada. Copyright 2006 ACM 1-59593-178-3/06/0004...$5.00. CHI 2006 Proceedings • Designing for Tangible Interactions April 22-27, 2006 • Montréal, Québec, Canada 457 Design  requirements  for  technologies   that  encourage  physical  acGvity   Sunny  Consolvo  et  al  (CHI2006)     This  paper   •  Presents  a  system  for  entering   pedometer  data  onto  mobile   phones   •  Presents  a  field  trial  of  the  system   with  a  social  group   •  Discuses  issues  in  presenGng  and   sharing  acGvity  data  using  mobile   phones       InteracGon  design  
  24. 24. Balancing Accuracy and Fun: Designing Camera Based Mobile Games for Implicit Heart Rate Monitoring Teng Han2 , Xiang Xiao1 , Lanfei Shi2 , John Canny3 , Jingtao Wang1 1 Department of Computer Science, 2 Intelligent Systems Program, University of Pittsburgh, Pittsburgh, PA, USA {teh24@, xiangxiao@cs., las231@, jingtaow@cs.}pitt.edu 3 Computer Science Division, University of California at Berkeley, 387 Soda Hall, Berkeley, CA, USA jfc@cs.berkeley.edu ABSTRACT Heart rate monitoring is widely used in clinical care, fitness training, and stress management. However, tracking individuals' heart rates faces two major challenges, namely equipment availability and user motivation. In this paper, we present a novel technique, LivePulse Games (LPG), to measure users’ heart rates in real time by having them play games on unmodified mobile phones. With LPG, the heart rate is calculated by detecting changes in transparency of users’ fingertips via the built-in camera of a mobile device. More importantly, LPG integrate users’ camera lens covering actions as an essential control mechanism in game play, and detect heart rates implicitly from intermittent lens covering actions. We explore the design space and trade- offs of LPG through three rounds of iterative design. In a 12-subject user study, we found that LPG are fun to play and can measure heart rates accurately. We also report the insights for balancing measurement speed, accuracy, and entertainment value in LPG. Author Keywords Heart rate, mobile phone, multi-modal interface, game design, serious game, ECG, quantified self. ACM Classification Keywords H5.2. Information interfaces and presentation (e.g., HCI): User Interfaces. General Terms Design, Experimentation, Human Factors. INTRODUCTION Heart rate is one important vital sign in health care [6, 29]. For healthy people, resting heart rate (RHR) is also an essential physiological marker of physical fitness [7, 30, 38], and expected life span [13]. Heart rate has been used in fitness training [19, 20] and competitive sports for managing work-out intensity and balancing physical exertion. Both continual readings of heart rates [5, 15, 37, 33] and heart rate variability, a.k.a. HRV [27, 29, 32, 33], can predict a user’s physiological state, including cognitive workload and mental stress levels, in contexts such as computer user interfaces [29, 33], traffic control [29], longitudinal monitoring of emotion and food intake [5], and intelligent tutoring [15]. Therefore, the efficient measurement of heart rate can be of great significance across scenarios involving physical health, mental activities or a combination of both. Unfortunately, most heart rate measurement methods are either time-consuming1 , or require special measurement equipment [25] that may not be available to a wide audience. For example, manual pulse counting with fingers may be tedious, and inaccurate. More precise methods include the Electrocardiograph (ECG) [22, 25] and pulse oximeters [25, 35]. These dedicated heart rate monitoring devices share at least three disadvantages. First, the costs of these devices could prevent wide adoption in everyday life. Second, it is not convenient to carry and use the devices “on the go”. Last but not least, existing methods provide little immediate benefits or intrinsic motivation to users and thus may be tedious to track heart rate in a longitudinal setting. Figure 1. Real-time heart rate measurement via LivePulse Games (left: City Defender, right: Gold Miner). To overcome the limitations of existing techniques, we have developed LivePulse Games (LPG, figure 1) to measure users’ heart rates in real time by having them play serious games on unmodified mobile phones. LPG calculate heart rates by detecting the transparency change of fingertips via the built-in camera (i.e. commodity camera 1 In both the preparation phase and the actual measurement stage. Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from Permissions@acm.org. CHI 2015, April 18 - 23 2015, Seoul, Republic of Korea Copyright 2015 ACM 978-1-4503-3145-6/15/04…$15.00 http://dx.doi.org/10.1145/2702123.2702502 Health Sensors & Monitoring CHI 2015, Crossings, Seoul, Korea 847 Balancing  accuracy  and  fun:  Designing   Camera  Based  Mobile  Games  for   Implicit  Heart  Rate  Monitoring   Teng  Han  et  al  (CHI  2015)     This  paper   •  Presents  "live  pulse  games"  for   smartphones  which  measure   pulse  during  play   •  The  smartphone  camera  is  used  as   controller  and  sensor  for  pulse.   •  This  allows  for  longitudinal   collecGon  of  heart  rate  data       InteracGon  design  
  25. 25. Pass the Ball: Enforced Turn-Taking in Activity Tracking John Rooksby, Mattias Rost, Alistair Morrison, Matthew Chalmers School of Computing Science, University of Glasgow, UK. {firstname.lastname}@glasgow.ac.uk ABSTRACT We have developed a mobile application called Pass The Ball that enables users to track, reflect on, and discuss physical activity with others. We followed an iterative design process, trialling a first version of the app with 20 people and a second version with 31. The trials were conducted in the wild, on users’ own devices. The second version of the app enforced a turn-taking system that meant only one member of a group of users could track their activity at any one time. This constrained tracking at the individual level, but more successfully led users to communicate and interact with each other. We discuss the second trial with reference to two concepts: social- relatedness and individual-competence. We discuss six key lessons from the trial, and identify two high-level design implications: attend to “practices” of tracking; and look within and beyond “collaboration” and “competition” in the design of activity trackers. Author Keywords: Activity Tracking; Mobile Health; Game. ACM Classification Keywords H.5.m. Information interfaces and presentation (e.g., HCI): Miscellaneous. INTRODUCTION The potential for smartphone-based activity trackers to support and encourage health related behaviour change has been widely recognised (see [14, 16, 18] for recent overviews). We have noticed that activity trackers are commonly designed as individual trackers that then have social features added to them. Typically, social features enable users to post an achievement such as a recent run or step-count to a social network site such as Facebook. In this paper we explore a social-first approach, reporting on an app we have developed and evaluated that takes interacting with others as prerequisite to tracking an activity. The app, Pass The Ball, is a team game in which players pass a virtual ball to each other. Only one user can have the ball at any one time, and only this user’s activity can be tracked by the app (the app awards activity points based on a simple motion tracking algorithm). Teams compete against each other to score the most points. This creates a coordination problem, one that requires users to think about and discuss not just their own activity but also that of others. For this work we adopted a “research through design” approach (see [13, 36]). We have created a mobile application and have studied its use in the wild on people’s own mobile phones. We have gone through this process iteratively (as is best practice in design [36]), producing and trialling the app for two weeks, then refining it and trialling it again for another two weeks. Gaver [13] argues that research through design is not about creating artefacts that embody, confirm or falsify theory, but artefacts that can be “annotated” by theory. In this paper we use two concepts from behaviour change theory as annotation: individual competence and social relatedness. Our work does not embody, confirm or falsify any particular theory, but treats these concepts as a way of discussing the relationship, similarities and differences of Pass The Ball to other activity trackers. Gaver views design not as a science, but as a process in which “we may build on one another’s results, but … also usefully subvert them” (p.946). Our app is subversive in that it prioritises social-relatedness over individual-competence, where the converse is the norm. BACKGROUND Pedometers have been widely available for a long time (they were introduced, in their modern form as step counters, by Yamasa in the 1960s). Recently, smartphone applications (apps) and networked hardware devices have begun to offer new possibilities for tracking steps and myriad other activities, sparking renewed interest in the relationship between tracking and health related behaviour change. Pedometers have been shown to have a positive effect on health related behaviour [34], and it seems a reasonable expectation that apps and networked hardware devices can have similar if not greater benefits. Studies such as [3, 4] are pointing to and cautiously confirming such benefits. However, with the range of new possibilities comes a large, complex design space; it is only beginning to become clear what the effects and relevancies of different designs are to behaviour change. In this paper we discuss our exploration of this design space. Over the last few years, researchers and developers have been creating apps and devices that augment tracking with social and game features. Apps such as SpyFeet [30] allow Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from Permissions@acm.org. CHI 2015, April 18 - 23 2015, Seoul, Republic of Korea Copyright is held by the owner/author(s). Publication rights licensed to ACM. ACM 978-1-4503-3145-6/15/04...$15.00 http://dx.doi.org/10.1145/2702123.2702577 Experience Design for Games CHI 2015, Crossings, Seoul, Korea 2417 InteracGon  design   Pass  the  ball:  Enforced  turn  taking  in   acGvity  tracking   John  Rooksby  et  al  (CHI2015)     This  paper:   •  Presents  a  novel  pedometer  based   game  where  team  members  take   it  in  turn  to  count  their  steps   •  Discusses  user  trials  of  two   versions  of  the  game   •  Discusses  the  experiences  and   pracGcaliGes  of  cooperaGve   tracking      
  26. 26. Rethinking the Mobile Food Journal: Exploring Opportunities for Lightweight Photo-Based Capture Felicia Cordeiro1 , Elizabeth Bales1,2 , Erin Cherry3 , James Fogarty1 1 Computer Science & Engineering 2 Human Centered Design & Engineering DUB Group, University of Washington {felicia0, lizbales, jfogarty}@cs.washington.edu ABSTRACT Food choices are among the most frequent and important health decisions in everyday life, but remain notoriously difficult to capture. This work examines opportunities for lightweight photo-based capture in mobile food journals. We first report on a survey of 257 people, examining how they define healthy eating, their experiences and challenges with existing food journaling methods, and their ability to interpret nutritional information that can be captured in a food journal. We then report on interviews and a field study with 27 participants using a lightweight, photo-based food journal for between 4 to 8 weeks. We discuss mismatches between motivations and current designs, challenges of current approaches to food journaling, and opportunities for photos as an alternative to the pervasive but often inappropriate emphasis on quantitative tracking in mobile food journals. Author Keywords Personal Informatics; Self-Tracking; Food Journals; Photos. ACM Classification Keywords H.5.m. Information interfaces and presentation (e.g., HCI). INTRODUCTION Food choices are among the most frequent and important health decisions in everyday life, yet it remains notoriously difficult to understand our food choices. People eat in many different contexts and have widely varying motivations and constraints on food. Being mindful of the quality and quantity of food choices is a crucial component of a healthy life [35,36], and food journals can be effective for monitoring food intake [8,15]. The implications of food also go beyond health, as food is central to our daily experiences and our relationship with food varies according to personal contexts and goals [14]. But food journals impose high burdens that detract from their potential benefit [11,12]. Effective food journaling is thus a grand challenge for personal informatics. Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from Permissions@acm.org. CHI 2015, April 18 - 23 2015, Seoul, Republic of Korea Copyright 2015 ACM 978-1-4503-3145-6/15/04$15.00 http://dx.doi.org/10.1145/2702123.2702154 3 Computer Science University of Rochester erinc@cs.rochester.edu Figure 1. An entry in our lightweight photo-based food journal. No calorie or nutrition information is shown, as the journal instead logs meal enjoyment, location context, and social context. Automated sensing has proven powerful in some domains of human activity, but remains out of reach for food despite recent advances [1,3,18,27,29,32,38]. It is also unclear whether automation is desirable, as it may undermine in-the-moment awareness created by food journaling [36]. Some existing methods involve taking photos of food as an intermediate step toward collecting underlying nutritional information [18,27,38]. We step further back, asking what people want to capture about food and what value photos themselves might provide in a lightweight food journal. Our work examines lightweight photo-based capture and reflection, reconsidering the common assumption that a quantitative approach is required. We first present a survey examining how people define healthy eating, experiences and challenges with existing food journals, and how people interpret the healthiness of food presented as either photos or nutrition labels. We then present interviews and field deployments of a lightweight, photo-based mobile food journal. A total of 27 people with varying food goals from two distinct trials use our application to journal for between 4 to 8 weeks. We explore reactions to a design focused on food photos in lieu of nutritional information and examine the value of food photos with regard to their goals. Finally, we discuss our results in the context of rethinking challenges and opportunities in the design of mobile food journals. InteracGon  design   Rethinking  the  mobile  food  journal:   Exploring  opportuniGes  for   lightweight  photo-­‐based  capture.   Felicia  Cordeiro  et  al  (CHI2015)     This  paper   •  Presents  a  survey  of  experiences   and  challenges  in  food  journaling   •  Presents  a  field  trial  of  a  photo   based  system  for  journaling   •  Discusses  the  pros  and  cons  of   photo  based  and  log  based   approaches.  
  27. 27. Personal Tracking as Lived Informatics John Rooksby, Mattias Rost, Alistair Morrison, Matthew Chalmers School of Computing Science, University of Glasgow, UK. {john.rooksby, mattias.rost, alistair.morrison, matthew.chalmers}@glasgow.ac.uk ABSTRACT This paper characterises the use of activity trackers as ‘lived informatics’. This characterisation is contrasted with other discussions of personal informatics and the quantified self. The paper reports an interview study with activity tracker users. The study found: people do not logically organise, but interweave various activity trackers, sometimes with ostensibly the same functionality; that tracking is often social and collaborative rather than personal; that there are different styles of tracking, including goal driven tracking and documentary tracking; and that tracking information is often used and interpreted with reference to daily or short term goals and decision making. We suggest there will be difficulties in personal informatics if we ignore the way that personal tracking is enmeshed with everyday life and people’s outlook on their future. Author Keywords Activity Tracking; Data; Qualitative methods ACM Classification Keywords H.5.m. Information interfaces and presentation (e.g., HCI): Miscellaneous. INTRODUCTION Over the past few years there has been a proliferation of mobile apps and consumer devices for tracking personal information, particularly those related to health and wellbeing (for example diet, weight, sleep, walking and exercise). Many apps can be downloaded for free or at low cost. Some physical devices (such as pedometers) cost trivial amounts (see [19]). Yet there is also a market for premium devices (see [11] for a discussion of the FitBit). Mobile phone manufacturers including Apple and Motorola have also begun to make specific provisions for activity tracking by, for example, incorporating always-on accelerometers into their latest high-end mobile devices. The advent of smart watches, smart glasses and other forms of wearable computing in the consumer domain is also likely to bring further innovation and proliferation in this area. Personal tracking is, however, not new. People have long been able to track and manage activities using diaries and/or personal computers. Tracking can in fact be traced back to at least Roman times (where trackers were used not as personal devices but for measuring the mobility of soldiers). However, with the popularity of smartphones and digital devices with built in accelerometers and location services, the area of personal tracking appears to be one of great investment and growth. Previous research in this area has predominantly focused on individual, researcher-supplied technologies. From a health research perspective, a tracker is either an instrument with which to measure activity, or an intervention to be applied across a cohort of people. Standard devices are used, and often treated as invisible lenses on activity (e.g. [19, 21]). In health research, consumer trackers are usually used, whereas evaluation in HCI is usually of a novel prototype (e.g. [13, 10]). In HCI the devices themselves are not treated invisibly but, as with health research, evaluation is predominantly of an individual technology and oriented to intervention. There is some research looking at integration of technologies, notably Bentley et al.’s [2] work on health mashups for behaviour change. Yet even here the researchers selected what the study participants should use. The agency of the people using such technologies is too often denied; Maitland et al.’s [12] study of weight loss and Mamykina et al.’s [14] study of diabetes management are rare exceptions. They point out that people choose, use, interweave and abandon various technologies in their own, lived efforts to improve their health. They found people were not changing their behaviour because of a technology, but were using technology because they wanted to change. What people decide to track using consumer products, what trackers they decide to use, and how they use them over days, weeks, months and potentially lifetimes remains understudied. Studying individual, researcher supplied technology is somewhat at odds with the literature around personal informatics, which suggests that people can and should track various aspects of their lives. It is also somewhat at odds with what we already know about smartphone use. Barkhuus et al. [1] have pointed out that Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from Permissions@acm.org. CHI 2014, April 26 - May 01 2014, Toronto, ON, Canada. Copyright is held by the owner/author(s). Publication rights licensed to ACM. ACM 978-1-4503-2473-1/14/04 $15.00 http://dx.doi.org/10.1145/2556288.2557039 ACM 978-1-4503-2473-1/14/04 $15.00. http://dx.doi.org/10.1145/2556288.2557039 Understanding  pracGces   Personal  tracking  as  lived  informaGcs   John  Rooksby  et  al  (CHI2014)     This  paper   •  Presents  a  study  of  users  of   personal  trackers  (apps  and   wearables)   •  Draws  anenGon  to  different  styles   and  purposes  of  tracking   •  Draws  anenGon  to  the  ways  in   which  people  use  mulGple   trackers  and  switch  over  Gme    
  28. 28. Snot, Sweat, Pain, Mud, and Snow - Performance and Experience in the Use of Sports Watches 1st Author Name Affiliation Address e-mail address Optional phone number 2nd Author Name Affiliation Address e-mail address Optional phone number 3rd Author Name Affiliation Address e-mail address Optional phone number ABSTRACT We have conducted interviews with ten elite and recreational athletes to understand their experiences and engagement with endurance sport and personal and wearable sports technology. In the interviews, athletes emphasized the experiential aspects of doing sports and the notion of feeling was repeatedly used to talk about their activities. The technology played both an instrumental role in measuring performance and feeding bio-data back to them, and an experiential role in supporting and confirming the sport experience. To guide further interaction design research in the sports domain, we suggest two interrelated ways of looking at sports performances and experiences, firstly through the notion of a measured sense of performance, and secondly as a lived-sense of performance. Author Keywords Sports, experience, heart rate monitors, feeling. ACM Classification Keywords H.5.m. Information interfaces and presentation (e.g., HCI): Miscellaneous. INTRODUCTION Measuring results as accurately as possible is the primary way of assessing performance in sports, and consequently an important driving force in the development of sports technology. Here, we attempt to expand what the notion of performance means in sports, and the implications this has for interaction design research. Endurance sports such as running, cycling, triathlon, and cross-country skiing is currently growing remarkably. This is seen in increasing participation in races and organized training groups, and the development of new forms of mass races such as ultra-marathons, swim-run races over large distances, and trail running. Hand in hand with this, a proliferation of mobile technologies dedicated to sports and exercise has emerged, such as watches, sensors, and apps. This technical and commercial development has brought increased attention of HCI to the domain of sports and novel ways of using technology in sports activities, examples include social sharing of heart-rate during cycling [33], interactive shirts for sharing running data [32], and novel feedback mechanisms for golfers [27], skiers [20], and runners [26]. So far, a significant part of the research in interactive sports technologies has been concerned with socio-motivational technologies [2, 22, 23], new forms of play [12, 15], gamification [5], bodily interaction [34], and explorations of technical challenges for wearable sports technologies [3, 4, 20, 37]. However, when it comes to supporting, enhancing or augmenting the sporting activities through deep engagement with the details of their execution, it turns out that less work has been reported. Counter-examples include [11, 18] which led to an innovative training device for advanced psychomotor skills in handball, Stienstra et al.’s. [33] work on sonification of speed skating motion; and Spelmezan’s [32] vibrational feedback for snowboarding instruction. By drawing on a set of “in-depth interviews” with elite and recreational athletes, we map out key characteristics of athletes’ experiences and engagement in endurance sports, and technologies that support this in various ways such as sports watches and heart-rate monitors. For a large group of engaged athletes, there is a close connection between the experience of the sport and how it is performed, and sports is valued for a lot more than pure measurable performance. Moreover, it is not only goals and results that motivate athletes, but a rich flora of additional factors such as the reward from meeting various challenges, the ability to manage exertion and fatigue, and the sheer fun and enjoyment of running, skiing, and cycling. Reoccurring in our material was the notion of feeling, and the various roles it played in building instrumental and experiential aspects of the athletes’ performances. As put by one of our participants: “.. and then you run ten kilometers and it feels like… well, did I run or am I going to run? I don’t feel the difference in my legs. That feeling is priceless in a way.” Karl Paste the appropriate copyright/license statement here. ACM now supports three different publication options: ACM copyright: ACM holds the copyright on the work. This is the historical approach. License: The author(s) retain copyright, but ACM receives an exclusive publication license. Open Access: The author(s) wish to pay for the work to be open access. The additional fee must be paid to ACM. This text field is large enough to hold the appropriate release statement assuming it is single-spaced in TimesNewRoman 8 point font. Please do not change or modify the size of this text box. Every submission will be assigned their own unique DOI string to be included here. Understanding  pracGces   Snot,  Sweat,  Pain,  Mud  and  Snow  –   Performance  and  Experience  in  the   Use  of  Sports  Watches   Jakob  Tholander  et  al  (CHI2015)     This  paper   •  Presents  an  interview  study  with   endurance  athletes     •  Draws  anenGon  to  feelings  and   the  roles  they  play  in  sport   •  Points  out  that  trackers  quanGfy   things  that  can  be  felt  and   therefore  help  understand  feeling   and  represent  feeling    
  29. 29. Concealing or Revealing Mobile Medical Devices? Designing for Onstage and Offstage Presentation Aisling Ann O’Kane UCL Interaction Centre University College London London, United Kingdom a.okane@cs.ucl.ac.uk Yvonne Rogers UCL Interaction Centre University College London London, United Kingdom y.rogers@ucl.ac.uk Ann Blandford UCL Interaction Centre University College London London, United Kingdom a.blandford@ucl.ac.uk ABSTRACT Adults with Type 1 Diabetes have choices regarding the technology they use to self-manage their chronic condition. They can use glucose meters, insulin pumps, smartphone apps, and other technologies to support their everyday care. However, little is known about how their social lives might influence what they adopt or how they use technologies. A multi-method study was conducted to examine contextual factors that influence their technology use. While individual differences play a large role in everyday use, social factors were also found to influence use. For example, people can hide their devices in uncertain social situations or show them off to achieve a purpose. We frame these social behaviours using Goffman’s theatre metaphor of onstage and offstage behaviour, and discuss how this kind of analysis can inform the design of future mobile medical devices for self-management of chronic conditions. INTRODUCTION Type 1 Diabetes (T1D) is a serious chronic condition that can involve the use of various mobile medical devices to support everyday self-care, and people’s adoption and use of diabetes technologies can differ significantly as devices become individually appropriated [36]. The range of T1D technologies includes glucose meters, continuous glucose meters, insulin pumps, and mobile phone applications. As T1D devices are mobile and need to be used in various contexts, it is important to understand how user experience might influence how devices are used in practice. T1D is an auto-immune chronic condition that is often associated with childhood onset [27], but people of all ages can be diagnosed with it. It involves the pancreas producing insufficient quantities of insulin, a hormone required for the regulation of blood glucose (BG), but the condition can be managed [21]. For T1D, careful self-management practices are encouraged by medical practitioners: low BG levels (hypoglycemia, or ‘hypos’) can lead to immediate health concerns, including feeling physically ill or even falling unconscious, while excess levels of BG (hyperglycemia or ‘hypers’) can eventually culminate in complications, such as eye, foot, kidney, and heart disease. Personal management practices include calculating medication doses to inject based on factors such as personal situation (e.g. digested sugars and carbohydrates, exercise, sickness, and stress), temperature/weather, their current BG level, and past experience. Balancing BG levels with ingested glucose and injected insulin can control the condition, significantly reducing the impact on a person’s life. Most diabetes care involves some form of self- management. This means people with diabetes are “more than passive recipients of medical expertise” [10]. Lutfey and Wishner [22] suggest that the term ‘compliance’ should not be used in efforts to improve self-management practices. Instead, they propose using ‘adherence’, which suggests appropriate autonomy in defining and following self-management plans for diabetes. However, people’s plans are not necessarily the same as the actions they take: actions are contingent on the unfolding context [39], which is relational, dynamic, occasioned, and arising from the on- going activity [9]. This is of particular relevance when looking at the self-management plans of people with T1D, where self-management occurs on a “daily basis within the context of the other goals, priorities, health issues, family demands, and other personal concerns that make up their lives” [10]. Self-management practices vary [37] but there is little research on how mobile T1D technologies are chosen to be used for everyday self-management and how everyday social life might influence practice. To address this gap, we conducted three user studies that examined how T1D devices are adopted, carried, and used. We used contextual interviews, a diary study, and observation of a T1D group meet-up. In the data analysis reported here, we used Goffman’s theatre metaphor of how people present themselves to others. This conceptual framing provides insight into the nuanced ways adults with TID conceal or reveal the use of mobile self-management devices in social situations, which could benefit the design of future mobile self-management devices for chronic conditions. Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from Permissions@acm.org. CHI 2015, April 18 - 23, 2015, Seoul, Republic of Korea Copyright is held by the owner/author(s). Publication rights licensed to ACM. ACM 978-1-4503-3145-6/15/04…$15.00 http://dx.doi.org/10.1145/2702123.2702453 Understanding  pracGces   Concealing  or  Revealing  Mobile   Medical  Devices?  Designing  for   Onstage  and  Offstage  PresentaGon.   Aisling  O'Kane  et  al  (CHI  2015)     This  paper     •  Explores  the  occasions  in  which   adults  with  type  1  diabetes   conceal  or  reveal  their   technologies.   •  Discusses  how  users  seek  to   customise  technologies  to  bener   suit  social  situaGons    
  30. 30. A Stage-Based Model of Personal Informatics Systems Ian Li1 , Anind Dey1 , and Jodi Forlizzi1,2 1 Human Computer Interaction Institute, 2 School of Design Carnegie Mellon University, Pittsburgh, PA 15213 ianli@cmu.edu, {anind, forlizzi}@cs.cmu.edu ABSTRACT People strive to obtain self-knowledge. A class of systems called personal informatics is appearing that help people collect and reflect on personal information. However, there is no comprehensive list of problems that users experience using these systems, and no guidance for making these systems more effective. To address this, we conducted surveys and interviews with people who collect and reflect on personal information. We derived a stage-based model of personal informatics systems composed of five stages (preparation, collection, integration, reflection, and action) and identified barriers in each of the stages. These stages have four essential properties: barriers cascade to later stages; they are iterative; they are user-driven and/or system-driven; and they are uni-faceted or multi-faceted. From these properties, we recommend that personal informatics systems should 1) be designed in a holistic manner across the stages; 2) allow iteration between stages; 3) apply an appropriate balance of automated technology and user control within each stage to facilitate the user experience; and 4) explore support for associating multiple facets of people’s lives to enrich the value of systems. Author Keywords Personal informatics, collection, reflection, model, barriers ACM Classification Keywords H5.m. Information interfaces and presentation (e.g., HCI): Miscellaneous. General Terms Design, Human Factors INTRODUCTION AND MOTIVATION The importance of knowing oneself has been known since ancient times. Ancient Greeks who pilgrimaged to the Temple of Apollo at Delphi to find answers were greeted with the inscription “Gnothi seauton” or “Know thyself”. To this day, people still strive to obtain self-knowledge. One way to obtain self-knowledge is to collect information about oneself—one’s behaviors, habits, and thoughts—and reflect on them. Computers can facilitate this activity because of advances in sensor technologies, ubiquity of access to information brought by the Internet, and improvements in visualizations. A class of systems called personal informatics is appearing that help people collect and reflect on personal information (e.g., Mint, http://mint.com, for finance and Nike+, http://nikeplus.com, for physical activity). Personal informatics represents an interesting area of study in human-computer interaction. First, these systems help people better understand their behavior. While many technologies inform people about the world, personal informatics systems inform people about themselves. Second, people participate in both the collection of behavioral information as well as the exploration and understanding of the information. This poses demands on users that need to be explored. Finally, we do not know all the problems that people may experience with personal informatics systems. We know that people want to get information about themselves to reflect on, and that systems that support this activity need to be effective and simple to use. Identifying problems that people experience in collecting and making sense of personal information while using such systems is critical for designing and developing effective personal informatics. To date, there is no comprehensive list of problems that users experience using these systems. Toward this end, we conducted surveys and interviews with people who collect and reflect on personal information. From this, we derived a model of personal informatics systems organized by stages, which emphasizes the interdependence of the different parts of personal informatics systems. We provide three main contributions in this paper: 1) we identify problems across personal informatics tools, 2) we introduce and discuss a model that improves the diagnosis, assessment, and prediction of problems in personal informatics systems, and 3) we make recommendations about how to improve existing systems and build new and effective personal informatics systems. In the next section, we provide a working definition of personal informatics and review related literature. We present the method and findings from our survey, and use them to introduce a stage-based model of personal informatics systems. We describe the barriers encountered in each stage and highlight opportunities for intervention within each stage. We also compare and analyze existing systems to demonstrate the use of the model for diagnosing Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. CHI 2010, April 10–15, 2010, Atlanta, Georgia, USA. Copyright 2010 ACM 978-1-60558-929-9/10/04....$10.00. CriGcal  perspecGves   A  stage  based  model  of  personal   informaGcs  systems   Ian  Li  et  al  (CHI2010)     This  paper   •  Introduces  and  defines  the  field  of   "Personal  InformaGcs"   •  IdenGfies  common  problems   across  personal  informaGcs   systems   •  Introduces  a  model  of  personal   informaGcs  for  systems  designers  
  31. 31. Problematising Upstream Technology through Speculative Design: The Case of Quantified Cats and Dogs Shaun Lawson, Ben Kirman, Conor Linehan, Tom Feltwell, Lisa Hopkins Lincoln Social Computing Research Centre University of Lincoln, UK {slawson, bkirman, clinehan, tfeltwell, lhopkins} @ lincoln.ac.uk ABSTRACT There is growing interest in technology that quantifies aspects of our lives. This paper draws on critical practice and speculative design to explore, question and problematise the ultimate consequences of such technology using the quantification of companion animals (pets) as a case study. We apply the concept of ‘moving upstream’ to study such technology and use a qualitative research approach in which both pet owners, and animal behavioural experts, were presented with, and asked to discuss, speculative designs for pet quantification applications, the design of which were extrapolated from contemporary trends. Our findings indicate a strong desire among pet owners for technology that has little scientific justification, whilst our experts caution that the use of technology to augment human-animal communication has the potential to disimprove animal welfare, undermine human-animal bonds, and create human-human conflicts. Our discussion informs wider debates regarding quantification technology. Author Keywords Personal informatics; critical design; design fiction; animal- computer interaction; the Quantified Dog. ACM Classification Keywords H.5.m. Information interfaces and presentation (e.g., HCI): Miscellaneous. INTRODUCTION HCI, as a discipline, is increasingly concerned with the wider social and cultural implications of design practice [5, 6]. Dunne and Raby [14] argue that design as critique, through practices such as speculative design, can be valuable in the problematisation of technologies. They suggest that by “moving upstream and exploring ideas before they become products…designers can look into the possible consequences of technological applications before they happen” [14]. This paper uses the perspectives of critical and speculative design in order to explore an area of near-future/upstream technology that is of substantial interest to both commercial developers and researchers – the “quantification of everything” via the deployment of technology that quantifies multiple aspects of our lives. Consumers now have access to a plethora of interactive web and mobile apps, often coupled with sensors, which can facilitate the casual collection, aggregation, visualization and sharing of data about the self. As observed in [48], technology has been available to measure e.g. “sleep, exercise, sex food, mood, location, alertness, productivity and even spiritual wellbeing” for quite some time. Engagement with such self-tracking and monitoring is part of an inter-related set of practices variously labelled as personal informatics and the quantified-self. These labels emphasize that it is the self that is the object under scrutiny, however it is also apparent that consumers will soon have access to technology that can also track, measure, log and interpret the behaviour of not only the self but of the people and things that are important to them and that surround them in their everyday lives; this could, for instance, include their partners and children [35, 43], their elderly relatives [7], homes [12] and pets [16]. The deployment of quantifying technology has widely- claimed, and far-reaching, positive outcomes and benefits both for individuals and society [48, 25]. Indeed, the HCI and ubicomp communities continue to play a leading role in determining the direction of research in this area e.g. as is evidenced through a continuous rolling schedule of workshops such as [24, 31]. Through these workshops, and a growing body of published work, it is evident that there is sustained research interest, generally, in the technical, user- centred and privacy issues raised by the proliferation of personal tracking technology. However, there is limited existing research by the HCI, or indeed any, research community, that takes a more critical perspective on the design of tracking and quantifying technologies, and that, for instance, challenges the positivist assumptions about its longer term implications. In this paper we present a case study that takes a critical approach towards the understanding of the implications of the increasing prevalence, and unquestioning acceptance, of Paste the appropriate copyright/license statement here. ACM now supports three different publication options: ACM copyright: ACM holds the copyright on the work. This is the historical approach. License: The author(s) retain copyright, but ACM receives an exclusive publication license. Open Access: The author(s) wish to pay for the work to be open access. The additional fee must be paid to ACM. This text field is large enough to hold the appropriate release statement assuming it is single-spaced in TimesNewRoman 8 point font. Please do not change or modify the size of this text box. Every submission will be assigned their own unique DOI string to be included here. CriGcal  perspecGves   ProblemaGsing  upstream  technology   through  speculaGve  design:  The  case   of  quanGfied  cats  and  dogs   Shaun  Lawson  et  al  (CHI2015)     This  paper   •  Argues  that  we  too  readily  accept   ideas  around  the  quanGfied  self   and  'quanGfied  everything'     •  They  use  a  design  ficGon  based   approach  to  explore  problems   with  "upstream  technology"  for   quanGfying  cats  and  dogs.    
  32. 32. CriGcal  perspecGves   How  to  evaluate  technologies  for   health  behaviour  change  in  HCI   research   Predrag  Klasnja  et  al  (CHI2011)     This  paper   •  Argues  that  the  role  of  HCI  cannot   be  to  demonstrate  behaviour   change,  which  requires  large,  long   term  studies  (RCTs)   •  Argues  that  evaluaGon  of  new   technology  should  be  field  trials  of   designs  linked  to  behavioural   change  strategies       How to Evaluate Technologies for Health Behavior Change in HCI Research Predrag Klasnja1 , Sunny Consolvo3 , & Wanda Pratt1,2 1 Information School & DUB group University of Washington Seattle, WA 98195, USA klasnja@uw.edu 2 Biomedical & Health Informatics University of Washington Seattle, WA 98195, USA wpratt@uw.edu 3 Intel Labs Seattle Seattle, WA 98105, USA sunny.consolvo@intel.com ABSTRACT New technologies for encouraging physical activity, healthy diet, and other types of health behavior change now frequently appear in the HCI literature. Yet, how such technologies should be evaluated within the context of HCI research remains unclear. In this paper, we argue that the obvious answer to this question—that evaluations should assess whether a technology brought about the intended change in behavior—is too limited. We propose that demonstrating behavior change is often infeasible as well as unnecessary for a meaningful contribution to HCI research, especially when in the early stages of design or when evaluating novel technologies. As an alternative, we suggest that HCI contributions should focus on efficacy evaluations that are tailored to the specific behavior-change intervention strategies (e.g., self-monitoring, conditioning) embodied in the system and studies that help gain a deep understanding of people’s experiences with the technology. Author Keywords Evaluation methods, behavior change, health informatics, user studies. ACM Classification Keywords H5.2 Information interfaces and presentation (e.g., HCI): User interfaces (Evaluation/Methodology). J.3 Life and Medical Sciences: Medical information systems. General Terms Experimentation, measurement. INTRODUCTION In the last several years, there has been an explosion of HCI research on technologies for supporting health behavior change. HCI researchers have developed systems for encouraging physical activity [2,7,8,24], healthy diet [12,17,23], glycemic control in diabetes [26,39], and self- regulation of emotions [31]. Work in this area is rapidly becoming a staple at many of the field’s preeminent publishing venues. This work has the potential to make a meaningful impact on society. The prevalence of chronic diseases such as diabetes, obesity, and coronary heart disease continue to rise and are now responsible for over 70% of U.S. healthcare expenditures [20]. Some of the most important risk factors for these conditions are behavioral, including smoking, physical inactivity, excessive food intake, and diets heavy in trans fats. A successful change in these behaviors is a fundamental aspect of both prevention and effective management of chronic conditions, as well as an important contributor to health and wellbeing more broadly. Due to their low cost, high penetration, and integration in people’s everyday lives, technologies such as mobile phones, web applications, and social networking tools hold great promise for supporting individuals as they strive to adopt and sustain health-promoting behaviors. HCI research can significantly contribute to the design of innovative and effective tools that help people in these efforts. However, as HCI researchers increasingly engage in the design of systems for health behavior change, an important question arises: how should interventions for health behavior change be evaluated within the context of HCI research? The question is twofold. First, what types of evaluations are appropriate and useful for systems that HCI researchers in this area are developing? And second, how should the research output of this work—primarily in the form of publications—be evaluated? These questions are key, we believe, to moving this area of HCI forward, and their careful consideration should aid both researchers and reviewers working in this area. In this paper, we argue that the obvious answer to these questions—namely, that the goal of an evaluation of a technology for health behavior change should be to show that the technology brought about the intended change in behavior—is too limited. We argue that behavior change in the traditional clinical sense is not the right metric for evaluating early stage technologies that are developed in the context of HCI research. However, a narrower notion of efficacy, one that tailors outcome measures to the particular intervention strategies a technology employs, can enable HCI researchers to test whether their systems are doing what they are intended to do even at early stages of development. Just as importantly, qualitative studies that Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. CHI 2011, May 7–12, 2011, Vancouver, BC, Canada. Copyright 2011 ACM 978-1-4503-0267-8/11/05...$10.00.
  33. 33. Summary   •  In  this  lecture  I  have   –  Given  examples  of  self  tracking  technology  and   applicaGons   –  Given  a  brief  history  of  tracking,  poinGng  out  that  it  is  not   a  new  area   •  Discussed  the  relaGonship  of  tracking  with   –  Mobile  health   –  Health  behaviour  change   •  Illustrated  the  role  of  HCI  with  a  selecGon  of  papers  from  CHI   (the  main  annual  HCI  conference)    
  34. 34. References   1.  Consolvo,  S.,  Everin,  K.,  Smith,  I.,  Landay,  J.  (2006)  Design  requirements  for  technologies  that   encourage  physical  acGvity.  Proceedings  of  ACM  CHI  2006,  457-­‐466.   2.  Consolvo,  S.,  McDonald,  D.,  Toscos,  T.,  et  al  (2008)  AcGvity  sensing  in  the  wild:  A  field  trial  of   UbiFit  Garden.  Proceedings  of  ACM  CHI  2008,  1797-­‐1806.   3.  Cordeiro,  F.,  Bales,  E.,  Cherry,  E.,  Fogarty,  J.  (2015)  Rethinking  the  mobile  food  journal:   Exploring  opportuniGes  for  lightweight  photo  based  capture.  Proceedings  of  ACM  CHI  2015,   3207-­‐3216.   4.  Crawford,  K.,  Lingel,  J.,  &  Karppi,  T.  (2015)  Our  metrics,  our  selves:  A  hundred  years  of  self-­‐ tracking  from  the  weight  scale  to  the  wrist  wearable  device.  European  Journal  of  Cultural   Studies  2015,  18(4-­‐5),  479-­‐496.   5.  Han,  T.,  Xiao,  X.,  Shi,  L.,  Canny,  J.,  Wang,  J.  (2015)  Balancing  accuracy  and  fun:  designing   camera  based  mobile  games  for  implicit  heart  rate  monitoring.  Proceedings  of  ACM  CHI   2015,  847-­‐856.   6.  Khot,  R.A.,  Lee,  J.,  Aggarwal,  D.,  Hjorth,  L.,  Mueller,  F.  (2015)  TastyBeats:  Designing  palatable   representaGons  of  physical  acGvity.  Proceedings  of  ACM  CHI  2015,  2933-­‐2942.        
  35. 35. References   7.  Klasnja,  P.,  Consolvo,  S.,  &  Pran,  W.  (2011)  How  to  evaluate  technologies  for  health   behaviour  chnage  in  HCI  research.  Proceedings  of  ACM  CHI  2011,  3063-­‐3072.   8.  Klasnja,  P.,  Pran,  W.  (2011)  Healthcare  in  the  pocket:  Mapping  the  space  of  mobile-­‐phone   intervenGons.  Journal  of  Biomedical  InformaGcs  45  (2012)  184-­‐198.   9.  Lawson,  S.,  Kirman,  B.,  Linehan,  C.,  Feltwell,  T.,  Hopkins,  L.  (2015)  ProblemaGsing  upstream   technology  through  speculaGve  design:  The  case  of  quanGfied  cats  and  dogs.  Proceedings  of   CHI  2015.  2663-­‐2672.   10.  Li,  I.,  Dey,  A.,  &  Forlizzi,  J.  (2010)  A  stage-­‐based  model  of  personal  informaGcs  systems.   Proceedings  of  ACM  CHI  2010,  557-­‐566.   11.  Mueller,  F.,  Muirhead,  M.,  (2015)  Jogging  with  a  quadcopter.  Proceedings  of  ACM  CHI  2015.   2023-­‐2032.   12.  O'Kane,  A.,  Rogers,  Y.,  Blandford,  A.  (2015)  Concealing  or  revealing  mobile  devices?   Designing  for  onstage  and  offstage  presentaGon.  Proceedings  of  ACM  CHI  2015,  1689-­‐1698.    
  36. 36. References   13.  Olla,  P.,  &  Shimskey,  C.  (2014)  mHealth  taxonomy:  a  literature  survey  of  mobile  health   applicaGons.  Health  Technol.  (2014)  4:299-­‐308   14.  Rooksby,  J.,  Rost,  M.,  Morrison,  A.,  &  Chalmers,  M.  (2014)  Pass  the  ball:  Enforced  turn  taking   in  acGvity  tracking.  Proceedings  of  ACM  CHI  2015,  2417-­‐2426.   15.  Rooksby,  J.,  Rost,  M.,  Morrison,  A.,  &  Chalmers,  M.  (2014)  Personal  tracking  as  lived   informaGcs.  Proceedings  of  ACM  CHI  2014,  1163-­‐1172.   16.  Simm,  W.,  Ferrario,  M.A.,  Gradinar,  A.,  Whinle,  J.  (2014)  Prototyping  Clasp:  ImplicaGons  for   designing  digital  technology  for  and  with  adults  with  auGsm.  Proceedings  of  ACM  DIS2014,   345-­‐354.   17.  Tholander,  J.,  Nylander,  S.  (2015)  Snot,  Sweat,  Pain,  Mud,  and  Snow:  Performance  and   experience  in  the  use  of  sportswatches.  Proceedings  of  ACM  CHI  2015.  2913-­‐2922.        
  37. 37. Images   Apple  watch  –  apple.com   MyFitnessPal  app  –  myfitnesspal.com   Withings  scales  –  withings.com   Moodnotes  app  –  Ustwo.com   Diabetes  devices  -­‐  hnp://news.utoronto.ca/meet-­‐bant-­‐diabetes-­‐iphone-­‐app   Argus  app  –  azumio.com   Digital  stress  –  from  Simm  et  al  2014.   Manpo-­‐Meter  –  hnp://www.yamasa-­‐tokei.co.jp/   Penny  scales  –  from  Crawford  et  al  2015.   Mobile  health  taxonomy  –  from  Olla  &  Shimskey  2014.          

×