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Empatica Health Monitoring Platform

Empatica Health Monitoring Platform

One platform, multiple applications

Components

EmbracePlus wearable
EmbraceMini wearable
New
Care software suite
eCOA
Digital biomarkers
Cloud API for Clinical Trials

Use Cases

Clinical Trials
Designed for the patient, enhanced for the scientist
Actigraphy
The new standard to measure sleep and physical activity
Contract Research Organizations
Enhanced value and effortless integrations for CROs
Parkinson's Monitoring
New
Improve patient outcomes with validated PKG measures
Parkinson’s & Movement Disorders
Digital endpoints for Parkinson's and movement disorders trials
Academic Research
Unlock the future of real-world research
Go to store
Publications
Scientific publications using our technology
Case Studies
Client success stories
Compliance
Global regulatory requirements
Blog
Thoughts and news
Digital resources library
Online and downloadable resources
Support center
Get support with our products
About us
People with purpose
Careers
Join the mission
Contact us
Talk to our team
EpiMonitor

Next-Gen Epilepsy Monitoring

Available in the US, UK, EU, AU, NZ and CA

Embrace2
Embrace2

Peace of Mind

No longer available for purchase

Contact Us
Research

E4 Bytes: Measuring emotional engagement during VR experiences

Empatica

Empatica

Jul 29, 2020• 2 min read

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Background

Emotions are crucial ingredients of meaningful and memorable tourism experiences. It is therefore essential for experience researchers to be able to accurately measure emotions while experiences are unfolding in time. Research methods borrowed from experimental psychology and psychophysiology are prime candidates for quantifying emotional engagement with great temporal precision. The present paper empirically evaluates the methodological feasibility and usefulness of ambulatory recordings of skin conductance (SC) responses during a tourism experience.

Methods

We recorded skin conductance (SC) with Empatica E4 wristbands in participants while they experienced a roller coaster ride with or without a Virtual Reality (VR) headset. As a roller coaster is a relatively adverse environment for physiological recordings, measurements contained substantial motion artifacts. We therefore developed and implemented a simple algorithm in Matlab (freely available upon request from the authors) that semi-automatically detects and removes motion artifacts from SCR measurements. Ride elements were identified that related to physical aspects (such as accelerations and braking), to events in the VR environment, and to the physical theming of the rollercoaster.

Results

SC response time series were meaningfully related to the different ride elements. SC responses did not significantly predict overall evaluations of the ride. We conclude that psychophysiological measurements are a new avenue for understanding how hospitality, tourism & leisure experiences dynamically develop over time.

References

Bastiaansen, M., Oosterholt, M., Mitas, O., Han, D., & Lub, X. (2020). . Journal of Hospitality & Tourism Research, 1096348020944436.

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