© Phil Hurvitz, 2006Slide 1 (of 26) Validation of New Technologies and Methodologies for Measuring Physical Activity and Location in Real Time-Space Phil Hurvitz UrbDP PhD Colloquium

Validation of New Technologies and Methodologies for Measuring Physical Activity and Location in Real Time-Space © Phil Hurvitz, 2006 Overview Background The Multi-Sensor Board (MSB) Methods Expected data Analyses for validation Future research directions

Validation of New Technologies and Methodologies for Measuring Physical Activity and Location in Real Time-Space © Phil Hurvitz, 2006 Overview Background The Multi-Sensor Board (MSB) Methods Expected data Analyses for validation Future research directions

Validation of New Technologies and Methodologies for Measuring Physical Activity and Location in Real Time-Space © Phil Hurvitz, 2006 Background Submitted for Royalty Research Funding, Fall 2006

Validation of New Technologies and Methodologies for Measuring Physical Activity and Location in Real Time-Space © Phil Hurvitz, 2006 Background Physical activity (PA) is important for health maintenance Adequate PA decreases incidence of cancer, diabetes, cardiovascular disease US Surgeon General recommends 30 minutes of moderate exercise most days of the week Physical activity is difficult to measure objectively in free-living individuals An accurate, reliable, valid, unobtrusive device for measuring PA would be valuable for: research in health (obesity, rehab. medicine, etc.) consumer level electronics

Validation of New Technologies and Methodologies for Measuring Physical Activity and Location in Real Time-Space © Phil Hurvitz, 2006 Background MethodAdvantagesLimitations Direct observation  Best recording of physical activity (PA) type  Information on PA context  Applicable to children  Time consuming  Potential reactivity of study participant  Subjectivity of the observer  Not appropriate for large-scale studies Pedometers  Lightweight, portable  Simple, inexpensive  Appropriate for free-living conditions  Only walking or running steps, no recording of horizontal or upper-body movements  No information of specific activity, only total (daily) PA  No locational capability Accelerometers  Same advantages as pedometers  Recording of accelerations in more than one plane and for extended time period  Measurement of intensity; possibility of measuring a specific activity  No recording of horizontal or upper-body movements, carrying a load  Potential reactivity of study participant  No locational capability Questionnaires  Applicable in epidemiological studies  Valid for gross PA classification for a population (e.g., low vs. high)  Limited validity; no detailed information of PA; dependent on subject’s memory and interpretation  Not suited for PA assessment at the individual level IDEEA  Accurate measure of type and dose of several activity patterns  Expensive  Cumbersome; electrodes and wires may impede free movement  Validity limited to level walking and running; unknown if device senses changes in elevation  Not appropriate for large-scale studies  No locational capability adapted from Vanhees et al Comparison of physical activity measurement methods

Validation of New Technologies and Methodologies for Measuring Physical Activity and Location in Real Time-Space © Phil Hurvitz, 2006 Background Current consumer-level electronics GPS with heart-rate monitor accelerometer in shoe linked to iPod

Validation of New Technologies and Methodologies for Measuring Physical Activity and Location in Real Time-Space © Phil Hurvitz, 2006 Overview Background The Multi-Sensor Board (MSB) Methods Expected data Analyses for validation Future research directions

Validation of New Technologies and Methodologies for Measuring Physical Activity and Location in Real Time-Space © Phil Hurvitz, 2006 The Multi-Sensor Board (MSB) Multi-modal, microprocessor based sensor of multiple environmental variables, developed by UW & Intel 3D acceleration barometric pressure humidity temperature compass bearing light (daylight & fluorescent) audio location (from WiFi or GPS) 18 MHz for some measurements Internal miniSD (2 GB) storage Nokia cell phone for additional data storage/data transfer, auxiliary data logger

Validation of New Technologies and Methodologies for Measuring Physical Activity and Location in Real Time-Space © Phil Hurvitz, 2006 The Multi-Sensor Board (MSB) 1-second temporal resolution In a pilot project, 92% accuracy (Lester et al., 2005) MSB classifies measurements Hidden Markov models and Decision Stumps methods Operationalized in Matlab Transforms raw sensor data into classified activities: walk (up/down stairs) bicycle sit jog stand car/bus elevator (up/down)

Validation of New Technologies and Methodologies for Measuring Physical Activity and Location in Real Time-Space © Phil Hurvitz, 2006 The Multi-Sensor Board (MSB) from Lester et al. 2005

Validation of New Technologies and Methodologies for Measuring Physical Activity and Location in Real Time-Space © Phil Hurvitz, 2006 The Multi-Sensor Board (MSB) from Lester et al precision = true positive / (true positive + false positive) recall = true positive / (true positive + false negative)

Validation of New Technologies and Methodologies for Measuring Physical Activity and Location in Real Time-Space © Phil Hurvitz, 2006 Overview Background The Multi-Sensor Board (MSB) Methods Expected data Analyses for validation Future research directions

Validation of New Technologies and Methodologies for Measuring Physical Activity and Location in Real Time-Space © Phil Hurvitz, 2006 Methods Subjects 50 adults y ~50% male, 50% female ¿Twin registry? 7 day measurement period (to include 2 weekend days) Self-report diary, hourly PA questionnaire post-measurement (International Physical Activity Questionnaire — IPAQ)

Validation of New Technologies and Methodologies for Measuring Physical Activity and Location in Real Time-Space © Phil Hurvitz, 2006 Methods Diary (self-reported measurements) Hourly surveys on Nokia cell phone ¿Same activity classes as MSB classification?

Validation of New Technologies and Methodologies for Measuring Physical Activity and Location in Real Time-Space © Phil Hurvitz, 2006 Methods IPAQ (Catalyst WebQ)

Validation of New Technologies and Methodologies for Measuring Physical Activity and Location in Real Time-Space © Phil Hurvitz, 2006 Overview Background The Multi-Sensor Board (MSB) Methods Expected data Analyses for validation Future research directions

Validation of New Technologies and Methodologies for Measuring Physical Activity and Location in Real Time-Space © Phil Hurvitz, 2006 Expected data Diary report vs. MSB-classified (counts) Self-Reported (Diary) Activities BicyclingSittingWalking MSB Classified Activities Bicycling100 Sitting3213 Walking101 Pilot data from 42 diary entries: 50 subjects * 7 d * 16 h/d * 3600 s/h = 20,160,000 measurements 50 subjects * 7 d * 16 h/d = 5,600 diary entries

Validation of New Technologies and Methodologies for Measuring Physical Activity and Location in Real Time-Space © Phil Hurvitz, 2006 Expected data IPAQ Results ¿What to do with these? Compare self-reported (diary), MSB-classified, and IPAQ Durations? Statistical tests comparing durations?

Validation of New Technologies and Methodologies for Measuring Physical Activity and Location in Real Time-Space © Phil Hurvitz, 2006 Expected data Map data (not specifically part of the RRF proposal, but essential for future research)

Validation of New Technologies and Methodologies for Measuring Physical Activity and Location in Real Time-Space © Phil Hurvitz, 2006 Overview Background The Multi-Sensor Board (MSB) Methods Expected data Analyses for validation Future research directions

Validation of New Technologies and Methodologies for Measuring Physical Activity and Location in Real Time-Space © Phil Hurvitz, 2006 Analyses for validation (PA) Compare counts or durations of self-reported vs. MSB- classified PA Cohen’s Kappa statistic? Used to assess inter-rater reliability when observing or otherwise coding qualitative/ categorical variables. Kappa is considered to be an improvement over using % agreement to evaluate this type of reliability. Not inferential (no p-level) κ > 0.7 considered satisfactory Chi-square (observed vs. expected) for inferential test? Other statistics?

Validation of New Technologies and Methodologies for Measuring Physical Activity and Location in Real Time-Space © Phil Hurvitz, 2006 Analyses for validation (location) Obtain coordinates of location where diary was recorded Define a buffer at the radius of instrument precision Select buildings or parcels within buffer If any features within buffer match self- reported location, consider this a match ¿What analyses?

Validation of New Technologies and Methodologies for Measuring Physical Activity and Location in Real Time-Space © Phil Hurvitz, 2006 Overview Background The Multi-Sensor Board (MSB) Methods Expected data Analyses for validation Future research directions

Validation of New Technologies and Methodologies for Measuring Physical Activity and Location in Real Time-Space © Phil Hurvitz, 2006 Future Research Directions Size of spatial realm of activity, comparing low to high SES Patterns in locations of long dwell time Stay tuned … Ultimately: PA & Urban Form relationships?

Validation of New Technologies and Methodologies for Measuring Physical Activity and Location in Real Time-Space © Phil Hurvitz, 2006 I Want You! Pilot & Feasibility study is ongoing