Nociception Detection via Arterial Waveform CUSUM Analysis
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Solution Overview
Problem
Current methods for detecting nociception in unconscious patients during surgery are inadequate, as they rely on verbal communication or subjective pain thresholds, leading to potential under or over-administration of analgesics, which can result in post-surgical pain or adverse side effects.
Innovation Solution
A hemodynamic monitoring system that analyzes arterial pressure waveforms using a cumulative sum algorithm and machine learning classification to detect nociception by extracting relevant signal measures and calculating a nociception score, providing a probability of nociception events and triggering alerts for medical personnel.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If verbal communication or subjective pain thresholds are used to detect nociception, then the detection method is simple, but the measurement precision is poor leading to under or over-administration of analgesics
Solution Approach 1:
The patent replaces subjective mechanical assessment methods (verbal communication, pain threshold evaluation) with automated electronic hemodynamic monitoring. The system uses arterial pressure waveform analysis with machine learning algorithms to objectively detect nociception, substituting human judgment with computational analysis of physiological signals.
Solution Approach 2:
The patent introduces an intermediary computational system that processes hemodynamic data between the physiological signal source and the clinical decision. The machine learning model acts as a mediator, translating complex arterial pressure waveform features into an interpretable nociception probability score that guides analgesic administration.
2Object-affected harmful factors
If analgesic administration is increased to prevent post-surgical pain, then the patient comfort is improved, but harmful side effects increase such as nausea, drowsiness, and impaired function
Solution Approach 1:
The patent implements a feedback-controlled analgesic administration system. The hemodynamic monitor continuously assesses nociception probability and provides real-time feedback to guide dosing decisions. This closed-loop approach allows dynamic adjustment of analgesic timing and dosage based on actual nociceptive response, preventing both under-treatment and over-treatment.
Solution Approach 2:
The patent enables preliminary detection of nociception events before they manifest as overt pain responses. By analyzing subtle hemodynamic changes that precede conscious pain perception, the system allows proactive analgesic intervention at optimal moments, improving pain prevention efficacy while minimizing required dosage.
3Object-generated harmful factors
If analgesic administration is decreased to minimize side effects, then harmful side effects are reduced, but the patient may awake from surgery with significant pain
Solution Approach 1:
The feedback mechanism continuously monitors nociception probability and adjusts analgesic dosing recommendations in real-time. This ensures the minimum effective dose is administered at critical moments, preventing pain while avoiding excessive dosing that would cause side effects.
Solution Approach 2:
The system replaces conservative empirical dosing protocols with data-driven, personalized analgesic recommendations based on individual hemodynamic responses. This objective measurement approach optimizes the balance between pain control and side effect prevention for each patient.
Data Source
AI summary
A method is disclosed for monitoring arterial pressure of a patient and identifying nociception of the patient. The method includes receiving, by a hemodynamic monitor, sensed hemodynamic data representative of an arterial pressure waveform of the patient. Waveform analysis is performed by the hemodynamic monitor of the sensed hemodynamic data to calculate a first signal measure and a second signal measure. Both the first and second signal measures are processed by the hemodynamic monitor through a cumulative sum (CUSUM) algorithm to acquire a first CUSUM output for the first signal measure and a second CUSUM output for the second signal measure. A nociception event of the patient is detected when a change in the first CUSUM output overlaps in time with a change in the second CUSUM output. A sensory signal is outputted to a user interface of the hemodynamic monitor to warn medical personnel of the nociception event.