Univariate and bivariate empirical mode decomposition for postural stability analysis

The aim of this paper was to compare empirical mode decomposition (EMD) and two new extended methods of Open image in new windowEMD named complex empirical mode decomposition (complex-EMD) and bivariate empirical mode decomposition (bivariate-EMD). All methods were used to analyze stabilogram center of pressure (COP) time series. The two new methods are suitable to be applied to complex time series to extract complex intrinsic mode functions (IMFs) before the Hilbert transform is subsequently applied on the IMFs. The trace of the analytic IMF in the complex plane has a circular form, with each IMF having its own rotation frequency. The area of the circle and the average rotation frequency of IMFs represent efficient indicators of the postural stability status of subjects. Experimental results show the effectiveness of these indicators to identify differences in standing posture between groups

Fractal time series analysis of postural stability in elderly and control subjects

<p>Abstract</p> <p>Background</p> <p>The study of balance using stabilogram analysis is of particular interest in the study of falls. Although simple statistical parameters derived from the stabilogram have been shown to predict risk of falls, such measures offer little insight into the underlying control mechanisms responsible for degradation in balance. In contrast, fractal and non-linear time-series analysis of stabilograms, such as estimations of the Hurst exponent (H), may provide information related to the underlying motor control strategies governing postural stability. In order to be adapted for a home-based follow-up of balance, such methods need to be robust, regardless of the experimental protocol, while producing time-series that are as short as possible. The present study compares two methods of calculating H: Detrended Fluctuation Analysis (DFA) and Stabilogram Diffusion Analysis (SDA) for elderly and control subjects, as well as evaluating the effect of recording duration.</p> <p>Methods</p> <p>Centre of pressure signals were obtained from 90 young adult subjects and 10 elderly subjects. Data were sampled at 100 Hz for 30 s, including stepping onto and off the force plate. Estimations of H were made using sliding windows of 10, 5, and 2.5 s durations, with windows slid forward in 1-s increments. Multivariate analysis of variance was used to test for the effect of time, age and estimation method on the Hurst exponent, while the intra-class correlation coefficient (ICC) was used as a measure of reliability.</p> <p>Results</p> <p>Both SDA and DFA methods were able to identify differences in postural stability between control and elderly subjects for time series as short as 5 s, with ICC values as high as 0.75 for DFA.</p> <p>Conclusion</p> <p>Both methods would be well-suited to non-invasive longitudinal assessment of balance. In addition, reliable estimations of H were obtained from time series as short as 5 s.</p

Identification of the period of stability in a balance test after stepping up using a simplified cumulative sum

Falls are a major cause of death in older people. One method used to predict falls is analysis of Centre of Pressure (CoP) displacement, which provides a measure of balance quality. The Balance Quality Tester (BQT) is a device based on a commercial bathroom scale that calculates instantaneous values of vertical ground reaction force (Fz) as well as the CoP in both anteroposterior (AP) and mediolateral (ML) directions. The entire testing process needs to take no longer than 12 s to ensure subject compliance, making it vital that calculations related to balance are only calculated for the period when the subject is static. In the present study, a method is presented to detect the stabilization period after a subject has stepped onto the BQT. Four different phases of the test are identified (stepping-on, stabilization, balancing, stepping-off), ensuring that subjects are static when parameters from the balancing phase are calculated. The method, based on a simplified cumulative sum (CUSUM) algorithm, could detect the change between unstable and stable stance. The time taken to stabilize significantly affected the static balance variables of surface area and trajectory velocity, and was also related to Timed-up-and-Go performance. Such a finding suggests that the time to stabilize could be a worthwhile parameter to explore as a potential indicator of balance problems and fall risk in older people

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A set of technological tools for physical frailty assessment

Early detection of frailty in the elderly is an important issue, to ensure appropriate interventions can be undertaken to improve the outcome for frail elderly. Among the various models proposed for frailty detection, physical criteria described by Fried et al can be fed by very simple and friendly devices usable in any uncontrolled environment. This paper proposes a set of such technological tools providing a measure of these physical and physiological indices of frailty

Surface electromyography as a tool to assess the responses of car passengers to lateral accelerations: Part I. Extraction of relevant muscular activities from noisy recordings

The aim of this paper is to develop a method to extract relevant activities from surface electromyography (SEMG) recordings under difficult experimental conditions with a poor signal to noise ratio. High amplitude artifacts, the QRS complex, low frequency noise and white noise significantly alter EMG characteristics. The CEM algorithm proved to be useful for segmentation of SEMG signals into high amplitude artifacts (HAA), phasic activity (PA) and background postural activity (BA) classes. This segmentation was performed on signal energy, with classes belonging to a χ2 distribution. Ninety-five percent of HAA events and 96.25% of BA events were detected, and the remaining noise was then identified using AR modeling, a classification based upon the position of the coordinates of the pole of highest module. This method eliminated 91.5% of noise and misclassified only 3.3% of EMG events when applied to SEMG recorded on passengers subjected to lateral accelerations

Design and validation of the Grip-ball for measurement of hand grip strength

The Grip-ball is a new dynamometer used to evaluate grip strength, as well as for use in home-based rehabilitation of the hand and forearm. The Grip-ball consists of pressure and temperature sensors and an electronic wireless communication system contained in an airtight ball. That can be inflated to different pressures. The device has advantages over standard dynamometers in that it looks like a simple ball, and can wirelessly communicate via Bluetooth to any compatible receiver, thus have potential to be used for clinical assessment and rehabilitation in a remote setting. The reliability and reproducibility of the device were assessed for the pressure sensor itself, as well as the relationship between the force applied and the pressure measured by the Grip-ball. The initial validation was performed using the pressure sensor without the ball in order to confirm the accuracy of the sensor used. A second validation study was conducted using the Grip-ball rather than just its sensor to examine the relationship between the pressure measured inside the ball and force applied. The results showed that there is a very good correlation (r=0.997, p<0.05) between the pressure measured by the Grip-ball sensor and that measured by a Vigorimeter, thus confirming the reliability of the sensor used in the Grip-ball. A quadratic regression equation was calculated in order to predict the force applied based on the pressure measured inside the ball, and the initial pressure to which the ball was inflated (R(2)=0.97, standard error 10.9N). Such a finding compares favourably with the variability inherent in Jamar recordings, thus indicating that the Grip-ball could be used to assess grip force. An industrial version of the Grip-ball, which is currently under development, will be able to be used for the entire range of grip force in the population

Nonlinear chaotic component extraction for postural stability analysis

This paper proposes a nonlinear analysis of the human postural steadiness system. The analyzed signal is the displacement of the centre of pressure (COP) collected from a force plate used for measuring postural sway. Instead of analyzing the classical nonlinear parameters on the whole signal, the proposed method consists of analyzing the nonlinear dynamics of the intrinsic mode functions (IMF) of the COP signal. Based on the computation of the IMFs Lyapunov exponents, it is shown that pre-processing the COP signal with the Empirical Mode Decomposition allows an efficient extraction of its chaotic component

Changes in impedance at the electrode-skin interface of surface EMG electrodes during long-term EMG recordings

Changes in the impedance at the electrode-skin interface of SEMG electrodes on the tibialis anterior were assessed in nine subjects. SEMG signals were recorded using a bipolar electrode configuration that conformed to the SENIAM recommendations for SEMG data collection. Impedance measurements were made between a pair of bipolar electrodes using a custom-built device consisting of a PC and an impedance conversion circuit. The impedance device enabled the simultaneous application and recording of a waveform constructed of a known combination of sinusoids passed between the two electrodes. SEMG recordings at 10% of each subject's maximal voluntary force during ankle dorsiflexion were made for a 30-s period every 15-min over a two hour period. Impedance was measured immediately before and after each SEMG recording. All subjects gave their written informed consent