ANTICIPATION EFFECT ON KNEE JOINT STABILITY DURING PLANNED AND UN-PLANNED MOVEMENT TESTS IN LABORATORY

The purpose of this study was to investigate the anticipation effect on knee stability during functional test in laboratory. Ten healthy male subjects were recruited and instructed to perform a series of planned and un-planned stop-jumping tasks. Knee joint kinematics was measured by a motion analysis system. The subjects demonstrated different abduction and rotation angles for reactive tasks. This suggested that if knee abduction or rotational stability is considered as a primary measurement in documenting knee stability, such as in the investigation of rehabilitation progress after anterior cruciate ligament reconstruction, both planned and un-planned tasks should be considered as to take the anticipation effect into account

Properties of Si-SiO2 interface traps due to low-energy Ar+ backsurface bombardment in n-channel nitrided MOSFETs

Flicker noise in backsurface gettered, nitrided n-channel MOSFETs is characterized over a wide range of temperatures and biases. The gettering time ranged from 10 to 40 minutes. The noise power spectra for devices with different gettering times are compared to the ungettered devices which serve as the control. It is found that flicker noise is reduced by backsurface gettering for short gettering times. A rebound in the noise magnitude is observed for long gettering times. Investigations of the temperature dependencies of the noise power spectra indicates that the low-frequency noise arises from thermal activation of carriers to traps at the Si-SiO2 interface. Backsurface gettering results in the modification of the energy distribution of the interface traps, probably due to stress relaxation at the Si-SiO2 interface.published_or_final_versio

Hybrid Taguchi-Differential Evolution Algorithm for Parameter Estimation of Differential Equation Models with Application to HIV Dynamics

This work emphasizes solving the problem of parameter estimation for a human immunodeficiency virus (HIV) dynamical model by using an improved differential evolution, which is called the hybrid Taguchi-differential evolution (HTDE). The HTDE, used to estimate parameters of an HIV dynamical model, can provide robust optimal solutions. In this work, the HTDE approach is effectively applied to solve the problem of parameter estimation for an HIV dynamical model and is also compared with the traditional differential evolution (DE) approach and the numerical methods presented in the literature. An illustrative example shows that the proposed HTDE gives an effective and robust way for obtaining optimal solution, and can get better results than the traditional DE approach and the numerical methods presented in the literature for an HIV dynamical model

Transcultural and psychometric validation of the Dispositional Resilience Scale (DRS-15) in Chinese adult women

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Reliability and validity of alternate step test times in subjects with chronic stroke

OBJECTIVE: (i) To investigate the intra-rater, inter-rater and test-retest reliability and minimal detectable change of the Alternate Step Test (AST) when assessing people with chronic stroke. (ii) To quantify the correlation between AST times and stroke-specific impairments. DESIGN: Cross-sectional study. SETTING: University-based rehabilitation centre. PARTICIPANTS: A convenience sample of 86 participants: 45 with chronic stroke, and 41 healthy elderly subjects. METHODS: The AST was administered along with the Fugl-Meyer Lower Extremity Assessment (FMA-LE), the Five Times Sit-To-Stand Test (FTSTS), limits of stability (LOS) measurements, Berg Balance Scale (BBS) scores, Chinese-translated Activities-specific Balance Confidence Scale (ABC-C) ratings, and the Timed “Up and Go” test (TUG). RESULTS: Excellent intra-rater, inter-rater and test-retest reliability were found, with a minimal detectable change of 3.26 s. AST times were significantly associated with FMA-LE assessment, FTSTS times, LOS in the forward and backward directions and to the affected side, BBS ratings and TUG times. CONCLUSION: AST time is a reliable assessment tool that correlates with different stroke-specific impairments in people with chronic stroke.published_or_final_versio

The use of motion analysis to measure pain-related behaviour in a rat model of degenerative tendon injuries

Chronic tendinopathy is characterized with longstanding activity-related pain with degenerative tendon injuries. An objective tool to measure painful responses in animal models is essential for the development of effective treatment for tendinopathy. Gait analysis has been developed to monitor the inflammatory pain in small animals. We reported the use of motion analysis to monitor gait changes in a rat model of degenerative tendon injury. Intratendinous injection of collagenase into the left patellar tendon of Sprague Dawley rat was used to induce degenerative tendon injury, while an equal volume of saline was injected in the control groups. Motion analyses with a high speed video camera were performed on all rats at pre-injury, 2, 4, 8, 12 or 16 weeks post injection. In the end-point study, the rats were sacrificed to obtain tendon samples for histological examination after motion analyses. In the follow-up study, repeated motion analyses were performed on another group of collagenase-treated and saline-treated rats. The results showed that rats with injured patellar tendon exhibited altered walking gait as compared to the controls. The change in double stance duration in the collagenase-treated rats was reversible by administration of buprenorphrine (p = 0.029), it suggested that the detected gait changes were associated with pain. Comparisons of end-point and follow-up studies revealed the confounding effects of training, which led to higher gait velocities and probably a different adaptive response to tendon pain in the trained rats. The results showed that motion analysis could be used to measure activity-related chronic tendon pain. © 2009 Elsevier B.V. All rights reserved

HIP-KNEE control for gait assistance with Powered Knee Orthosis

A Powered Knee Orthosis (PKO) was developed for the elderly and patients with disordered gait to regain normal walking. In order to enhance the PKO performance and reduce system complexity especially for people with muscle weakness in their knee joints, an algorithm named HIP-KNEE control is proposed. This algorithm is based on the analysis of kinematic gait model, and the desired knee joint angle (KNEE) is estimated from the measurements of hip joint angle (HIP). The relationship between HIP and KNEE is modeled as a polynomial, which can be easily implemented to an embedded controller for real-time control. This control method is suitable to subjects with good function in hip joint, and it can provide help in walking without special training. An Inertia Measurement Units (IMU) is used for obtaining HIP input, and integrated with a footswitch for checking the heel condition; the gait assistance performance can be further improved

Hybrid ensemble model with optimal weightage for suicidal behavior prediction

Suicidal behavior is a complex phenomenon that is contextually dependent and changes rapidly from one day to another. The problem in predicting suicidal behavior is identifying individuals and at-risk groups in crisis and at risk for suicide. The current predictive model, which uses machine learning techniques, has been shown to lack accuracy, and no study has attempted to use a voting ensemble model to predict suicidal behavior. The soft voting ensemble model demonstrated good performance in the healthcare setting, but assigning optimal weights for machine learning models is challenging. Therefore, this paper aims to propose a hybrid voting ensemble model to achieve optimal weights in predicting an individual with suicidal behavior. The results show that the proposed hybrid voting ensemble model can effectively classify an individual with suicidal behavior with an accuracy of 0.84 compared to other machine learning models (logistic regression, support vector machine, random forest, gradient boosting). Hybridization of soft voting with brute force algorithm has shown that the proposed hybrid ensemble model can find the optimal weights for the machine learning model in the context of predicting suicidal behavior. Furthermore, the proposed hybrid ensemble model shows that clinical data can be used to improve the performance of machine learning models in predicting an individual with suicidal behavior

Blended learning as a conduit for inquiry-based instruction, active learning, formative assessment and its impact on students’ learning outcomes in higher education

There is a definite impact of inquiry-based instruction, active learning and formative assessment on students’ learning outcomes because all of these factors have the tendency to drive student’s motivation, interest and performance in learning, especially when it is grounded in the use of the Blended Learning (BL) method. In view of this, the study attempted to identify the effect of these factor(s) on students’ learning outcomes such as self interest, self efficacy and cognitive development.This study employed a quantitative method and a 5 point Likert scale survey instrument was used to gauge the response from students at the Faculty of Education in a public university. A total of 500 questionnaires were distributed and about 80% were returned from 444 student respondents. BL based formative assessment was found to be a strong contributor to the variance in learning outcomes, in higher education. The study indicated that a student’s interest, cognitive development and self efficacy were influenced by many factors however, providing them with BL based active learning opportunities were extremely fruitful.In addition, inquiry based instruction and formative performance assessment are known as outstanding methods in recent years that have produced a shift in the focus of students’ attention particularly towards learning in tertiary institutions

The relationship between collaboration in learning, quantity and timing of feedback, and self-efficacy of students in higher education / Chan Yuen Fook … [et al.]

The purpose of this study was to identify the effect of collaboration in learning, and the quantity and timing of feedback towards the enhancement of self-efficacy among students in a public university in Malaysia. Data was collected using a survey questionnaire. The questionnaire was distributed to a total of 500 randomly selected tertiary students. A total of 475 questionnaires were returned and used for analysis. Data was analysed with both descriptive and inferential st atistics. The findings revealed that most of the students collaborate with peers in their learning. Feedback that was identified has a positive and significant relationship with student selfefficacy. A moderate, positive and significant correlation has been identified between collaboration in learning, quantity and timing of feedback and selfefficacy among the students in a public university. However, collaboration in learning and quantity and timing of feedback only induced a low effect size on self-efficacy