emotion sense: from design to deployment

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