The Relation between a Three-Day Sitting Meditation Fasting and the Participant’s Psychophysiological Condition: Through Nonlinear Chaos Analysis of Pulse Waves

Amyloid-β (Aβ) and tau oligomers have been identified as neurotoxic agents responsible for causing Alzheimer’s disease (AD). Clinical trials using Aβ and tau as targets have failed, giving rise to calls for new research approaches to combat AD. This paper provides such an approach. Most basic AD research has involved quiescent Aβ and tau solutions. However, studies involving laminar and extensional flow of proteins have demonstrated that mechanical agitation of proteins induces or accelerates protein aggregation. Recent MRI brain studies have revealed high energy, chaotic motion of cerebrospinal fluid (CSF) in lower brain and brainstem regions. These and studies showing CSF flow within the brain have shown that there are two energetic hot spots. These are within the third and fourth brain ventricles and in the neighborhood of the circle of Willis blood vessel region. These two regions are also the same locations as those of the earliest Aβ and tau AD pathology. In this paper, it is proposed that cardiac systolic pulse waves that emanate from the major brain arteries in the lower brain and brainstem regions and whose pulse waves drive CSF flows within the brain are responsible for initiating AD and possibly other amyloid diseases. It is further proposed that the triggering of these diseases comes about because of the strengthening of systolic pulses due to major artery hardening that generates intense CSF extensional flow stress. Such stress provides the activation energy needed to induce conformational changes of both Aβ and tau within the lower brain and brainstem region, producing unique neurotoxic oligomer molecule conformations that induce AD.

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Study of Rehabilitation of Injured Knee Joint Applying Chaotic Theory in Human Body Motion

Key Engineering Materials ◽

10.4028/www.scientific.net/kem.342-343.581 ◽

2007 ◽

Vol 342-343 ◽

pp. 581-584

Author(s):

Byung Young Moon ◽

Kwon Son ◽

Jung Hong Park

Keyword(s):

Time Series ◽

Lyapunov Exponent ◽

Angular Displacement ◽

Three Dimensional ◽

Gait Pattern ◽

Body Motion ◽

Largest Lyapunov Exponent ◽

Chaos Analysis ◽

Nonlinear Technique ◽

Injured Knee

Gait analysis is essential to identify accurate cause and knee condition from patients who display abnormal walking. Traditional linear tools can, however, mask the true structure of motor variability, since biomechanical data from a few strides during the gait have limitation to understanding the system. Therefore, it is necessary to propose a more precise dynamic method. The chaos analysis, a nonlinear technique, focuses on understanding how variations in the gait pattern change over time. Healthy eight subjects walked on a treadmill for 100 seconds at 60 Hz. Three dimensional walking kinematic data were obtained using two cameras and KWON3D motion analyzer. The largest Lyapunov exponent from the measured knee angular displacement time series was calculated to quantify local stability. This study quantified the variability present in time series generated from gait parameter via chaos analysis. Gait pattern is found to be chaotic. The proposed Lyapunov exponent can be used in rehabilitation and diagnosis of recoverable patients.

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