Pain Detection Using Physiological Signal Temporal Correlation
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Solution Overview
Problem
Current methods for measuring pain during dental procedures are subjective and lack real-time, objective assessment, making it difficult to differentiate between pain and non-pain arousal responses, which are both associated with physiological changes.
Innovation Solution
A processor that classifies pain and non-pain arousal states by analyzing the temporal proximity between physiological response events and oral contact events, using biological signals such as skin conductance or heart rate, to determine if a causal relationship exists between the mechanical engagement and the physiological response.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If physiological signals are used to measure pain and arousal, then objective real-time assessment is improved, but the ability to distinguish between pain and non-pain arousal deteriorates
Solution Approach 1:
The patent segments the continuous biological signal into discrete physiological response events by detecting specific patterns (peaks, troughs, or combinations) that indicate arousal. Each response event is then individually evaluated for temporal proximity to contact events, allowing differentiation between pain responses (closely timed) and non-pain arousal (less closely timed).
Solution Approach 2:
The system performs preliminary classification by establishing temporal proximity thresholds before final pain assessment. By pre-defining time windows and proximity criteria, the system prepares the framework for distinguishing pain from non-pain arousal responses, enabling more accurate real-time differentiation.
2Ease of operation
If subjective pain scales are used, then simplicity is improved, but measurement accuracy and temporal resolution deteriorate
Solution Approach 1:
The patent replaces the mechanical/subjective VAS scale method with an automated physiological signal processing system. Biological signals are continuously monitored and automatically analyzed to detect physiological response events, providing objective real-time pain assessment without requiring patient subjectivity or manual intervention.
Solution Approach 2:
The system enables self-service pain monitoring by automatically detecting and classifying physiological response events without requiring patient input. The processor autonomously evaluates temporal proximity between contact events and physiological responses, generating pain assessments independently of patient participation.
3Measurement precision
If physiological monitoring is implemented continuously, then real-time assessment is improved, but device complexity increases
Solution Approach 1:
The patent implements partial monitoring by focusing only on detecting specific physiological response events rather than analyzing every aspect of the continuous signal. The system applies temporal proximity evaluation only when response events occur, rather than continuously assessing all signal characteristics, thereby reducing computational complexity while maintaining real-time capability.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables real-time, objective differentiation between pain and non-pain arousal, providing a more accurate and sensitive assessment of pain levels during dental procedures, allowing for immediate adjustments and improved patient care.
Implementation Method 1
One such physiological signal is skin conductance which can be measured using galvanic skin resistance. Skin conductance measurements reflect changes in resistance and electrical conductivity in the skin
Data Source
AI summary
A processor and method for detecting pain and non-pain arousal responsive to physical stimuli applied to oral surfaces of a subject. A biological signal such as skin conductance, or another physiological parameter, can be used as a proxy measure for acute pain and/or non-pain arousal. The instances of mechanical engagement with the oral surfaces can be detected or tracked. Differential detection of pain vs non-pain arousal is achieved based on assessing signal synchronization or correlation between the biological signal and the oral contact events.