Gait termination : a review of experimental methods and the effects of aging and gait pathologies

The study of human gait has expanded and diversified to the extent that it is now possible to identify a substantive literature concerning a variety of gait tasks, such as gait initiation [Halliday SE, Winter DA, Frank JS, Patla AE, Prince F. The initiation of gait in young, elderly, and Parkinson's disease subjects. Gait Posture 1998;8:8–14; Mickelborough J, van der Linden ML, Tallis RC, Ennos AR. Muscle activity during gait initiation in normal elderly people. Gait Posture 2004;19:50–57], stepping over and across obstacles [Patla AE, Prentice SD, Robinson C, Newfold J. Visual control of locomotion: strategies for changing direction and for going over obstacles. J Exp Psych 1991;17:603–34; Chen, HC, Ashton-Miller JA, Alexander NB, Schultz AB. Effect of age and available response time on ability to step over an obstacle. J Gerontol 1994;49:227–33; Sparrow WA, Shinkfield AJ, Chow S, Begg RK. Gait characteristics in stepping over obstacles. Hum Mov Sci 1996;15:605–22; Begg RK, Sparrow WA, Lythgo ND. Time-domain analysis of foot–ground reaction forces in negotiating obstacles. Gait Posture 1998;7:99–109; Patla AE, Rietdyk S. Visual control of limb trajectory over obstacles during locomotion: effect of obstacle height and width. Gait Posture 1993;1:45–60] negotiating raised surfaces such as curbs and stairs [Begg RK, Sparrow WA. Gait characteristics of young and older individuals negotiating a raised surface: implications for the prevention of falls. J Gerontol Med Sci 2000;55A:147–54; Mcfayden BJ, Winter DA. An integrated biomechanical analysis of normal stair ascent and descent. J Biomech 1988;21:733–44]. In addition, increasing research interest in age-related declines in gait that might predispose individuals to falls has engendered a very extensive literature concerning ageing effects on gait. While rapid locomotor adjustments are common in the course of daily activities there has been no previous review of the findings concerning gait adaptations when walking is terminated both rapidly and unexpectedly. The aims of this review were first, to summarise the key research findings and methodological considerations from studies of termination. The second aim was to demonstrate the effects of ageing and gait pathologies on termination with respect to the regulation of step characteristics, lower-limb muscle activation patterns and foot–ground reaction forces.

A neural networks learning algorithm for minor component analysis and its convergence analysis

The eigenvector associated with the smallest eigenvalue of the autocorrelation matrix of input signals is called minor component. Minor component analysis (MCA) is a statistical approach for extracting minor component from input signals and has been applied in many fields of signal processing and data analysis. In this letter, we propose a neural networks learning algorithm for estimating adaptively minor component from input signals. Dynamics of the proposed algorithm are analyzed via a deterministic discrete time (DDT) method. Some sufficient conditions are obtained to guarantee convergence of the proposed algorithm.

A stable MCA learning algorithm

Minor component analysis (MCA) is an important statistical tool for signal processing and data analysis. Neural networks can be used to extract online minor component from input data. Compared with traditional algebraic  approaches, a neural network method has a lower computational complexity. Stability of neural networks learning algorithms is crucial to practical applications. In this paper, we propose a stable MCA neural networks learning algorithm, which has a more satisfactory numerical stability than some existing MCA algorithms. Dynamical behaviors of the proposed algorithm are analyzed via deterministic discrete time (DDT) method and the conditions are obtained to guarantee convergence. Simulations are carried out to illustrate the theoretical results achieved.

Development of a new versatile computer controlled electrochemical/ESR data acquisition system

A new versatile computer controlled electrochemlcal/ESR data acquisition system has been developed for the Investigation of short-lived radicals with life-times of 20 milliseconds and greater, Different computer programs have been developed to monitor the decay of radicals; over hours or minutes, seconds or milliseconds. Signal averaging and Fourier smoothing is employed in order to improve the signal to noise ratio. Two microcomputers are used to control the system, one home-made computer containing the M6800 chip which controls the magnetic field, and an IBM PC XT which controls the electrochemistry and the data acquisition. The computer programs are written in Fortran and C, and call machine language subroutines, The system functions by having the radical generated by an electrochemical pulse: after or during the pulse the ESR data are collected. Decaying radicals which have half-lives of seconds or greater have their spectra collected in the magnetic field domain, which can be swept as fast as 200 Gauss per second. The decay of the radicals in the millisecond region is monitored by time-resolved ESR: a technique in which data is collected in both the time domain and in the magnetic field domain. Previously, time-resolved ESR has been used (without field modulation) to investigate ultra-short-lived species with life-times in the region of only a few microseconds. The application of the data acquisition system to chemical systems is illustrated. This is the first time a computer controlled system whereby the radical is generated by electrochemical means and subsequently the ESR data collected, has been developed.

On the incremental learning and recognition of the pattern of movement of multiple labelled objects in dynamic scenes

In this paper we discuss combining incremental learning and incremental recognition to classify patterns consisting of multiple objects, each represented by multiple spatio-temporal features. Importantly the technique allows for ambiguity in terms of the positions of the start and finish of the pattern. This involves a progressive classification which considers the data at each time instance in the query and thus provides a probable answer before all the query information becomes available. We present two methods that combine incremental learning and incremental recognition: a time instance method and an overall best match method.

Design and analysis of an antenna for wireless energy harvesting in head-mountable DBS device

This paper presents design and simulation of a circular meander dipole antenna at the industrial, scientific, and medical band of 915 MHz for energy scavenging in a passive head-mountable deep brain stimulation device. The interaction of the proposed antenna with a rat body is modeled and discussed. In the antenna, the radiating layer is meandered, and a FR-4 substrate is used to limit the radius and height of the antenna to 14 mm and 1.60 mm, respectively. The resonance frequency of the designed antenna is 915 MHz and the bandwidth of 15 MHz at a return loss of -10 dB in free space. To model the interaction of the antenna with a rat body, two aspects including functional and biological are considered. The functional aspect includes input impedance, resonance frequency, gain pattern, radiation efficiency of the antenna, and the biological aspect involves electric field distribution, and SAR value. A complete rat model is used in the finite difference time domain based EM simulation software XFdtd. The simulated results demonstrate that the specific absorption rate distributions occur within the skull in the rat model, and their values are higher than the standard regulated values for the antenna receiving power of 1W.

Electromagnetic energy harvesting in a head-mountable DBS device using a circular PIFA

A circular planar inverted-F antenna (PIFA) is designed and simulated at the industrial, scientific, and medical (ISM) band of 915 MHz for energy harvesting in a head-mountable deep brain stimulation device. Moreover, a rectifier is designed, and also the interaction of the PIFA with a rat head model is investigated. In the proposed PIFA, the top radiating layer is meandered, and a substrate of FR-4 is used. The radius and the height of the antenna are 10 mm and 1.8 mm, respectively. The bottom conductive layer works as a ground plate, and a superstrate of polyethylene reduces the electromagnetic penetration into the rat head. The resonance frequency of the designed antenna is 915 MHz with a bandwidth of 18 MHz at the return loss of -10 dB in free space. The antenna parameters (e.g. reflection coefficient, gain, radiation efficiency), electric field distribution, and SAR value are evaluated within a seven-layer rat head model by using the finite difference time domain EM simulation software XFdtd. The interactions of the antenna and the rat head model are studied in both functional and biological aspects.

Altered cardiac autonomic nervous function in depression

Background:
Depression is an independent risk factor for coronary artery disease. Autonomic instability may play a mediating or moderating role in this relationship; however this is not well understood. The objective of this study was to explore cardiac autonomic function and cardiac arrhythmia in depression, the correlation between depression severity and Heart Rate Variability (HRV) related indices, and the prevalence of arrhythmia.

Methods:
Individuals (n = 53) with major depression as assessed by the Diagnostic and Statistical Manual of Mental Disorders, who had a Hamilton Rating Scale for Depression (HAMD) score ≥20 and a Zung Self-Rating Depression Scale score > 53 were compared to 53 healthy individuals, matched for age and gender. Multichannel Electrocardiograph ECG-92C data were collected over 24 hours. Long-term changes in HRV were used to assess the following vagally mediated changes in autonomic tone, expressed as time domain indices: Standard deviation of the NN intervals (SDNN), standard deviation of 5 min averaged NN intervals (SDANN), Root Mean Square of the Successive Differences (RMSSD) and percentage of NN intervals > 50 ms different from preceding interval (pNN50). Pearson’s correlations were conducted to explore the strength of the association between depression severity (using the SDS and HRV related indices, specifically SDNN and low frequency domain / high frequency domain (LF/HF)).

Results:
The values of SDNN, SDANN, RMSSD, PNN50 and HF were lower in the depression group compared to the control group (P<.05). The mean value of the LF in the depression group was higher than the in control group (P<.05). Furthermore the ratio of LF/HF was higher among the depression group than the control group (P<.05). A linear relationship was shown to exist between the severity of the depression and HRV indices. In the depression group, the prevalence of arrhythmia was significantly higher than in the control group (P<.05), particularly supraventricular arrhythmias.

Conclusions:
Our findings suggest that depression is accompanied by dysfunction of the cardiac autonomic nervous system, and further, that depression severity is linked to severity of this dysfunction. Individuals with depression appear to be susceptible to premature atrial and/or ventricular disease.

Design and analysis of an antenna for batteryless transcranial direct current stimulation devices

The purpose of this study is to design a low-cost planar Archimedean dipole antenna for batteryless transcranial direct current stimulation devices. The antenna parameters including resonance frequency, radiation efficiency, radiation pattern, and gain are simulated using finite difference time domain based electromagnetic simulation software XFdtd. The proposed antenna is simulated with low-cost FR4 PCB substrate of thickness of 1.6 mm. The antenna is designed with half wavelength of resonant frequency and fed with a matching line. The target frequency band is the industrial, scientific and medical (ISM) band of 915 MHz which is in the simulated band width of 31 MHz (903-934MHz). Moreover, since the bio-effect of specific absorption rate by radio frequency electromagnetic wave for power harvesting is an important concern, we try to find out the safety limit. Thus a quantitative analysis of distributions of electric field and power absorption in anatomical human head model by the far field radio frequency energy received by our designed antenna has been presented.

An effective VAR planning to improve dynamic voltage profile of distribution networks with distributed wind generation

This paper proposes an effective VAR planning based on reactive power margin for the enhancement of dynamic voltage stability in distribution networks with distributed wind generation. The analysis is carried over a distribution test system representative of the Kumamoto area in Japan. The detailed mathematical modeling of the system is also presented. Firstly, this paper provides simulation results showing the effects of composite load on voltage dynamics in the distribution network through an accurate time-domain analysis. Then, a cost-effective combination of shunt capacitor bank and distribution static synchronous compensator (D-STATCOM) is selected to ensure fast voltage recovery after a sudden disturbance. The analysis shows that the proposed approach can reduce the size of compensating devices, which in turn, reduces the cost. It also reduces power loss of the system.

Effects of load modeling in power distribution system with distributed wind generation

This paper presents the impact of different types of load models in distribution network with distributed wind generation. The analysis is carried out for a test distribution system representative of the Kumamoto area in Japan. Firstly, this paper provides static analysis showing the impact of static load on distribution system. Then, it investigates the effects of static as well as composite load based on the load composition of IEEE task force report [1] through an accurate time-domain analysis. The analysis shows that modeling of loads has a significant impact on the voltage dynamics of the distribution system with distributed generation.

New variable step-sizes minimizing mean-square deviation for the lms-type algorithms

The least-mean-square-type (LMS-type) algorithms are known as simple and effective adaptation algorithms. However, the LMS-type algorithms have a trade-off between the convergence rate and steady-state performance. In this paper, we investigate a new variable step-size approach to achieve fast convergence rate and low steady-state misadjustment. By approximating the optimal step-size that minimizes the mean-square deviation, we derive variable step-sizes for both the time-domain normalized LMS (NLMS) algorithm and the transform-domain LMS (TDLMS) algorithm. The proposed variable step-sizes are simple quotient forms of the filtered versions of the quadratic error and very effective for the NLMS and TDLMS algorithms. The computer simulations are demonstrated in the framework of adaptive system modeling. Superior performance is obtained compared to the existing popular variable step-size approaches of the NLMS and TDLMS algorithms. © 2014 Springer Science+Business Media New York.

Identifying the determinants of renewable energy consumption in leading renewable energy investor emerging countries

This article analyses the determinants of renewable energy consumption in six major emerging economies who are proactively accelerating the adoption of renewable energy. The long-run elasticities from both panel methods (fully modified ordinary least square and dynamic least square) and the time series method (autoregressive distributed lag) seem to be pretty consistent. For Brazil, China, India and Indonesia, in the long-run, renewable energy consumption is significantly determined by income and pollutant emission. However, for Philippines and Turkey, income seems to be the main driver for renewable energy consumption. In the short-run, for Brazil and China bi-directional causalities between renewable energy and income; and between renewable energy and pollutant emission are found. This research justifies the efforts undertaken by emerging countries to reduce the carbon intensity by increasing the energy efficiency and substantially increasing the share of renewable in the overall energy mix

Classification of team sport activities using a single wearable tracking device

Wearable tracking devices incorporating accelerometers and gyroscopes are increasingly being used for activity analysis in sports. However, minimal research exists relating to their ability to classify common activities. The purpose of this study was to determine whether data obtained from a single wearable tracking device can be used to classify team sport-related activities. Seventy-six non-elite sporting participants were tested during a simulated team sport circuit (involving stationary, walking, jogging, running, changing direction, counter-movement jumping, jumping for distance and tackling activities) in a laboratory setting. A MinimaxX S4 wearable tracking device was worn below the neck, in-line and dorsal to the first to fifth thoracic vertebrae of the spine, with tri-axial accelerometer and gyroscope data collected at 100Hz. Multiple time domain, frequency domain and custom features were extracted from each sensor using 0.5, 1.0, and 1.5s movement capture durations. Features were further screened using a combination of ANOVA and Lasso methods. Relevant features were used to classify the eight activities performed using the Random Forest (RF), Support Vector Machine (SVM) and Logistic Model Tree (LMT) algorithms. The LMT (79-92% classification accuracy) outperformed RF (32-43%) and SVM algorithms (27-40%), obtaining strongest performance using the full model (accelerometer and gyroscope inputs). Processing time can be reduced through feature selection methods (range 1.5-30.2%), however a trade-off exists between classification accuracy and processing time. Movement capture duration also had little impact on classification accuracy or processing time. In sporting scenarios where wearable tracking devices are employed, it is both possible and feasible to accurately classify team sport-related activities.