# Smart Cuff: Multi-Parameter Hemodynamic Monitoring via a Single Convenient Device

> **NIH NIH R01** · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · 2024 · $653,622

## Abstract

PROJECT SUMMARY/ABSTRACT
Multi-parameter hemodynamic monitoring is needed to manage surgical and intensive care patients.
Monitoring blood pressure (BP), cardiac output (CO), and left ventricular ejection fraction (EF), in
particular, permits detection of frequent hypotension and hemodynamic instability, diagnosis of the
cause for selecting appropriate therapy, and titration of interventions (e.g., goal-directed therapy).
However, measurement of these three hemodynamic variables currently requires multiple devices
that are invasive, manual, or specialized. While the oscillometric arm cuff device is non-invasive,
automated, and standard, it only estimates BP from the measured cuff pressure waveform via a
population average algorithm that does not maintain accuracy over the clinical range. The overall
goal of this project is to extend the ubiquitous arm cuff device for accurate and convenient multi-
parameter hemodynamic monitoring via smart algorithms. The specific aims are: (1) to build an arm
cuff device for recording cuff pressure waveforms; (2) to simultaneously acquire patient data with this
and reference devices for algorithm training; (3) to develop and incorporate algorithms for accurately
computing BP, CO, and EF from the cuff pressure waveform based on the training data; and (4) to
validate the real-time Smart Cuff against reliable reference measurements in patients. The device will
be developed to control the cuff pressure and incorporate custom algorithms. The cuff pressure
waveform via the device and reference BP, CO, and EF via arterial and pulmonary artery catheters
and echocardiography will be recorded before and after clinical interventions in many surgical and
intensive care patients. These training data will be analyzed to refine or adapt previous physiologic
algorithms and to investigate potentially superior machine learning algorithms for best estimation of
the three hemodynamic variables. The final algorithms will be implemented for a real-time device,
and the integrated system will be tested against the same reference measurements during clinical
interventions but from new patients. Achievement of the specific aims will be followed by a
translational project to bring the Smart Cuff to patient care and a research project to extend the
device capabilities including addition of automated clinical decision support. Ultimately, these efforts
may help in improving patient outcomes and reducing healthcare costs in the near-term.

## Key facts

- **NIH application ID:** 10806944
- **Project number:** 5R01HL163691-02
- **Recipient organization:** UNIVERSITY OF PITTSBURGH AT PITTSBURGH
- **Principal Investigator:** RAMAKRISHNA MUKKAMALA
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $653,622
- **Award type:** 5
- **Project period:** 2023-03-10 → 2027-01-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10806944

## Citation

> US National Institutes of Health, RePORTER application 10806944, Smart Cuff: Multi-Parameter Hemodynamic Monitoring via a Single Convenient Device (5R01HL163691-02). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10806944. Licensed CC0.

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