EEG-Based Pain Monitoring Using Theta-Alpha Power Indicators
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Solution Overview
Problem
Current methods for assessing pain levels in subjects, especially non-verbal patients or those with modified consciousness, lack efficiency, reliability, and objectivity, leading to risks of overdosing or underdosing in pain management, as they rely on subjective self-reporting and fail to accurately measure conscious pain perception.
Innovation Solution
A computer-implemented method using EEG data from frontal and parietal electrodes to extract indicators of depth of state and level of pain, allowing for objective measurement and monitoring of modified consciousness and pain levels, enabling more accurate diagnosis and treatment planning.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual pain scales relying on self-reporting are used, then the measure reflects the patient's perceived pain, but the assessment lacks efficiency, reliability, precision and reproducibility
Solution Approach 1:
The patent replaces manual mechanical assessment methods (pain scales requiring clinician interpretation of patient responses) with an automated electronic system that uses EEG sensors to objectively measure pain levels. The system processes brain wave signals algorithmically to generate pain intensity scores, eliminating the need for manual scaling and interpretation while improving both precision and efficiency.
Solution Approach 2:
The system enables patients to be assessed without requiring their active participation or self-reporting capabilities. The EEG-based measurement automatically captures pain levels through physiological signals, allowing the assessment to serve itself without relying on the patient's ability to communicate or respond to pain scale questions.
2Reliability
If physiological pain response signals (nociception indexes) are used, then objective measurement is provided, but the indication of consciously perceived pain level is unreliable
Solution Approach 1:
The patent focuses on specific local characteristics of EEG signals (alpha and theta wave power spectra in particular frequency bands) rather than attempting to analyze all physiological responses. By concentrating on these specific local signal properties known to correlate with conscious perception, the system achieves reliable pain measurement without the complexity of monitoring multiple physiological systems.
Solution Approach 2:
The system transforms raw EEG signals into meaningful pain indicators by analyzing changes in specific parameters (power spectral density in alpha and theta bands). This parameter transformation converts complex physiological data into simplified, reliable pain intensity scores that directly reflect conscious perception without requiring complex multi-parameter analysis.
3Productivity
If automated EEG-based measurement is implemented, then efficiency and reproducibility are improved, but the system complexity increases
Solution Approach 1:
The patent designs the EEG-based pain assessment system to serve multiple functions: it monitors pain levels, tracks changes in conscious perception, provides objective data for clinical decision-making, and can be integrated into existing medical workflows. This multi-functionality justifies the initial complexity by delivering comprehensive pain management capabilities in a single integrated system.
Data Source
AI summary
There is described a computer-implemented method for measurement of a level of modified consciousness and a level of pain. The method comprises the steps of: - receiving measured data comprising electroencephalogram, EEG, data collected from one or more EEG electrodes; - extracting from the EEG data, a group indicators corresponding to: - a power, power (ta), associated with a theta-alpha frequency band, ta, within a theta-alpha frequency range; and - a power, F-power(dt) and/or P-power(dt), associated with a delta-theta frequency band, dt, within a delta-theta frequency range extracted from the at least one F- EEG and/or P- EEG electrode data; - determining, based on said group indicators, a depth of state, DoS, which is a value indicative for the level of a modified state of consciousness and a level of pain, LoP, which is a value indicative for the level of pain in the subject.