The Network Wave, first demonstrated by Dr. Donny Epstein over 25 years ago, has been described as a spinal healing wave that helps to promote wellness, self-awareness, and healthier lifestyle choices. The Network Wave response is a visible physiologic process or undulatory motion of the spine, and surrounding structures, which has been demonstrated to be linked to specific frequency entrained spinal oscillation (rocking vertebrae), arising from precise force or touch applications to the spine. 

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The EpiEnergetics Foundation currently provides a grant to the University of Southern California (USC) Department of Electrical Engineering and Mathematics through the lab of Edmond Jonckheere, Ph.D.  Research explores the mathematical and physiological effects and properties of the Network Wave, spinal coherence and the human body as a dynamical system.

Visit Dr. Jonckheere's Website

 

 

 

“...the spinal wave is a coherent movement elicited by a Central Pattern Generator, opening the road for the potential of this coherence analysis to become part of the neurological suite.”
— Martin-del Campo R, Jonckheere E. Stationary regime for standing wave central pattern generator. (2015)
Network Wave Published Research
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Detection of Rhythmic Synchronized Double Neuronal Discharges & Bursting Rate Variability Assessment

Bursting neurons play an important role in motor pattern synchronization and neuronal communication resulting in the ability to coordinate muscles across large anatomical distances. Such synchronization among multiple motor units is revealed by rhythmic surface electromyographic (sEMG) activity along paraspinal muscles.

Stationary versus bifurcation regime for standing wave central pattern generator.

The purpose of this research is to show that the correlation analysis on surface electromyographic (sEMG) signals that originally confirmed existence of a standing wave central pattern generator (CPG) along the spine are reproducible despite evolution of the entrainment technique, different hardware and data collection protocol.

The Network Spinal Wave as a Central Pattern Generator

Objectives: This article explains the research on a unique spinal wave visibly observed in association with network spinal analysis care. Since 1997, the network wave has been studied using surface electromyography (sEMG), characterized mathematically, and determined to be a unique and repeatable phenomenon.

Stationary Regime for Standing Wave Central Pattern Generator

The purpose of this research is to show that the spatio-temporal analysis on surface Electromyographic (sEMG) signals that originally confirmed existence of a standing wave Central Pattern Generator (CPG) along the spine are reproducible under less than ideal conditions and despite evolution of the entrainment technique, different hardware and data collection protocol.

On a Standing Wave Central Pattern Generator and the Coherence problem

An electrophysiological phenomenon running up and down the spine, elicited by light pressure contact at very precise points and thereafter taking the external appearance of an undulatory motion of the spine, is analyzed from its standing wave, coherence, and synchronization-at-a-distance properties.

Letter to the Editor: Network Spinal Analysis

There has been much debate about the objective basis of Network Spinal Analysis (NSA) and Network Spinal Analysis Care. I and a number of my colleagues set out to study this. Our work during the last 10 years has revealed some significant objective, repeatable, reliable, and measurable changes, which are the subject of a full paper being submitted for publication.

Visualization of a stationary CPG-revealing spinal wave

Central Pattern Generator (CPG) is still an elusive concept that has a visual manifestation as a rhythmic oscillation commanded from the spine, but that also has another manifestation as a train of bursts in the surface electromyographic (sEMG) signals recorded on the para-spinal muscles.

Chaotic Modeling in Network Spinal Analysis: Nonlinear Canonical Correlation with Alternating Conditional Expectation (ACE): A Preliminary Report

This paper presents a preliminary non-linear mathematical analysis of surface electromyographic (sEMG) signals from a subject receiving Network Spinal Analysis (NSA).The unfiltered sEMG data was collected over a bandwidth of 10-500 Hz and stored on a PC compatible computer.