End-To-End Prediction of Emotion From Heartbeat Data Collected by a Consumer Fitness Tracker
Automatic detection of emotion has the potential to revolutionize mental health and wellbeing. Recent work has been successful in predicting affect from unimodal electrocardiogram (ECG) data. However, to be immediately relevant for real-world applications, physiology-based emotion detection must make use of ubiquitous photoplethysmogram (PPG) data collected by affordable consumer fitness trackers. Additionally, applications of emotion detection in healthcare settings will require some measure of uncertainty over model predictions. We present here a Bayesian deep learning model for end-to-end classification of emotional valence, using only the unimodal heartbeat time series collected by a consumer fitness tracker (Garmin V\'ivosmart 3). We collected a new dataset for this task, and report a peak F1 score of 0.7. This demonstrates a practical relevance of physiology-based emotion detection `in the wild' today.
NurtureToken New!

Token crowdsale for this paper ends in

Buy Nurture Tokens

Authors

Are you an author of this paper? Check the Twitter handle we have for you is correct.

Ross Harper (edit)
Joshua Southern (edit)
Ask The Authors

Ask the authors of this paper a question or leave a comment.

Read it. Rate it.
#1. Which part of the paper did you read?

#2. The paper contains new data or analyses that is openly accessible?
#3. The conclusion is supported by the data and analyses?
#4. The conclusion is of scientific interest?
#5. The result is likely to lead to future research?

Github
User:
None (add)
Repo:
None (add)
Stargazers:
0
Forks:
0
Open Issues:
0
Network:
0
Subscribers:
0
Language:
None
Youtube
Link:
None (add)
Views:
0
Likes:
0
Dislikes:
0
Favorites:
0
Comments:
0
Other
Sample Sizes (N=):
Inserted:
Words Total:
Words Unique:
Source:
Abstract:
None
07/17/19 06:04PM
5,307
2,087
Tweets
arxiv_cshc: End-To-End Prediction of Emotion From Heartbeat Data Collected by a Consumer Fitness Tracker https://t.co/wpfstPnE2A
Memoirs: End-To-End Prediction of Emotion From Heartbeat Data Collected by a Consumer Fitness Tracker. https://t.co/RWy9pjzZbl
arxiv_cshc: End-To-End Prediction of Emotion From Heartbeat Data Collected by a Consumer Fitness Tracker https://t.co/wpfstP63b2
arxivml: "End-To-End Prediction of Emotion From Heartbeat Data Collected by a Consumer Fitness Tracker", Ross Harper, Joshua… https://t.co/f45k03nw4Y
Images
Related