The aim of our project is modulating heart rate interoception through music feedback to check if getting in tune with your heart has an impact on your performance in cognitive tasks and emotional state.
The hypothesis for the current experiment is that better cardiac interoception might be positively correlated with task performance and emotion regulation, hence our next step would be training cardiac interoception through music based biofeedback.
The groundbreaking part of our project is that we are testing a new, easily accessible biofeedback - where you get in tune with your heart while listening to music, and the only device you need is your phone and smartwatch. In future we hope that our music based HR feedback allows people to manage their emotions in distress and also help them focus better.
Establish correlations between cardiac interoceptions and cognitive task performance and emotional health
Design a musical biofeedback to train people to get in tune with their heart and improve their daily lives
Good first issues
Heart rate to music
Develop audio based on resting HR
Convert HR signal to audio stream
Tools: Python
Data: Example HR data provided, participants own data (if wearing Fitbit)
Extension to BrainHack:
Enable real-time streaming and processing of HR data to generate audio
Tools: Fitbit software developer kit (API), web app integration
Experimental Designers
Data collection & analysis
Coding (python or other)
App or Game Developers
Music expertise
Onboarding documentation
No response
What will participants learn?
Extracting, analysing and converting biological signals to audio feedback
Learning experiment designing for biofeedback
Linking physiological data with cognitive performance
Data to use
No response
Number of collaborators
more
Credit to collaborators
Project contributors will be listed in project ReadME and their contributions to the project will be mentioned wherever the project is discussed.
Image
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Type
coding_methods, method_development, pipeline_development, other
Development status
0_concept_no_content
Topic
hypothesis_testing, physiology
Tools
Jupyter
Programming language
Matlab, Python, R, html_css, javascript
Modalities
behavioral, ECG, other
Git skills
0_no_git_skills
Anything else?
NA
Things to do after the project is submitted and ready to review.
[X] Add a comment below the main post of your issue saying: Hi @brainhackorg/project-monitors my project is ready!
Title
Tune into your heart
Leaders
Rochelle De Silva: rochelled@student.unimelb.edu.au Shivam Puri: sppuri@student.unimelb.edu.au
Collaborators
Dr. Pip Karoly Dr. Jodie Naim-Feil Feil Dr. Rachel Stirling
Brainhack Global 2024 Event
Brainhack Aus
Project Description
The aim of our project is modulating heart rate interoception through music feedback to check if getting in tune with your heart has an impact on your performance in cognitive tasks and emotional state.
The hypothesis for the current experiment is that better cardiac interoception might be positively correlated with task performance and emotion regulation, hence our next step would be training cardiac interoception through music based biofeedback.
The groundbreaking part of our project is that we are testing a new, easily accessible biofeedback - where you get in tune with your heart while listening to music, and the only device you need is your phone and smartwatch. In future we hope that our music based HR feedback allows people to manage their emotions in distress and also help them focus better.
if you are interested, please fill out this Expression of Interest form - https://forms.gle/SmtpUonp23ys3HhH7
For more information, please do visit our GitHub Repository - https://github.com/shivam-sunita-puri/TIYA/tree/main
Link to project repository/sources
https://github.com/shivam-sunita-puri/TIYA
Goals for Brainhack Global
Establish correlations between cardiac interoceptions and cognitive task performance and emotional health Design a musical biofeedback to train people to get in tune with their heart and improve their daily lives
Good first issues
Heart rate to music Develop audio based on resting HR Convert HR signal to audio stream Tools: Python Data: Example HR data provided, participants own data (if wearing Fitbit)
Cognitive tasks Implement SART, Flanker’s, Posner’s Cueing and subjective scale Tools: PsychoPy (Pavlovia)
Extension to BrainHack: Enable real-time streaming and processing of HR data to generate audio Tools: Fitbit software developer kit (API), web app integration
Communication channels
https://mattermost.brainhack.org/brainhack/channels/tiya
Skills
Experimental Designers Data collection & analysis Coding (python or other) App or Game Developers Music expertise
Onboarding documentation
No response
What will participants learn?
Extracting, analysing and converting biological signals to audio feedback Learning experiment designing for biofeedback Linking physiological data with cognitive performance
Data to use
No response
Number of collaborators
more
Credit to collaborators
Project contributors will be listed in project ReadME and their contributions to the project will be mentioned wherever the project is discussed.
Image
Leave this text if you don't have an image yet.
Type
coding_methods, method_development, pipeline_development, other
Development status
0_concept_no_content
Topic
hypothesis_testing, physiology
Tools
Jupyter
Programming language
Matlab, Python,
R
, html_css, javascriptModalities
behavioral, ECG, other
Git skills
0_no_git_skills
Anything else?
NA
Things to do after the project is submitted and ready to review.
Hi @brainhackorg/project-monitors my project is ready!