CORAL: A Modality Invariant Framework for Robust Vital Sign Rate Estimation Using Correloform Analysis
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
[2608.14973] CORAL: A Modality Invariant Framework for Robust Vital Sign Rate Estimation Using Correloform Analysis Skip to main content Search Submit Donate Log in Search arXiv Press Enter to search · Advanced search Electrical Engineering and Systems Science > Signal Processing arXiv:2608.14973 (eess) [Submitted on 15 Aug 2026] Title: CORAL: A Modality Invariant Framework for Robust Vital Sign Rate Estimation Using Correloform Analysis Authors: Jacob Trueb , Amey Kasbe , Aniruddh Srinivasan View a PDF of the paper titled CORAL: A Modality Invariant Framework for Robust Vital Sign Rate Estimation Using Correloform Analysis, by Jacob Trueb and 2 other authors View PDF Abstract: Heart rate and respiration rate are crucial vital signs. We present CORAL to address challenges in automating continuous vital sign monitoring 1) in-hospital across broader populations (age, disease states), 2) at-home in telehealth and wellbeing applications (noise, placement), and 3) across data modalities (ECG, PPG, SCG, BioZ, etc.). We re-introduce Short-Time Autocorrelation Functions (STACFs) to introduce the correloform - a highly interpretable 2D signal transformation for tracking periodicity over time - and define CORAL as a generic analytical framework for robust rate estimation of quasi-periodic signals. We rigorously benchmark CORAL to show ubiquitous application in biosignals via capabilities arising by mathematical construction rather than domain-specific engineering, including rate estimation, resilient noise handling, automatic channel selection, and signal quality indication. CORAL achieves excellent instantaneous noninvasive fetal HR agreement in FECGSYNDB (F1 = 0.999) and ADFECGDB (F1 = 1.000). With difficult NICU neonates, CORAL estimates RR from wearable BioZ at r = 0.858 against breath-interval RR from simultaneous wired Philips impedance. CORAL SCG HR on CEBS achieves r = 0.990 and in free-living activity r = 0.970 when compared against commercial ECG. Without QRS detection, CORAL's instantaneous HR agrees with Pan-Tompkins and NeuroKit2 detectors as closely as they agree with each other (MIMIC-IV ICU ECG r = 0.87 to each vs. 0.88 between them). CORAL's HR standard deviation correlates strongly with interval-based HRV SDNN, even from mechanical SCG (CEBS r = 0.733) and across an ICU ECG cohort (r = 0.768). Comments: main manuscript: 11 pages, 2 tables, 4 figures supplemental materials: 25 pages, 4 tabes, 31 figures Subjects: Signal Processing (eess.SP) ; Quantitative Methods (q-bio.QM) Cite as: arXiv:2608.14973 [eess.SP] (or arXiv:2608.14973v1 [eess.SP] for this version) https://doi.org/10.48550/arXiv.2608.14973 Focus to learn more arXiv-issued DOI via DataCite Submission history From: Jacob Trueb [ view email ] [v1] Sat, 15 Aug 2026 01:53:49 UTC (12,541 KB) Full-text links: Access Paper: View a PDF of the paper titled CORAL: A Modality Invariant Framework for Robust Vital Sign Rate Estimation Using Correloform Analysis, by Jacob Trueb and 2 other authors View PDF view license Current browse context: eess.SP < prev | next > new | recent | 2026-08 Change to browse by: eess q-bio q-bio.QM References & Citations NASA ADS Google Scholar Semantic Scholar export BibTeX citation Loading... BibTeX formatted citation × loading... Data provided by: Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer ( What is the Explorer? ) Connected Papers Toggle Connected Papers ( What is Connected Papers? ) Litmaps Toggle Litmaps ( What is Litmaps? ) scite.ai Toggle scite Smart Citations ( What are Smart Citations? ) Code, Data, Media Code, Data and Media Associated with this Article alphaXiv Toggle alphaXiv ( What is alphaXiv? ) Links to Code Toggle CatalyzeX Code Finder for Papers ( What is CatalyzeX? ) DagsHub Toggle DagsHub ( What is DagsHub? ) GotitPub Toggle Gotit.pub ( What is GotitPub? ) Huggingface Toggle Hugging Face ( What is Huggingface? ) ScienceCast Toggle ScienceCast ( What is ScienceCast? ) Demos Demos Replicate Toggle Replicate ( What is Replicate? ) Spaces Toggle Hugging Face Spaces ( What is Spaces? ) Spaces Toggle TXYZ.AI ( What is TXYZ.AI? ) Related Papers Recommenders and Search Tools Link to Influence Flower Influence Flower ( What are Influence Flowers? ) Core recommender toggle CORE Recommender ( What is CORE? ) Author Venue Institution Topic About arXivLabs arXivLabs: experimental projects with community collaborators arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs . Which authors of this paper are endorsers? | Disable MathJax ( What is MathJax? ) We gratefully acknowledge support from our major funders , member institutions , , and all contributors. About · Help · Contact · Subscribe · Copyright · Privacy · Accessibility · Operational Status (opens in new tab) Major funding support from
Related documents
- CORAL: A Modality Invariant Framework for Robust Vital Sign Rate Estimation Using Correloform Analysis#610933
- Zero declination and atmospheric pressure data as indicators of the timing of coral spawning#398041
- TinyCardioUNet: IMU-to-ECG Translation with Graph-Encoded Inter-Axis Dependencies and Tensor Decomposition-Based Parameter Reduction#1077251
- DiverReef: The global repository of divers' and snorkelers' behavior during tourism activities and their interactions with reef environments over 20 years#1019326
- Analysis of Vital Signs in Patients With COVID-19#858561
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive