title: Designing effective visualizations of habits data to aid clinical decision making.
abstract: BACKGROUND
  Changes in daily habits can provide important information regarding the overall health status of an individual. This research aimed to determine how meaningful information may be extracted from limited sensor data and transformed to provide clear visualization for the clinicians who must use and interact with the data and make judgments on the condition of patients. We ascertained that a number of insightful features related to habits and physical condition could be determined from usage and motion sensor data.
  
  
  METHODS
  Our approach to the design of the visualization follows User Centered Design, specifically, defining requirements, designing corresponding visualizations and finally evaluating results. This cycle was iterated three times.
  
  
  RESULTS
  The User Centered Design method was successfully employed to converge to a design that met the main objective of this study. The resulting visualizations of relevant features that were extracted from the sensor data were considered highly effective and intuitive to the clinicians and were considered suitable for monitoring the behavior patterns of patients.
  
  
  CONCLUSIONS
  We observed important differences in the approach and attitude of the researchers and clinicians. Whereas the researchers would prefer to have as many features and information as possible in each visualization, the clinicians would prefer clarity and simplicity, often each visualization having only a single feature, with several visualizations per page. In addition, concepts considered intuitive to the researchers were not always to the clinicians.
authors.affiliation: Brunel University, Uxbridge, UB8 3PH, UK. joost.defolter@brunel.ac.uk.
authors.forename: Joost
authors.initials: J
authors.lastname: de Folter
authors.affiliation: Brunel University, Uxbridge, UB8 3PH, UK. hulya.gokalp@brunel.ac.uk.
authors.forename: Hulya
authors.initials: H
authors.lastname: Gokalp
authors.affiliation: Chorleywood Health Centre, 15 Lower Rd, Chorleywood, Rickmansworth, WD3 5EA, UK. j.fursse@gmail.com.
authors.forename: Joanna
authors.initials: J
authors.lastname: Fursse
authors.affiliation: Brunel University, Uxbridge, UB8 3PH, UK. urvashi.sharma@brunel.ac.uk.
authors.forename: Urvashi
authors.initials: U
authors.lastname: Sharma
authors.affiliation: Brunel University, Uxbridge, UB8 3PH, UK. malcolm.clarke@brunel.ac.uk.
authors.forename: Malcolm
authors.initials: M
authors.lastname: Clarke
mesh_terms: D000368:Aged; D001291:Attitude of Health Personnel; D020000:Decision Support Systems, Clinical / Q000295:instrumentation*; D004867:Equipment Design; D005069:Evaluation Studies as Topic; D005260:Female; D016330:Frail Elderly; D006184:Habits; D006801:Humans; D007407:Interviews as Topic; D008297:Male; D018670:Monitoring, Ambulatory / Q000295:instrumentation* / Q000379:methods; D009038:Motion; D010364:Pattern Recognition, Visual; D036301:Qualitative Research; D017216:Telemedicine / Q000295:instrumentation* / Q000379:methods