Behavioural science for wearable technology and the quantified workplace
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This document discusses the capabilities of wearable technology to track and analyze human behavior and physiology. It summarizes research showing that wearables can detect stress levels, predict personality traits, and identify physical activities like sitting, walking or cycling with high accuracy by collecting data from sensors. However, it notes that sustained long-term use of wearables is challenging, with many users stopping use within 6-12 months. It also discusses challenges regarding data access, ownership and privacy.
Behavioural science for wearable technology and the quantified workplace
- 1. Behavioural science for wearable technology and the quanti鍖ed workplace Dr Lukasz Piwek
- 3. GPS traces can be used to tell your identity and predict where you are likely to go next ? de Montjoye et al. (2013a) Song et al. (2010) Do & Garcia-Perez (2014)
- 4. stress level can be detected with 80% accuracy by capturing only a few words with microphone Lu et al. (2012)
- 5. call logs, SMS logs, Bluetooth scans, and application usage can be used to predict personality traits with up to 70% accuracy de Montjoye et al. (2013b) Chittaranjan et al. (2013)
- 6. accelerometers can be used to predict whether youre sitting, walking, jogging, cycling, driving or sleeping with up to 95% accuracy Khalil & Glal, 2009 He & Li, 2013 Behar et al. (2013)
- 7. Image source: Apple, Nike, Fitbit, Motorola, Jawbone, Microsoft, Withings, Neurosky, Duoferility, Nuubo
- 8. =
- 9. Headbands Camera clips Sensors embedded in clothing Smartwatches Sociometric badges OXI ALT ECG EMG EEG OXI ALT ECG EMG EEG Accelerometer Electrocardiogram Microphone Oximeter Electromyorgaph Electroencephalogram Thermometer Electrodermograph Location GPS Digital camera Bluetooth proximity Pressure Altimeter Consumer health wearables Piwek, Ellis, Andrews, Joinson (2016) PLOS Medicine: 13 (2): e1001953
- 10. self-monitoring + feedback continuous intelligent detailed instant personalised Festinger, 1954 Mcfall and Hammen,1971 Kirsenbaum et al., 1981 Bandura, 1997 Wilbur et al., 2003 Womble et al., 2004 Williams et al., 2007 Du et al., 2011 Swan, 2012 Bird et al., 2013
- 11. high blood pressure high cholesterol level physical inactivity obesity 45%* *NHS The Atlas of Risk (2014)
- 12. Those three devices accounted for 97% of all smartphone-enabled activity trackers sold in 2013* *cmo.com Fitbit Jawbone UP Nike Fuelband
- 13. Battery life Data access User interface Reliability SecurityData ownership Build qualityFeedback Fitbit Jawbone UP Nike Fuelband
- 14. distance per day (km) days squash gym squash 5 10 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 fuelband jawbone average distance over 30 days (km) 0 2 4 6 8
- 16. Each new device should reduce the complexity of the system and increase the value of everything else in the ecosystem. Bill Buxton
- 17. *Ledger et al. (2014) 0% 25% 50% 75% 100% 0 3 6 9 12 15 18 21 24 time (months) rate of sustained use (%) 32% drop rate within 6 months 50% drop rate after 12 months
- 18. Self-monitoring in cycling Piwek, Joinson, Morvan (2015) Transportation Research Part A: 77, 126136
- 19. 33 features performance (e.g. tracking speed, distance traveled) social (e.g. joining challenges against other cyclists) mapping (e.g. viewing map with directions) other (e.g. answering a call)
- 20. speed distance duration simplicity, utility & relevance is critical
- 21. vs free1 year
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- 26. norms beliefs attitudes motivations personality traits cultural in鍖uences socio-economic factors
- 27. Strava louts & Big Behavioural Cycling Data Project in progress
- 28. Quanti鍖ed runner Project in progress
- 29. Project in progress Quanti鍖ed workplace
- 30. on off Andrews, Ellis, Shaw, Piwek (2015) PLOS One 10 (10): e0139004 Smartphone research methods PSYCHOLOGY SENSOR LAB TM NetPropagate Systems TM
- 31. Project in preparation PhD student co-supervision Digital footprints for behavioural pro鍖ling PSYCHOLOGY SENSOR LAB TM NetPropagate Systems TM
- 32. Project in preparation Awaiting grant application outcomes Sociometric wearables for research PSYCHOLOGY SENSOR LAB TM NetPropagate Systems TM
- 33. () without the proper behavioural design, without considering how new products and services fit into people's day-to-day lives, any new technology can be terrifying. That's where the challenge comes in. The task of making (new technology, new world version) can't be left up to engineers and technologists alone - otherwise we will find ourselves overrun with amazing capabilities that people refuse to take advantage of. Cliff Kuang Wired 10/2013
- 34. Prof Adam Joinson | Bath Dr David Ellis | Lancaster Dr Phoebe Moore | Middlesex Dr Sally Andrews | Nottingham Trent Prof Alan Tapp | UWE Dr Fiona Spotswood | UWE