Autonomic Nerve Index Calculation via Complex Waveform Analysis
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Solution Overview
Problem
Existing autonomic nerve function measuring apparatuses struggle to provide a constant autonomic nerve index due to fluctuating indices, making it difficult to perceive physiological signals as scalar quantities, especially in relaxed and tensed states.
Innovation Solution
An autonomic nerve index calculation system that generates pulse wave and heartbeat interval waveform data, filters it into specific frequency bands, converts the data into complex numbers, and calculates the autonomic nerve index using Hilbert transformation, allowing for the extraction of distribution coefficients that represent physiological states as constant numerical values.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If power spectral density of amplitude variation is calculated using Fourier transformation and LF/HF ratio is computed, then autonomic nerve function can be indexed, but the index changes from moment to moment and cannot provide a definite constant value
Solution Approach 1:
The patent transforms the analysis parameters from simple amplitude spectral density to complex number representation including both amplitude and phase information. By using Hilbert transformation to extract instantaneous amplitude and phase, the system captures the dynamic characteristics of pulse waves while maintaining a stable indexing method that accounts for moment-to-moment variations through proper parameter selection and combination.
Solution Approach 2:
The patent introduces complex numbers as an intermediary representation between the raw pulse wave signal and the final autonomic nerve index. The complex number formulation allows simultaneous consideration of amplitude and phase relationships in multiple frequency bands, providing a more robust intermediate representation that leads to a stable final index despite instantaneous signal variations.
2Loss of information
If spectral intensity and phase information of low frequency and high frequency components are indexed, then autonomic nerve indices can be presented, but variance of physiological indices increases in relaxed state and decreases in tensed state making scalar perception difficult
Solution Approach 1:
The patent extends the analysis from single-dimensional amplitude spectral density to two-dimensional complex number space incorporating both amplitude and phase. This dimensional expansion allows the system to capture richer physiological information while the final index computation projects this multi-dimensional data back to a scalar value that is easy to interpret and compare across different physiological states.
Solution Approach 2:
The complex number-based indexing method serves multiple functions simultaneously: it captures amplitude variations, phase relationships, and cross-frequency interactions within a unified framework. This multi-functional approach allows the same indexing system to effectively represent different physiological states (relaxed, tensed, etc.) while maintaining consistent scalar output that is easy to perceive and compare.
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 the calculation of a constant autonomic nerve index, effectively quantifying physiological states by distributing amplitude and phase terms into normal distributions, allowing for accurate description of autonomic nerve responses and physiological conditions.
Implementation Method 1
a band-pass filter configured to filter the generated pulse wave waveform data or the generated heartbeat interval waveform data in at least one predetermined frequency band
Implementation Method 2
a complex number conversion unit configured to convert the filtered pulse wave waveform data into a complex number and calculate pulse wave complex waveform data of the at least one predetermined frequency band
Data Source
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AI summary
An autonomic nerve index calculation system (1) for calculating an autonomic nerve index of a living body according to an embodiment of the present disclosure generates pulse wave waveform data using at least one pulse wave signal of the living body (S101), filters the generated pulse wave waveform data in at least one predetermined frequency band (S102), converts the filtered pulse wave waveform data into a complex number and calculate pulse wave complex waveform data of the at least one frequency band (S103), and calculates the autonomic nerve index of the living body in the at least one frequency band based on the calculated pulse wave complex waveform data (S107, S108).