emotion sense: from design to deployment
DESCRIPTION
Research talk @ St. Andrew's University, October 2014TRANSCRIPT
Emotion Sense:From Design to Deployment@neal_lathia – October 2014
Background
Collecting Sensor Data
First Trial
Re-design & launch
Market & react
Analyse data
Apply to new domains
Background
Collecting Sensor Data
First Trial
Re-design & launch
Market & react
Analyse data
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.
Lathia et. al. “Contextual Dissonance: Design Bias in Sensor Based Experience Sampling Methods.” Ubicomp 2013.
Ongoing work.
Background
Collecting Sensor Data
First Trial
Re-design & launch
Market & react
Analyse data
Lathia et. al. “Smartphones for Large-Scale Behaviour Change Interventions.” IEEE Pervasive.
Apply to new domains
● …[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
Background
Collecting Sensor Data
First Trial
Re-design & launch
Market & react
Analyse data
Apply to new domains
Lathia et. al. “Open-Source Smartphone Libraries for Computational Social Science.” MCSS 2013.
“... 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
● 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
Android ESSensorManager
Background
Collecting Sensor Data
First Trial
Re-design & launch
Market & react
Analyse data
Apply to new domains
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?
We built a system that includes: sensor data collection, ESM interfaces, etc., and remote reconfiguration.
22 users; 1-month; questions about mood & current context (location, sociability); background sensing from many sensors; triggers remotely reconfigured weekly.
Dissonance; a tension or clash resulting from the combination of two disharmonious elements
Dissonance; between using sensor states to trigger ESM surveys while using sensor data to quantify context and behaviour.
Background
Collecting Sensor Data
First Trial
Re-design & launch
Market & react
Analyse data
Apply to new domains
Background
Collecting Sensor Data
First Trial
Re-design & launch
Market & react
Analyse data
Apply to new domains Ongoing work.
We have:State/trait surveysContext labelsSensor data
signals of behaviour
Background
Collecting Sensor Data
First Trial
Re-design & launch
Market & react
Analyse data
Apply to new domains Ongoing work.
Generalise sensor-enhanced experience sampling tool. Currently in alpha testing.
Emotion Sense:From Design to Deployment@neal_lathia – October 2014