Center of pressure motion after calf vibration is more random in fallers than non-fallers: Prospective study of older individuals

Aging is associated with changes in balance control and elderly take longer to adapt to changing sensory conditions, which may increase falls risk. Low amplitude calf muscle vibration stimulates local sensory afferents/receptors and affects sense of upright when applied in stance. It has been used to assess the extent the nervous system relies on calf muscle somatosensory information and to rapidly change/perturb part of the somatosensory information causing balance unsteadiness by addition and removal of the vibratory stimulus. This study assessed the effect of addition and removal of calf vibration on balance control (in the absence of vision) in elderly individuals (> 65 years, n = 99) who did (n = 41) or did not prospectively report falls (n = 58), and in a group of young individuals (18-25 years, n = 23). Participants stood barefoot and blindfolded on a force plate for 135 s. Vibrators (60 Hz, 1 mm) attached bilaterally over the triceps surae muscles were activated twice for 15 s; after 15 and 75 s (45 s for recovery). Balance measures were applied in a windowed (15 s epoch) manner to compare center-of-pressure (CoP) motion before, during and after removal of calf vibration between groups. In each epoch, CoP motion was quantified using linear measures, and non-linear measures to assess temporal structure of CoP motion [using recurrence quantification analysis (RQA) and detrended fluctuation analysis]. Mean CoP displacement during and after vibration did not differ between groups, which suggests that calf proprioception and/or weighting assigned by the nervous system to calf proprioception was similar for the young and both groups of older individuals. Overall, compared to the elderly, CoP motion of young was more predictable and persistent. Balance measures were not different between fallers and non-fallers before and during vibration. However, non-linear aspects of CoP motion of fallers and non-fallers differed after removal of vibration, when dynamic re-weighting is required. During this period fallers exhibited more random CoP motion, which could result from a reduced ability to control balance and/or a reduced ability to dynamically reweight proprioceptive information. These results show that non-linear measures of balance provide evidence for deficits in balance control in people who go on to fall in the following 12 months

Transition from Persistent to Anti-Persistent Correlations in Postural Sway Indicates Velocity-Based Control

The displacement of the center-of-pressure (COP) during quiet stance has often been accounted for by the control of COP position dynamics. In this paper, we discuss the conclusions drawn from previous analyses of COP dynamics using fractal-related methods. On the basis of some methodological clarification and the analysis of experimental data using stabilogram diffusion analysis, detrended fluctuation analysis, and an improved version of spectral analysis, we show that COP velocity is typically bounded between upper and lower limits. We argue that the hypothesis of an intermittent velocity-based control of posture is more relevant than position-based control. A simple model for COP velocity dynamics, based on a bounded correlated random walk, reproduces the main statistical signatures evidenced in the experimental series. The implications of these results are discussed

Assessment Of Blood Pressure Regulatory Controls To Detect Hypovolemia And Orthostatic Intolerance

Regulation of blood pressure is vital for maintaining organ perfusion and homeostasis. A significant decline in arterial blood pressure could lead to fainting and hypovolemic shock. In contrast to young and healthy, people with impaired autonomic control due to aging or disease find regulating blood pressure rather demanding during orthostatic challenge. This thesis performed an assessment of blood pressure regulatory controls during orthostatic challenge via traditional as well as novel approaches with two distinct applications 1) to design a robust automated system for early identification of hypovolemia and 2) to assess orthostatic tolerance in humans. In chapter 3, moderate intensity hemorrhage was simulated via lower-body negative pressure (LBNP) with an aim to identify moderate intensity hemorrhage (-30 and -40 mmHg LBNP) from resting baseline. Utilizing features extracted from common vital sign monitors, a classification accuracy of 82% and 91% was achieved for differentiating -30 and -40 mmHg LBNP, respectively from baseline. In chapter 4, cause-and-effect relationship between the representative signals of the cardiovascular and postural systems to ascertain blood pressure homeostasis during standing was performed. The degree of causal interaction between the two systems, studied via convergent cross mapping (CCM), showcased the existence of a significant bi-directional interaction between the representative signals of two systems to regulate blood pressure. Therefore, the two systems should be accounted for jointly when addressing physiology behind fall. Further, in chapter 5, the potential of artificial gravity (2-g) induced via short-arm human centrifuge at feet towards evoking blood pressure regulatory controls analogous to standing was investigated. The observation of no difference in the blood pressure regulatory controls, during 2-g centrifugation compared to standing, strongly supported the hypothesis of artificial hypergravity for mitigating cardiovascular deconditioning, hence minimizing post-flight orthostatic intolerance

Comparing postural stability entropy analyses to differentiate fallers and non-fallers

The health and financial cost of falls has spurred research to differentiate the characteristics of fallers and non-fallers. Postural stability has received much of the attention with recent studies exploring various measures of entropy. This study compared the discriminatory ability of several entropy methods at differentiating two paradigms in the center-of-pressure of elderly individuals: (1) eyes open (EO) vs. eyes closed (EC) and (2) fallers (F) vs. non-fallers (NF). Methods were compared using the area under the curve (AUC) of the receiver-operating characteristic curves developed from logistic regression models. Overall, multiscale entropy (MSE) and composite multiscale entropy (CompMSE) performed the best with AUCs of 0.71 for EO/EC and 0.77 for F/NF. When methods were combined together to maximize the AUC, the entropy classifier had an AUC of for 0.91 the F/NF comparison. These results suggest researchers and clinicians attempting to create clinical tests to identify fallers should consider a combination of every entropy method when creating a classifying test. Additionally, MSE and CompMSE classifiers using polar coordinate data outperformed rectangular coordinate data, encouraging more research into the most appropriate time series for postural stability entropy analysis

Ann Biomed Eng

The health and financial cost of falls has spurred research to differentiate the characteristics of fallers and non-fallers. Postural stability has received much of the attention with recent studies exploring various measures of entropy. This study compared the discriminatory ability of several entropy methods at differentiating two paradigms in the center-of-pressure of elderly individuals: (1) eyes open (EO) vs. eyes closed (EC) and (2) fallers (F) vs. non-fallers (NF). Methods were compared using the area under the curve (AUC) of the receiver-operating characteristic curves developed from logistic regression models. Overall, multiscale entropy (MSE) and composite multiscale entropy (CompMSE) performed the best with AUCs of 0.71 for EO/EC and 0.77 for F/NF. When methods were combined together to maximize the AUC, the entropy classifier had an AUC of for 0.91 the F/NF comparison. These results suggest researchers and clinicians attempting to create clinical tests to identify fallers should consider a combination of every entropy method when creating a classifying test. Additionally, MSE and CompMSE classifiers using polar coordinate data outperformed rectangular coordinate data, encouraging more research into the most appropriate time series for postural stability entropy analysis.L30 AG022963/AG/NIA NIH HHS/United StatesR01 OH009222/OH/NIOSH CDC HHS/United States2017-05-01T00:00:00Z26464267PMC483370

METHODS FOR KINEMATIC ANALYSIS OF HUMAN MOVEMENT IN MILITARY APPLICATIONS: A REVIEW OF CURRENT AND PROSPECTIVE METHODS

Expansion of methods employed in the kinematic analysis of human movement for diagnosing of the physical and mental health of subjects can be traced back to the 1990`s when new information technologies and electronic recording systems started their development boom. Evaluation methods of body movement for the diagnostics of physical and mental health expanded significantly in clinical practice. This study presents an overview of these methods with the focus on how applicable the analysis of human movement can be in military practice, where they are currently marginally used. The aim of this study is to offer some recommendations on how particular methods could be utilized in an army context. This article also suggests the most appropriate methods of quantitative evaluation for posture and motion control in the course of standing, gait and other activities carried out in military training and active duty

Postural control: learning to balance and responses to mechanical and sensory perturbations

The purpose of the current research was to examine how a novel balance task is learnt by individuals with a mature neurological system, and to investigate the responses of experienced hand balancers to mechanical and sensory perturbations. Balance in each posture was assessed by various techniques, including: traditional measures of centre of pressure, nonlinear time series analysis of centre of pressure, estimates of feedback time delay from cross correlations and delayed regression models, and calculation of small, medium, and large movement corrections. Data from this study suggests that the best balance metric for distinguishing between each of the balance conditions was the traditional balance measure of sway velocity. However, sway velocity cannot provide any further information on the underlying process of balance. Nonlinear measures of balance offer insight into the underlying deterministic processes that control balance, offering measures of system determinism, complexity, and predictability. Assessments of feedback time delay and movement corrections provide both an insight into the control of posture and help distinguish one condition from another. Both feedback time delay and movement corrections and magnitudes may be used simultaneously to delve further into the control of posture. Delayed regression models seem to be an appropriate and useful tool for estimating feedback time delays during balance. Findings support the use of the third term in the adapted regression model as a means of estimating the effect of passive stiffness on feedback time delay. Generally, with increased duration in handstand subjects displayed reduced sway as measured by traditional measures of balance. A more marked change in nonlinear measures of balance can be seen, with quicker reductions in variance for some nonlinear measures of balance than in the traditional measures. It may be that more pronounced changes in nonlinear measures represent changes in the subjects underlying process of postural control, whereas less pronounced changes in traditional measures relate more to their general ability or performance in the balance task

Fractal Analysis of Center of Pressure Velocity Time Series in Parkinson's Disease

Abstract The purpose of this study was to test the sensitivity of system parameters of the Center of Pressure velocity (COPv) time series using Detrended Fluctuation Analysis to pre-clinical postural instability (PI) in PD, the progression of PI due to PD progression, and ultimately fall risk. The long term goal is to create quantitative clinically significant measures of pre-clinical PD PI, the progression of PI due to PD progression, and fall risk. Postural sway data collected in a previous study, including participants with mild PD (PD-Mi), moderate PD (PD-Mo) and age-range-matched healthy controls (HC), were analyzed in this study. Ground reaction forces and moments were collected from subjects standing on force plates in quiet postural sway in eyes open (EO) and eyes closed (EC) conditions. COPv was calculated and analyzed as a non-stationary time series. We investigated the temporal parameter of Absolute Average Maximal Velocity (AAMV), the system order parameter of Approximate Entropy (ApEn), and fractal parameters from the DFA which were the short (α1) and long (α2) term scaling behavior of the time series and the time scale at which the behavior changes – the crossover index (CrI). AAMV showed significant group differences between HC and PD-Mo and significant condition differences. In the fractal analysis, α1 showed significant group differences between HC and PD-Mo and α2 showed significant differences between conditions. Due to the pilot nature of the study, power analysis was conducted on all non-significant measures in order to investigate required subject numbers for significance. Feasible subject numbers were found for many of the measures. These results suggest that the temporal and fractal analysis of the COPv time series are sensitive measures of the differences between PD and HC and can be used in concert with traditional measures to further benefit clinical analysis, understanding of disease pathology, and development of computer simulation models of postural control in PD

Distinction of non-specific low back pain patients with proprioceptive disorders from healthy individuals by linear discriminant analysis

The central nervous system (CNS) dynamically employs a sophisticated weighting strategy of sensory input, including vision, vestibular and proprioception signals, towards attaining optimal postural control during different conditions. Non-specific low back pain (NSLBP) patients frequently demonstrate postural control deficiencies which are generally attributed to challenges in proprioceptive reweighting, where they often rely on an ankle strategy regardless of postural conditions. Such impairment could lead to potential loss of balance, increased risk of falling, and Low back pain recurrence. In this study, linear and non-linear indicators were extracted from center-of-pressure (COP) and trunk sagittal angle data based on 4 conditions of vibration positioning (vibration on the back, ankle, none or both), 2 surface conditions (foam or rigid), and 2 different groups (healthy and non-specific low back pain patients). Linear discriminant analysis (LDA) was performed on linear and non-linear indicators to identify the best sensory condition towards accurate distinction of non-specific low back pain patients from healthy controls. Two indicators: Phase Plane Portrait ML and Entropy ML with foam surface condition and both ankle and back vibration on, were able to completely differentiate the non-specific low back pain groups. The proposed methodology can help clinicians quantitatively assess the sensory status of non-specific low back pain patients at the initial phase of diagnosis and throughout treatment. Although the results demonstrated the potential effectiveness of our approach in Low back pain patient distinction, a larger and more diverse population is required for comprehensive validation