Effect of Novel Nanoscale Energy Patches on Spectral and Nonlinear Dynamic Features of Heart Rate Variability Signals

Abstract -LifeWave energy patches are novel nanoscale semiconducting biomolecular antennas, that when placed in the oscillating bioelectromagnetic field of the body, resonate at frequencies in unison with certain biomolecules in the cells and signal specific metabolic pathways to accelerate fat metabolism. As a consequence of accelerated fat burning more cellular energy becomes readily available to support all bodily energyconsuming functions. Heart rate variability refers to the beat-to-beat variation in heart rate (HR) and is modulated largely by the autonomic nervous system via changes in the balance between parasympathetic and sympathetic influences. Since short-term variations in HR reflect sympathetic nervous activity, they provide useful non-invasive markers for assessing autonomic control under various physiologic states and conditions. To evaluate the effect of LifeWave energy patches on HRV signals, pilot data from healthy volunteers were collected under three different conditions during rest and exercise using a BIOPAC system. The HRV signal was derived from preprocessed ECG signals using an Enhanced Hilbert Transform (EHT) algorithm with built-in missing beat detection capability for reliable QRS detection. Autoregressive (AR) modeling of the HRV signal power spectrum was achieved and different parameters from power spectrum as well as approximate entropy were calculated for comparison. Poincaré plots were then used as a visualization tool to highlight the variations in HRV signals before and after exercise under normal conditions and under the influence of placebo and energy patches. In this paper, for the first time, we present the spectral features and approximate entropy of the HRV signals in healthy individuals during rest, exercise, with placebo, and with energy patches. The results demonstrate that LifeWave energy patches have significant and clearly distinguishable effects on these important HRV signal features. These exciting results warrant comprehensive investigations to study the effects of these energy patches under different physical and health conditions in a large number of subjects in different age groups. Keywords -LifeWave energy patches; nanoscale molecular antennas; bioelectromagnetic field; heart rate variability signal processing; athletic training aids; acupuncture points

An integrated signal processing environment for detection of sleep disordered breathing in children using spectral and nonlinear dynamic measures of heart rate variability signal

This thesis emphasizes an application of novel signal processing techniques to detect Sleep Disordered Breathing (SDB) in children using their Heart Rate Variability (HRV). The HRV has been derived using an Enhanced Hilbert Transform (EHT) algorithm with a missing peak correction capability. Various signal processing techniques have been implemented on the HRV signal to obtain sensitive measures used in detection of SDB. All these techniques have been integrated into a user friendly interface. The algorithms were implemented in MATLAB 6.5 and the Graphical User Interface (GUI) in LabVIEW 7.1. The GUI provides a complete patient report with the summary of all the analyses performed. All the algorithms were developed, validated, and implemented on data from Physionet\u27s ECG databases and children data obtained from Adelaide Women\u27s and Children\u27s Hospital (WCH). The final results demonstrated that the EHT derived HRV yielded 100% accuracy when checked manually. The results obtained from the data files JT and NS have shown 80% sensitivity, 70% specificity giving an overall accuracy of 75%. The analyses performed were integrated into a friendly and easy to access software and the features obtained demonstrated needed sensitivity to detect SDB

Influence of starting material particle size on pellet surface roughness

10.1208/s12249-013-0031-5AAPS PharmSciTech151131-13

Application of thermal effusivity as a process analytical technology tool for monitoring and control of the roller compaction process

The aim of this study was to examine the relationship between physical characteristics of compacted ribbons and their thermal effusivity in an attempt to evaluate the feasibility of using effusivity for in-process monitoring of roller compaction. In this study, thermal effusivity, solid fraction, tensile strength, and Young's modulus of ribbons of microcrystal-line cellulose (MCC), anhydrous lactose, and placebo (PBO) formulations containing various ratios of MCC to anhydrous lactose (75∶20, 55∶40, 40∶55, and 20∶75) were determined at various compaction pressures (25–150 bars). The effusivity-square root of solid fraction relationship was linear for MCC and all the PBO formulations but was a second-order polynomial function for lactose. This could be due to the predominant deformation of lactose by brittle fracture, which might have significantly increased the number and size of contact points between particles, causing a change in thermal conductivity along with a density change. The effusivitytensile strength and effusivity-Young's modulus relationships were best described by logarithmic functions for MCC but were linear for lactose up to a compaction pressure of 65 bars. There were similar relationships for effusivity with tensile strength and Young's modulus for all PBO formulations except PBO IV, which might have been due to the deformation of lactose, the largest component in this formulation. Strong correlations between effusivity and physical properties of ribbons were established. Although these correlations were formulation-dependent, they demonstrate the possibility of using effusivity as a tool in monitoring roller compaction