Behavioural science for wearable technology and the quantified workplace
-
Upload
lukasz-piwek -
Category
Technology
-
view
298 -
download
3
Transcript of Behavioural science for wearable technology and the quantified workplace
GPS tracescan be usedto tell your identity and predictwhere you are likely to go next
?de Montjoye et al. (2013a) Song et al. (2010) Do & Garcia-Perez (2014)
stress level can be detectedwith 80% accuracyby capturing only a few wordswith microphoneLu et al. (2012)
call logs, SMS logs,Bluetooth scans, and application usagecan be used to predict personality traitswith up to 70% accuracyde Montjoye et al. (2013b) Chittaranjan et al. (2013)
accelerometerscan be used to predict whether you’re sitting,walking, jogging, cycling, driving or sleepingwith up to 95% accuracyKhalil & Glal, 2009 He & Li, 2013 Behar et al. (2013)
Image source: Apple, Nike, Fitbit, Motorola, Jawbone, Microsoft, Withings, Neurosky, Duoferility, Nuubo
Headbands
Camera clips
Sensors embedded in clothing
Smartwatches
Sociometric badges
OXI
ALTECG 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 wearablesPiwek, Ellis, Andrews, Joinson (2016) PLOS Medicine: 13 (2): e1001953
self-monitoring + feedback
continuousintelligentdetailed
instantpersonalised
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
high blood pressurehigh cholesterol levelphysical inactivityobesity
45%*
*NHS The Atlas of Risk (2014)
Those three devices accounted for
97%of all smartphone-enabledactivity trackers sold in 2013**cmo.com
Fitbit Jawbone UP Nike Fuelband
Battery life
Data access
User interface
Reliability SecurityData ownership
Build qualityFeedback
Fitbit Jawbone UP Nike Fuelband
distance per day (km)
days
squash
gymsquash
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
“Each new device should reduce the complexity of the system and increase the value of everything else in the ecosystem.”
Bill Buxton
*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
33 featuresperformance (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)
on off
Andrews, Ellis, Shaw, Piwek (2015) PLOS One 10 (10): e0139004
Smartphone research methods
PSYCHOLOGYSENSOR LAB
TMNetPropagateSystems
TM
Project in preparation PhD student co-supervision
Digital footprints for behavioural profiling
PSYCHOLOGYSENSOR LAB
TMNetPropagateSystems
TM
Project in preparation Awaiting grant application outcomes
Sociometric wearables for research
PSYCHOLOGYSENSOR LAB
TMNetPropagateSystems
TM
“(…) 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
Prof Adam Joinson | BathDr David Ellis | LancasterDr Phoebe Moore | MiddlesexDr Sally Andrews | Nottingham TrentProf Alan Tapp | UWE Dr Fiona Spotswood | UWE