Does heel height cause imbalance during sit-to-stand task: surface EMG perspective

© 2017 Naik, Al-Ani, Gobbo and Nguyen. The purpose of this study was to determine whether electromyography (EMG) muscle activities around the knee differ during sit-to-stand (STS) and returning task for females wearing shoes with different heel heights. Sixteen healthy young women (age = 25.2 ± 3.9 years, body mass index = 20.8 ± 2.7 kg/m2 ) participated in this study. Electromyography signals were recorded from the two muscles, vastus medialis (VM) and vastus lateralis (VL) that involve in the extension of knee. The participants wore shoes with five different heights, including 4, 6, 8, 10, and 12 cm. Surface electromyography (sEMG) data were acquired during STS and stand-to-sit-returning (STSR) tasks. The data was filtered using a fourth order Butterworth (band pass) filter of 20–450 Hz frequency range. For each heel height, we extracted median frequency (MDF) and root mean square (RMS) features to measure sEMG activities between VM and VL muscles. The experimental results (based on MDF and RMS-values) indicated that there is imbalance between vasti muscles for more elevated heels. The results are also quantified with statistical measures. The study findings suggest that there would be an increased likelihood of knee imbalance and fatigue with regular usage of high heel shoes (HHS) in women

Blind Source Separation Based Classification Scheme for Myoelectric Prosthesis Hand

For over three decades, researchers have been working on using surface electromyography (sEMG) as a means for amputees to use remaining muscles to control prosthetic limbs (Baker, Scheme, Englehart, Hutcinson, & Greger, 2010; Hamdi, Dweiri, Al-Abdallat, & Haneya, 2010; Kiguchi, Tanaka, & Fukuda, 2004). Most research in this domain has focused on using the muscles of the upper arms and shoulders to control the gross orientation and grasp of a low-degree-of-freedom prosthetic device for manipulating objects (Jacobsen & Jerard, 1974). Each measured upper arm muscle is typically mapped directly to one degree of freedom of the prosthetic. For example, tricep contraction could be used for rotation while bicep flexion might close or open the prosthetic. More recently, researchers have begun to look at the potential of using the forearm muscles in hand amputees to control a multi-fingered prosthetic hand. While we know of no fully functional hand prosthetic, this is clearly a promising new area of EMG research. One of the challenges for creating hand prosthetics is that there is not a trivial mapping of individual muscles to finger movements. Instead, many of the same muscles are used for several different fingers (Schieber, 1995)

Activity Index (AI) and extent of collaboration: a case study of rainwater harvesting literature with a scientometric overview

Rainwater harvesting research is being conducted in much wider perspectives from agriculture to using in house toilets. The study has assessed the research activity by different countries with the help of Activity Index (AI) and the collaboration and its impact. The SCOPUS publication records are made use of for the analysis of RWH research activities. The quality of the publications is analysed in terms of citations received to the papers and Spain has come on the top having 42 citations per paper. Cross-field relative activity in rainwater harvesting research is measured and it was interesting to note that among the leading countries conducting RWH research, a few developed countries are below world average of RWH activity. Out of the 141 countries which have at least one publication on RWH, 132 (94%) have at least one paper written in collaboration with other countries. US is the collaboration hub of many countries and the strength of collaboration of India, China, UK, Brazil is noteworthy. It was also found that there is a positive correlation between the collaboration strength and impact of papers. The results are relevant to know the relative of strength of different countries in RWH as well as boosting the collaboration among countries and researcher mobility

Analysis of Superconducting Fault Current Limiterin DC System with Renewable Energy Sources

Superconducting fault-current limiters (SFCLs) have been the subject of research and development for many years and offer an attractive solution to the problem of rising fault levels in electrical distribution systems.  SFCLs can greatly reduce fault currents and the damage at the point of fault, and help improve the stability of a power system. Superconducting fault-current limiters (SFCL) provide a  new efficient approach to the reliable handling of such  faults.(SCFLs) can be used for various nominal voltages and currents, and can  be  adapted  to  particular  limiting  characteristics  in  case  of  short  circuits. In this project, dc resistive type superconducting fault current limiter (SFCL) is presented. This SFCL is designed for the HVDC system. Uniform current and voltage sharing among the SFCL modules can be observed through contact resistance tests, dc flow-through tests, and ac flow-through tests. Results of tests show that each limiting module has good uniformity in higher current system. The proposed concept can be implemented using renewable energy sources.The results are presented by using Matlab/Simulink platform

Free vibration analysis of simply supported rectangular plates

In this paper, numerical analysis for free vibration of simply supported thin rectangular plates has been simulated using Ansys. The vibration of plate follows Kirchhoff plate theory. The natural frequency calculated using Ansys has been compared with Levy type solution results available in the literature. It is observed that the natural frequencies of the simply supported rectangular plate is in close agreement with exact solution results as reported in literature

Epilepsy attacks recognition based on 1D octal pattern, wavelet transform and EEG signals

Electroencephalogram (EEG) signals have been generally utilized for diagnostic systems. Nowadays artificial intelligence-based systems have been proposed to classify EEG signals to ease diagnosis process. However, machine learning models have generally been used deep learning based classification model to reach high classification accuracies. This work focuses classification epilepsy attacks using EEG signals with a lightweight and simple classification model. Hence, an automated EEG classification model is presented. The used phases of the presented automated EEG classification model are (i) multileveled feature generation using one-dimensional (1D) octal-pattern (OP) and discrete wavelet transform (DWT). Here, main feature generation function is the presented octal-pattern. DWT is employed for level creation. By employing DWT frequency coefficients of the EEG signal is obtained and octal-pattern generates texture features from raw EEG signal and wavelet coefficients. This DWT and octal-pattern based feature generator extracts 128 × 8 = 1024 (Octal-pattern generates 128 features from a signal, 8 signal are used in the feature generation 1 raw EEG and 7 wavelet low-pass filter coefficients). (ii) To select the most useful features, neighborhood component analysis (NCA) is deployed and 128 features are selected. (iii) The selected features are feed to k nearest neighborhood classifier. To test this model, an epilepsy seizure dataset is used and 96.0% accuracy is attained for five categories. The results clearly denoted the success of the presented octal-pattern based epilepsy classification model

Analysis of Superconducting Fault Current Limiterin DC System with Renewable Energy Sources

Superconducting fault-current limiters (SFCLs) have been the subject of research and development for many years and offer an attractive solution to the problem of rising fault levels in electrical distribution systems. SFCLs can greatly reduce fault currents and the damage at the point of fault, and help improve the stability of a power system. Superconducting fault-current limiters (SFCL) provide a new efficient approach to the reliable handling of such faults.(SCFLs) can be used for various nominal voltages and currents, and can be adapted to particular limiting characteristics in case of short circuits. In this project, dc resistive type superconducting fault current limiter (SFCL) is presented. This SFCL is designed for the HVDC system. Uniform current and voltage sharing among the SFCL modules can be observed through contact resistance tests, dc flow-through tests, and ac flow-through tests. Results of tests show that each limiting module has good uniformity in higher current system. The proposed concept can be implemented using renewable energy sources.The results are presented by using Matlab/Simulink platform