US 2026/0207083 A1 · PHYSIOLOGICAL MONITORING APPARATUS AND METHODS

Abstract

A real-time, AI-driven respiratory monitoring system is disclosed comprising a wearable diaphragm sensor configured to detect mechanomyographic signals, optionally with additional sensors including a photoplethysmographic (PPG) sensor, carbon dioxide (CO2) sensor, and temperature sensor. A processor is configured to receive synchronized multi-sensor signals and execute machine learning algorithms trained to derive respiratory parameters such as respiratory rate, tidal volume, I:E ratio, minute volume, and rapid shallow breathing index. The system may classify respiratory abnormalities, generate adaptive alerts, and display trends through a graphical interface. Patient posture and symptom input may adjust model inference and alert thresholds. The system may operate in therapy-assist and post-therapy monitoring modes, support closed-loop ventilator control, and transmit time-stamped respiratory data and alerts to remote caregiver dashboards. A population-trained model may adapt alerts to patient-specific baselines and detect conditions including COPD exacerbation, neuromuscular decline, respiratory distress, post-surgical complications, and dialysis-related impairment.

Claims26

Dependent claims

A respiratory monitoring system comprising:

a wearable sensor configured to be positioned over a patient's diaphragm and comprising:
a flexible capacitive diaphragm sensor configured to detect mechanomyographic (MMG) data in three spatial dimensions;
and
an accelerometer configured to detect patient motion;
a processor configured to receive signals comprising time-varying signals from the diaphragm sensor and accelerometer;
a machine learning module stored in memory and configured to be executed by the processor, the machine learning module trained to derive, based on the received signals, one or more respiratory parameters selected from the group consisting of respiratory rate, inspiratory and expiratory phases, inspiratory-expiratory ratio, tidal volume, minute volume, respiratory mechanics, rapid shallow breathing index, cough detection, and dyspnea detection;
a GUI configured to display at least one of said respiratory parameters in real time;
and
an alert module configured to generate a notification when one or more of the respiratory parameters deviates from a predefined threshold.

6 more elements

Dependencies are inferred from the claim text.

Physiological monitoring apparatus and methods

Life of this patent

Physiological monitoring apparatus and methods

Life of this patent

Abstract

Claims26