Machine-Learned Nociception Index for Perioperative Analgesia
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Solution Overview
Problem
Current anesthesia practices lack reliable methods for objectively assessing nociception in anesthetized patients, leading to variability in opioid dosing and associated negative consequences such as delayed recovery, hemodynamic instability, and increased pain levels.
Innovation Solution
A device and method utilizing a processing unit to compute a nociception index from multiple physiological parameters, applying machine learning techniques, and provide closed-loop analgesic administration based on threshold comparisons and clinical concerns to ensure optimal perioperative pain management.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If surrogate measures (heart rate, blood pressure, tearing, pupillary response, sweating) are used to assess nociception, then monitoring is possible, but reliability is poor due to influence by other factors such as hypoxia, hypercarbia, hypo- or hyperthermia, and medications
Solution Approach 1:
The patent introduces an intermediary substance (nociceptive stimulus) that directly activates nociceptors, allowing objective measurement of nociception through electrophysiological signals rather than relying on unreliable surrogate measures. This intermediary approach isolates the nociceptive pathway from confounding factors like hypoxia, hypercarbia, and medications.
Solution Approach 2:
The patent replaces the mechanical/physiological surrogate measures (heart rate, blood pressure, tearing) with an electrophysiological measurement system that directly records nociceptive nerve signals. This substitution eliminates the indirect inference chain and provides direct, reliable measurement of nociception.
2Ease of operation
If opioid dosing is adjusted based on unreliable surrogate measures, then treatment attempts are made, but manufacturing precision (dosage control) deteriorates leading to large variability in opioid dosing
Solution Approach 1:
The patent implements a feedback mechanism where nociceptive stimulus intensity is systematically varied and the resulting electrophysiological response is measured. This feedback loop allows real-time adjustment of opioid dosing based on actual nociceptive response rather than unreliable surrogates, achieving precise dosage control.
Solution Approach 2:
The patent changes the measurement parameter from indirect physiological surrogates to direct electrophysiological signals from nociceptive nerves. This parameter change enables precise quantification of nociception and subsequent precise control of opioid dosing.
3Object-affected harmful factors
If excessive or insufficient opioid doses are administered, then pain management attempts are made, but harmful factors increase including delayed recovery of spontaneous ventilation, delayed return of consciousness, increased risk of arterial hypotension, and post-operative opioid-induced hyperalgesia
Solution Approach 1:
The patent applies preliminary action by systematically assessing nociceptive sensitivity before and during surgical procedures. This allows preemptive adjustment of opioid dosing to match actual nociceptive thresholds, preventing both excessive and insufficient dosing before harmful effects can occur.
Solution Approach 2:
The patent enables the patient's own nociceptive nervous system to serve as the measurement tool for assessing pain sensitivity. The patient's endogenous nociceptive responses provide self-diagnostic information about their pain threshold, allowing personalized opioid dosing without relying on external surrogates or predictions.
4Productivity
If closed-loop automated analgesic administration is implemented, then productivity and consistency improve, but device complexity increases
Solution Approach 1:
The patent implements self-service automation where the system uses the patient's own physiological responses (nociceptive electrophysiological signals) as the control input. This eliminates the need for complex external monitoring systems or manual assessment, reducing overall system complexity while maintaining automated efficiency.
Solution Approach 2:
The patent makes the electrophysiological measurement system multi-functional by using the same nociceptive nerve signals for both diagnostic assessment and therapeutic control. This universal approach eliminates the need for separate monitoring and control systems, reducing device complexity.
Data Source
AI summary
Method, device, system and associated processing logic for providing optimal perioperative nociception management to anesthetized patient, including monitoring a plurality of nociception-related physiological parameters of the patient using at least two non-invasive physiological sensors; combining the plurality of nociception-related physiological parameters into a nociception index value indicative of a level of nociception of the patient, by applying a machine learning algorithm on the plurality of nociception-related physiological parameters and/or features derived therefrom; comparing the nociception index value to a first threshold value indicative of an upper limit of nociceptive-anti-nociceptive balance (NANB) and to a second threshold value indicative of a lower limit of NANB; and providing a treatment or treatment recommendation based on the comparison and on a clinical concern.