System and method for scalable ECG analysis

By controlling the working nodes through the master node in the cloud computing environment and combining GPU and CPU to execute ECG analysis applications, the problem of insufficient computing resources in the ECG data processing system is solved, efficient ECG data processing and real-time monitoring are achieved, false alarms are reduced, and the simultaneous processing capacity of the number of patients is expanded.

CN120751978AInactive Publication Date: 2025-10-03BARDY DIAGNOSTICS INC
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Patent Information

Application Number
CN202480014535.6
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Priority Date
2023-01-30
Filing Date
2024-01-22
Publication Date
2025-10-03
Estimated Expiration
Not applicable · inactive patent

AI Technical Summary

Technical Problem

Existing ECG data processing systems lack computing resources when faced with large amounts of patient monitoring data, leading to diagnostic delays and false alarms. In particular, they are unable to capture incidental cardiac events in real time during dynamic monitoring, and the predefined frequency transmission is not flexible enough.

Method used

The master node in the cloud computing environment controls the startup and shutdown of the working nodes, utilizes the available computing resources, combines GPU and CPU to execute ECG analysis applications, dynamically adjusts the data transmission frequency and alarm generation, and realizes the effective utilization of computing resources and efficient processing of monitoring data.

Benefits of technology

It improves the efficiency of ECG data processing, expands the number of patients processed simultaneously, reduces diagnostic delays, enhances the real-time monitoring capabilities of cardiac conditions, and reduces the occurrence of false alarms.

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Abstract

Effective utilization is provided in a cloud computing environment in which a master plane executing on a master node controls startup and shutdown of working nodes in which a working node that outputs necessary for operation of other working nodes is started prior to the working node that requires that output. By specifying available computing resources to earlier launched working nodes, these working nodes can process a larger amount of monitoring data. Once the outputs of these working nodes are ready, available resources will be reallocated to working nodes that use earlier launched working node outputs. Additional control of heart monitoring may be provided by communicating with the monitor to increase the rate at which the monitor transmits the collected data and suspend alarm generation based on the monitored data if such alarms may be inaccurate.
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