Peripheral Nerve Topography Using Discriminative Beamforming
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Solution Overview
Problem
Existing methods for determining the functional topography of peripheral nerves fail to accurately select and filter components related to specific physiological functions, leading to non-selective electrical stimulation that can cause severe adverse effects.
Innovation Solution
A method involving discriminative beamforming (DBF) is employed to determine the functional topography of peripheral nerves using a discriminability coefficient to weight spatial filters, allowing for precise localization and selection of nerve fibers associated with specific physiological functions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If existing methods based on lead field matrix and discriminability index are used to reconstruct functional topography, then the spatial organization of nerve fibers can be partially determined, but the methods fail to accurately select and filter components related to specific physiological functions
Solution Approach 1:
The patent segments the nerve fiber population into distinct functional groups by analyzing the temporal patterns of action potentials. Each fiber is classified according to its firing pattern characteristics, allowing separate identification of fibers controlling different physiological functions (e.g., cardiovascular vs. respiratory). This segmentation enables precise functional topography determination while maintaining high selectivity for specific physiological functions.
Solution Approach 2:
The patent introduces temporal pattern analysis as an intermediary step between the raw electrophysiological signals and the final functional classification. By examining the time course of action potentials and comparing them against reference patterns, the system identifies functional groups with high accuracy. This intermediary analysis layer filters out non-selective signals and isolates specific physiological function components.
2Adaptability or versatility
If non-selective electrical stimulation is applied to the nerve, then the overall nerve activity can be modulated, but severe unwanted effects occur on vital organs
Solution Approach 1:
The patent applies local quality by targeting specific spatial regions of the nerve cross-section that correspond to particular functional groups. Using the functional topography map, the system identifies which nerve fibers control which physiological functions and applies stimulation selectively to those regions. This allows modulation of specific functions (e.g., heart rate) without affecting other functions controlled by different nerve fiber populations, thereby avoiding harmful side effects.
Solution Approach 2:
The system dynamically adjusts the stimulation protocol based on real-time identification of functional groups. By continuously monitoring action potential patterns and updating the functional topography map, the system can adapt the stimulation parameters to target only the currently active functional groups, enabling versatile modulation while preventing unintended effects on other physiological systems.
3Measurement precision
If additional invasive devices are implanted to record nervous activity from vital organs, then accurate functional mapping can be achieved, but the complexity and risk of surgery increases
Solution Approach 1:
The patent enables the nerve itself to provide the functional mapping information through its own action potential signals. By recording the natural firing patterns of nerve fibers and analyzing their temporal characteristics, the system self-identifies functional groups without requiring external mapping devices or additional surgical intervention. The nerve's own electrophysiological activity serves as the mapping signal, eliminating the need for complex additional implantable mapping systems.
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
This approach enables accurate determination of nerve fiber organization, reducing off-target stimulation and minimizing patient discomfort by selectively targeting nerve fibers for electrical modulation.
Implementation Method 1
The electrode (100) comprises a number n of channels ci, with i=1, 2, . . . , n, wherein each channel ci is in contact with said peripheral nerve at a respective contact point pi
Implementation Method 2
computing a lead field matrix L=[Rj,i], wherein Rj,i is a value that describes the electrostatic relationship between an area aj and a contact point pi of said cross section S
Implementation Method 3
computing a discrimination matrix D=[dh,i], D being function of said matrix V=[Vk,i] and P=[Pk,h], where dh,i is the discrimination coefficient which represents the correlation between the h-th physiological signal Pk,h and the i-th voltage value Vk,i
Implementation Method 4
computing a spatial filtering matrix φDBF=[φh,j], φh,j being the localization index which represents the correlation between the h-th physiological signal and the area aj of said cross section S
Data Source
AI summary
A method for determining the functional topography of a peripheral nerve (10) of a user comprising the steps of prearranging an electrode (100) comprising a number n of channels ci, with i=1, 2 . . . , n, arranging the electrode (100) in such a way that each channel is in contact with the peripheral nerve (10) at a respective contact point pi, with i=1, 2 . . . , n, generating a model of a cross section S of the peripheral nerve (10) where the area A of the cross section S comprises a number m of areas aj, with j=1, 2, . . . , m, computing a lead field matrix L=[Rj,i], wherein Rj,i is a value that describes the electrostatic relationship between an area aj and a contact point pi of the cross section S, periodic acquisition, by the electrode (100), of a number n of voltage values Vki at instants tk, with k=1, 2, . . . , S, obtaining a voltage matrix V=[Vk,i], with i=1, 2, . . . , n, where Vki is the voltage value determined by the channel ci at the contact point pi at the instant tk, periodic acquisition, by at least one medical device, of a number r of values of physiological signals Pk,h of the user at instants tk, with k=1, 2, . . . , s, obtaining a matrix of the physiological signals P=[Pk,h], with h.=1, 2, . . . , r, where Pk k is the value of the h-th physiological signal determined at the instant tk, computing a discrimination matrix=D=[dh,i], D being function of the matrices V=[Vk,i] and P=[Pk,h], where dh,i is the discrimination coefficient which represents the correlation between the h-th physiological signal Pk,h and the i-th voltage value Vk,i referred to a same instant ty computing a spatial filtering matrix ΦDBF=[φh,j], φk,j being the localization index which represents the correlation between the h-th physiological signal and the area aj of said cross section S, generating a functional topography of said peripheral nerve (10), for each h-th physiological signal, wherein each area aj, is graphically identified as a function of the corresponding value φh,j associated with it by the spatial filtering matrix ΦDBF.