Research talk @ St. Andrew's University, October 2014

1. Emotion Sense:
From Design to Deployment
@neal_lathia – October 2014

2. Apply to new domains
Analyse data
Market & react
Re-design & launch
First Trial
Collecting Sensor Data
Background

3. Analyse data
Market & react
Re-design & launch
First Trial
Collecting Sensor Data
Background
Ongoing work.
Lathia et. al. “Contextual
Dissonance: Design Bias in Sensor
Based Experience Sampling
Methods.” Ubicomp 2013.
Lathia et. al. “Smartphones for
Large-Scale Behaviour Change
Interventions.” IEEE Pervasive.
Apply to new domains
Lathia et. al. “Open-Source
Smartphone Libraries for
Computational Social Science.”
MCSS 2013.

4. Analyse data
Market & react
Re-design & launch
First Trial
Collecting Sensor Data
Background
Lathia et. al. “Smartphones for
Large-Scale Behaviour Change
Interventions.” IEEE Pervasive.
Apply to new domains

6. ● …[short term] to collect research data about moods
and behaviours as people experience them
● …[long term] to explore whether machine learning
approaches could infer people's subjective
responses/complex behaviours
● …[vision] to understand the extent that behavioural
support can be automated and personalised with
sensor data

7. Apply to new domains
Analyse data
Market & react
Re-design & launch
First Trial
Collecting Sensor Data
Background
Lathia et. al. “Open-Source
Smartphone Libraries for
Computational Social Science.”
MCSS 2013.

8. “... a number of challenges remain in
the development of sensor-based
applications [...] there is mixed API and
operating system (OS) support to
access the low-level sensors...”
“A Survey of Mobile Phone Sensing,” Lane et. al

10. Android ESSensorManager
● Everything as a “sensor”
● Simple API with two modes (get, subscribe);
sensor data in two lines of code
● API exposes battery issues, configuration to
programmer
● Student project-led evaluation
● https://github.com/xsenselabs

11. Apply to new domains
Analyse data
Market & react
Re-design & launch
First Trial
Collecting Sensor Data
Background
Lathia et. al. “Contextual
Dissonance: Design Bias in Sensor
Based Experience Sampling
Methods.” Ubicomp 2013.
How should we design the
relationship between interacting
and collecting 'labelled' data?

12. We built a system that
includes: sensor data
collection, ESM
interfaces, etc., and
remote reconfiguration.

13. 22 users; 1-month;
questions about mood
& current context
(location, sociability);
background sensing
from many sensors;
triggers remotely
reconfigured weekly.

15. Dissonance; a tension or clash resulting
from the combination of two
disharmonious elements

16. Dissonance; between using sensor
states to trigger ESM surveys while
using sensor data to quantify context
and behaviour.

18. Apply to new domains
Analyse data
Market & react
Re-design & launch
First Trial
Collecting Sensor Data
Background

30. Ongoing work. Apply to new domains
Analyse data
Market & react
Re-design & launch
First Trial
Collecting Sensor Data
Background

31. We have:
State/trait surveys
Context labels
Sensor data

32. signals of behaviour

34. Ongoing work. Apply to new domains
Analyse data
Market & react
Re-design & launch
First Trial
Collecting Sensor Data
Background

35. Generalise sensor-enhanced
experience
sampling tool. Currently
in alpha testing.

37. Emotion Sense:
From Design to Deployment
@neal_lathia – October 2014