VitalWave: An End-to-End Open-Source High-Frequency Wearable Device and Data Collection Platform

Lauren Elizabeth Lederer, Ali R Roghanizad, Ritvik Janamsetty, Luke Redmore, Seijung Kim, Krish Bansal, Amy Liu, Benjamin Asomani, Lauren Baur, Cindy Wang, Amy Duan, Jamee Krzanich, Naomi Patel, Arthur Zhao, Jessilyn Dunn

Confirmation: I have read and agree with the IEEE BSN 2025 conference submission's policy on behalf of myself and my co-authors.

Keywords: digital biomarkers, wearable device, mobile app, high-frequency sensors, cloud platform

TL;DR: We present an initial prototype for VitalWave, a novel open-source end-to-end platform consisting of a wearable device and corresponding mobile/web application capable of capturing and visualizing high-frequency sensor data.

Abstract: We present an initial prototype for VitalWave, a novel open-source end-to-end platform consisting of a wearable device and corresponding mobile/web application capable of capturing and visualizing high-frequency sensor data. The platform includes cloud-based data processing and a web interface for data visualization and analysis. This system was designed to overcome the limitations of existing commercial wearables, which often only offer low-frequency, pre-processed data and limited raw data access. Our device samples at up to 100Hz from multiple biosensors and includes real-time mobile streaming, secure cloud storage, and integrated web-based visualization tools. Ultimately, this work serves as a foundational platform for the development of digital biomarkers and machine learning models in health applications.

Track: 2. Sensors and systems for digital health, wellness, and athletics

NominateReviewer: Lauren Lederer - [e-mail]

Submission Number: 110