Research Project

BORACLE – The Oracle for Your Body

Research Team

Lead Researchers:

Nhut Ho, Mechanical Engineering
Xunfei Jiang, Computer Science

Collaborators:

Mr. Trung Dung, Industry
Peter Washington, University of California, San Francisco
Trang Le Hong, Ho Chi Minh City University of Technology

Student Team:

Toan Pham, MS, Computer Science (NCSU)
Brandon Ismalej, BS, Computer Science
Abhinav Neelam, MS, Comp Science
Chongye Wang, MS, Computer Science
Leena Shah, BS, Comp Science
Ryan Franco, BS, Comp Science
Saurabh Gaglani, MS, Computer Engineering
Hemanth Vijay Reddy Karri, BS, Computer Engineering
Zachary Frappier, BS, Comp Science
Kyle Laguilles, BS, Comp Science
Richard Phan, BS, Comp Science
Carlos Figueroa, MS, Math
Arian Partovi, BS, Comp Science

Alumni Team:

Spencer J.H. Yang, MS Data Analytics at Oregon State
Patrick Prayoonpruk, Maxwell Kozlov, Ridham Patel, Mishek Sambahangphe (Comp Science 2024-2025 Senior Design Team)
Jose Villalobos, Alana Murry, Joshua Itchon, Amy Cardenas (Comp Science 2024-2025 Senior Design Team)*
Bihn Nguyen, Tong Luong, Anh Nguyen (Ho Chi Minh City University of Technology)
Bhumil Kukadiya, Pranati Jamalpuri, Abhinav Neelam (MS Comp Sci)
Matthew Smith (2024 ARCS Fellow), MS Comp Sci
Stephen Reilly, David Antonio Pedroza, Miles Kaddoura (BS Comp Sci)
Neha Ananthavaram, MS Comp Sci
Benjamin Tran, Foothill High School
Helena Hill, B.S. in Public Health
Shanlin Qian, B.S. in Electrical Engineering at UCSD
Himanshu Kumar, M.S. in Software Engineering
Manpreet Dhindsa, M.S. in Computer Science
Martin Ha, Taguhi Yenokyan (B.S. in Computer Science)
Christopher Pishaki, Paige Watanabe, Arfan Myint, Joseph Held (Computer Science 2023-2024 Senior Design Team)
Jacob Solorzano, B.S. in Psychobiology at UCLA
Justin Ho*, B.S in Business Administration
Xinyi Wang, B.A. in Arts
Anthony Bernal, Georgina Argueta, Diego Martinez (B.S. in Public Health)
Daniel Carter, B.A. in Economics
Junhe Chen, B.S in Computer Science
Mayur Rahangdale, Mohammad Shaik, Subhobrata Chakraborty (M.S. in Computer Science)
Arpon Dhar, BS Comp Science
Reshma Sheikh, BS Comp Science
Zackary McLaughlin, BS Comp Science
Guanyu Hou, BS Comp Science

Funding

Funding Organization:
Funding Program: CSUN Campus Funding Initiative

SYNOPSIS

Use benefits of wearable technology to advance healthcare.
Decouple sensor data from smart wearables for faster innovation.
Boracle Platform shares standardized wearable data to 3rd parties.
Boracle Marketplace pairs users to wearable devices.
Intelligent Algorithms detect healthcare conditions using ML models.

Abstract

Wearable devices and body sensor technology have evolved rapidly in the past years. While various types of devices collect different types of data, these data are currently only available to the device manufacturers’ internal team of developers. If the device’s manufacturers could make their devices’ body vital data available to 3rd party developers, significantly more health condition prognostics can be derived from trustworthy and intelligent algorithmic analysis. The decoupling of body sensor devices and intelligent algorithmic analysis of body vital data will accelerate independent and innovative growth in each of the areas. In this research, we will conduct comprehensive market research of commercial wearable devices, the APIs, the different collected data, and their digital health applications. We propose to build a platform, Boracle, that will collect data from any wearable devices, integrate the data and use big data technologies for intelligent analysis, and provide supporting services for both individual users and help app developers to create health condition prognostics. Borable will facilitate the intereoperability between applications and wearable body sensor devices and help end-users to improve their medical IQ/EQ and democratize accessibility to medical prognostics.

Motivation/Research Problem

Noninvasive, mass-market, affordable, wearable, body sensor technology will continue its rapid evolution with more capabilities to deliver richer body vital data. If the body vital data from these wearable devices is made available to 3rd party developers, more health condition prognostics can be derived from trustworthy and intelligent algorithmic analysis. The decoupling of body sensor devices and intelligent algorithmic analysis of body vital data will accelerate independent and innovative growth in each of the areas. Data privacy has been a major concern for health monitoring. It is critical that the individual consumer has complete rights to his/her personal health dataset and in total controls of what digital health application and/or organization can have access to this data.

Image collage of flow diagrams and charts

Research Objectives

The objective of this project is to create a centralized data platform, Boracle, that communicates with wearable devices and collects authorized data shared by users, then processes and stores the data securely, and provides services and user authorized data access to 3rd party digital health applications.

In this project, we will develop a prototype platform that:

receives data from various wearable body sensor devices,
processes and stores the data securely
makes data available to developers in a safe and secure way to build new & innovative digital health applications
enable digital health applications to access the individual data in a safe and secure way once proper access control is granted by the individual consumer
data safety and privacy centers around the individual consumer’s right and control of his / her own data.

Research Methods

We will create an open platform where 2 distinct areas of expertise can collaborate:

(1) body sensor devices extracting body vital data, and

(2) intelligent algorithmic analysis of body vital data delivering actionable health conditions
prognostic.

By decoupling these 2 areas of expertise, we will spur independent, innovative and faster growth in each of the areas. Examples of body vital data (aka biomarkers) are: heart rate & rhythm, blood pressure, ECG, body temperature, spO2, heart & lung sounds, glucose level, etc.

Research Results and Deliverables (Publications, Presentations, and other Products), Current/Anticipated

A standardized method to interface with many kinds of wearable devices to access the captured body vital data
A central platform system, Boracle platform, that stores data collected from wearable body sensor devices, share data with app developers, and provides data analysis services for users
A number of digital health applications that receive data from the Boracle platform, process data for data analysis, and deliver innovative health condition prognostics
Conference and Journal papers in the areas of biomedical and intelligent healthcare

[1] C. A. Dimalanta, M. Smith, K. Bonakdar, X. F. Jiang, N. Ho, and T. Dung, “Poster – Boracle: An Open Data Platform For Health Condition Prognostics” in 2024 IEEE/ACM Conference on Connected Health: Applications, Systems and Engineering Technologies (CHASE), Wilmington, DE, USA, 2024 pp. 200-201. doi: 10.1109/CHASE60773.2024.00038
[2] Matthew Smith, Nhut Ho, Xunfei Jiang, Trung Dung, “The Boracle Project: The Oracle for Your Body”. Democratize Accessibility to Human Body Information: Opportunities and Challenges Workshop in Hawaii International Conference on System Sciences 2024 (HICSS-57). Jan 3, 2024. (Poster Presentation)
[3] Jittapatana Prayoonpruk, Maxwell Kozlov, Brandon Ismalej, Abhinav Neelam, Xunfei Jiang, Nhut Ho. “Stress Detection Through Sleep-Based Physiological Signals: An Integrated Semi-Supervised and Supervised Learning Approach”. IEEE Annual Computing and Communication Workshop and Conference (IEEE CCWC 2026), Las Vegas, Nevada, January 5–7, 2026.
[4] Abhinav Neelam, Xunfei Jiang and Nhut Ho. “A Self-Attention Enhanced Deep Learning Framework for Fatigue Prediction”. IEEE Annual Computing and Communication Workshop and Conference (IEEE CCWC 2026), Las Vegas, Nevada, January 5–7, 2026.
[5] Neha Ananthavaram, Xunfei Jiang, Nhut Ho. “Sliding Window based Physical Activity Classification using Smart Wearable Data”. 2025 IEEE International Conference on Future Machine Learning and Data Science (FMLDS2025), 02-05 November 2025, Los Angeles, USA. (In press)

Commercialization Opportunities

Application: Wearable data pipeline with mobile app interface.
Key Values: Easily access and share health data created by wearable tech.
Potential Users: Anyone with a smart wearable device!

Research Timeline

Start Date:09/21/2022