Mentors: Suresh Krishna <suresh.krishna@mcgill.ca> and Oren Gurevitch <oren.gurevitch@mcgill.ca>
Skill level: Intermediate/Advanced
Required skills: Fluency with Android/iOS development (with framework of choice, preferably cross-platform). Basic signal processing familiarity preferred
Time commitment: Full time (350 hours)
Forum for discussion
About: While there are several commercial, closed-source apps to interface with breathing and heart-rate sensors (like SniffLogic and the Polar H10), as well as open-source software to interface with each of them separately, there is an acute need for open-source software to record from both sensors simultaneously and provide a large battery of metrics and algorithms operating on the two time-series.
Aims: The project will develop the first version of an app that uses Bluetooth and/or USB to connect with heart-rate and respiration sensors, calculate metrics of synchronization and variability based on these measurements and implement a biofeedback protocol to control this variability. This will allow the study of autonomic nervous function, and will allow biofeedback protocols for mood and health intervention to be implemented via live tracking of breathing and heart-rate. Future work can interface with consumer EEG devices like the Muse.
Websites: m2b3.com/BreathState
Tech keywords: App development, biofeedback, mood intervention, health ML/AI
Hello Everyone,
I was going through the INCF GSOC project lists and saw this project BreathState, an app for breathing and heart-rate synchronization. I did my research about the project and I am very much interested in building the app.
I already have experience in building apps in flutter and currently am working on a similar project related to measuring ECG signals of the heart using a sensor and calculating the various metrics using time series analysis like LSTM and random forest.
About myself, I am michael lewis, a pre-final student pursuing computer science. I have worked on many flutter projects and ML projects as well.
I am very much interested in this project and would like to know about how to proceed on this project and also had a few doubts regarding the usage of AI/ML and is the scaffold of the app already made.
Yours Sincerely,
Michael Lewis
Hello Everyone,
I hope you’re doing well. My name is Siddarth and I study Computer Science at USC. I’m very excited about the BreathState project and wanted to reach out to express my strong interest and share why I believe I’m a great fit.
I have experience developing and launching cross-platform mobile applications using Swift, Flutter, and React Native. Most recently, I built and published an iOS app called LiveTunez, which helps users discover concerts and create Spotify playlists from setlists. I also currently lead engineering efforts for a startup, where I’m building a React Native app focused on helping the visually impaired, while managing a small team and overseeing the architecture and deployment process.
In addition, I have worked on research projects with Professors involving signal processing and real-time data visualization, and I’m excited about applying these skills in the health tech space, especially in an open-source context that can benefit broader research and well-being. The opportunity to contribute to a platform that supports biofeedback, mood regulation, and live synchronization of physiological data aligns perfectly with my interests in impactful software and applied AI.
I’d love to hear more about the direction you’re envisioning for the project and any suggestions for what I can explore to strengthen my GSoC proposal. I’m eager to dive in.
Thank you for your time and consideration. I look forward to connecting!
Best,
Siddarth
1 Like
Hello @suresh.krishna and Oren,
I’m Anushka Sharma, an engineering student with a background in Python and JavaScript, and I’m highly interested in working on the BreathState project for GSoC 2025. I love the idea of combining mobile app development with biofeedback for mood and health intervention.
I noticed the project site m2b3.com/BreathState seems to be down, and I wanted to check if there’s a repo, design doc, or any material I can start exploring. I’d love to contribute and begin preparing a strong proposal with your guidance.
Thank you so much and looking forward to hearing from you!
Best regards,
Anushka Sharma
This is the correct link - BreathState
Hello mentors,
I’m very interested in contributing to the BreathState project via Google Summer of Code 2025. As part of getting familiar with the HNN-Core codebase and demonstrating my seriousness, I’ve submitted a Pull Request with meaningful improvements to docstrings in the visualization module, after thoroughly exploring the structure and contributing guidelines.
Here’s the PR link for reference: Enhance docstrings across visualization module for improved clarity and consistency by AnuzkaSharma · Pull Request #1021 · jonescompneurolab/hnn-core · GitHub
Looking forward to feedback, and excited to dive deeper into BreathState!
Best,
Anushka
Hello @suresh.krishna , Oren Gurevitvh,
I’ve gone through the BreathState project idea and the current GitHub repo. From what I understand, it’s still in the early phase and primarily has a README outlining the goal.
Since the current repo is still in the early stages, I’d like to begin building a basic prototype using ReactJS to explore:
- UI layout for real-time heart-rate & breathing data
- Initial Bluetooth connectivity (browser-supported devices)
- A flexible structure that can later be adapted to React Native or other frameworks
I fully understand the goal is to build a cross-platform mobile/desktop app, and I’m happy to evolve the prototype into a full app using React Native or any framework you prefer, once the basic logic is validated.
Would this be a good starting point?
Looking forward to your feedback!
Best regards,
Anushka
1 Like
yes, that is fine. The more detail you provide, the stronger the proposal will be.
Your proposal should indicate in detail what you will do, how you will do it, why you are the right person to do it (given your background, skillset etc) and that you will be able to do it (feasibility).
Please use the gsoc incf template. under recommendations here - Google Summer of Code | INCF
Please see the updates on the Github page
Thanks for the prompt reply @suresh.krishna
I have a few things that I wanted to clarify a few implementation details. Since I’ll be working on the app from my laptop without access to real sensors, I plan to:
Simulate Sensor Data: Use mathematical models or pre-recorded datasets to generate heart rate & breathing signals. Would you have any sample datasets or preferred methods for this?
Develop a Mock Bluetooth/USB Connection: Implement a placeholder module that mimics data streaming from real sensors, ensuring that actual integration is seamless later.
Ensure Easy Sensor Integration: Structure the code so future contributors can easily connect real sensors when available.
Does this approach align with the project’s goals? Would you suggest any specific datasets or frameworks for simulation?
Looking forward to your guidance!
yes, these are fine. we dont have any datasets in mind for now. you could also consider looking into what you would do with the heart-rate and breathing signals, look into heart-rate variability biofeedback protocols etc. good luck.
i suggest you use the template to actually create the proposal and then i can give you comments that you can use to develop it further before submission.
Hi Suresh and Oren,
I’m Himaneesh Mishra, a Master’s student in Cybersecurity at Northeastern University with a background in Python, C++, and Go. I’m very interested in contributing to BreathState for GSoC 2025 and am currently drafting my proposal using the INCF template.
Given my current setup, I plan to focus on building a PC-based MVP of the app using Python, with a modular architecture that supports future sensor integration and cross-platform expansion. To begin, I’ll:
*Simulate sensor data using mathematical models or available datasets.
*Implement a mock Bluetooth/USB module that mimics real-time data streaming.
*Design the app architecture to make adding real sensors straightforward later.
I saw in earlier responses that this direction seems aligned with the project’s goals, but I wanted to quickly confirm:
- Are there any existing data sources you’d recommend for simulating HRV/breathing signals?
- Would a structured PC-first approach that prioritizes clean modularity and future mobile extension be a good fit for the project?
Thanks again for the helpful thread responses and for your time — looking forward to your feedback so I can finalize my proposal.
Best regards,
Himaneesh Mishra
BreathState Prototype - HRV Tracker Update
Progress on the HRV tracking prototype is coming along well. The system currently simulates real-time HRV data, visualizes it, and computes coherence. The next phase involves integrating real sensor data and refining biofeedback calculations.
Attached is a preview of the chart in action. Any feedback or suggestions are welcome.
GitHub Repository:GitHub - AnuzkaSharma/BreathState_prototype
hey mentors… @suresh.krishna , Oren Gurevitch
I was planning to add the breathing visualization feature, where users can follow a guided breathing pattern along with the HRV tracking. The code runs successfully in VS Code, and the development server compiles without errors. But when I open the React app in the browser, the screen is completely blank. There are no visible errors in the console, but nothing is rendering. I’m not sure what’s causing this—could you help me figure it out?
Dear mentors,
I hope you’re doing well. I’m Mrunmayee, a second-year Electronics and Communication Engineering student at IIIT Nagpur, excited to contribute to the BreathState project for GSoC 2025.
Skills & Relevant Experience:
Android Development: Experience with cross-platform frameworks and integrating hardware via Bluetooth/USB.
Embedded Systems & IoT: Worked with Arduino, ESP32, and biometric sensors for real-time data processing.
Signal Processing: Being an ECE student, subjects like signal processing and MATLAB have been a part of our coursework which I have been interested in from the very beginning.
AI/ML: Being an AIML beginner, I have started to work my way up to making projects using Python, OpenCV, TensorFlow/PyTorch, CNN.
I’m passionate about health-focused AI and real-time biofeedback systems. The challenge of developing an open-source platform for heart-rate and breathing synchronization excites me, and I’d love to contribute my development + hardware integration skills to this project. I’ll be submitting my proposal soon and would appreciate any guidance on next steps. Looking forward to your feedback!
Best regards,
Mrunmayee
