Md. Asraf Ali

Bio: Md. Asraf Ali is an academic researcher from Daffodil International University. The author has contributed to research in topics: Isometric exercise & Electromyography. The author has an hindex of 10, co-authored 32 publications receiving 249 citations. Previous affiliations of Md. Asraf Ali include Universiti Malaysia Perlis.

Mechanomyography Sensor Development, Related Signal Processing, and Applications: A Systematic Review

Abstract: Mechanomyography (MMG) is extensively used in the research of sensor development, signal processing, characterization of muscle activity, development of prosthesis and/or switch control, diagnosis of neuromuscular disorders, and as a medical rehabilitation tool. Despite much existing MMG research, there has been no systematic review of these. This paper aims to determine the current status of MMG in sensor development, related signal processing, and applications. Six electronic databases were extensively searched for potentially eligible studies published between 2003 and 2012. From a total of 175 citations, 119 were selected for full-text evaluation and 86 potential studies were identified for further analysis. This systematic review initially reveals that the development of accelerometers for MMG is still in the initial stage. Another important finding of this paper is that sensor placement location on muscles may influence the MMG signal. In addition, we observe that the majority of research processes MMG signals using wavelet transform. Time/frequency domain analysis of MMG signals provides useful information to examine muscle. In addition, we find that MMG may be applied to diagnose muscle conditions, to control prosthesis and/or switch devices, to assess muscle activities during exercises, to study motor unit activity, and to identify the type of muscle fiber. Finally, we find that the majority of the studies use accelerometers as sensors for MMG measurements. We also observe that currently MMG-based rehabilitation is still in a nascent stage. In conclusion, we recommend further improvements of MMG in the areas of sensor development, particularly on accelerometers, and signal processing aspects, as well as increasing future applications of the technique in prosthesis and/or switch control, clinical practices, and rehabilitation.

A review on crosstalk in myographic signals

Abstract: Crosstalk in myographic signals is a major hindrance to the understanding of local information related to individual muscle function. This review aims to analyse the problem of crosstalk in electromyography and mechanomyography. An initial search of the SCOPUS database using an appropriate set of keywords yielded 290 studies, and 59 potential studies were selected after all the records were screened using the eligibility criteria. This review on crosstalk revealed that signal contamination due to crosstalk remains a major challenge in the application of surface myography techniques. Various methods have been employed in previous studies to identify, quantify and reduce crosstalk in surface myographic signals. Although correlation-based methods for crosstalk quantification are easy to use, there is a possibility that co-contraction could be interpreted as crosstalk. High-definition EMG has emerged as a new technique that has been successfully applied to reduce crosstalk. The phenomenon of crosstalk needs to be investigated carefully because it depends on many factors related to muscle task and physiology. This review article not only provides a good summary of the literature on crosstalk in myographic signals but also discusses new directions related to techniques for crosstalk identification, quantification and reduction. The review also provides insights into muscle-related issues that impact crosstalk in myographic signals.

Cross-Talk in Mechanomyographic Signals from the Forearm Muscles during Sub-Maximal to Maximal Isometric Grip Force

Abstract: PURPOSE: This study aimed: i) to examine the relationship between the magnitude of cross-talk in mechanomyographic (MMG) signals generated by the extensor digitorum (ED), extensor carpi ulnaris (ECU), and flexor carpi ulnaris (FCU) muscles with the sub-maximal to maximal isometric grip force, and with the anthropometric parameters of the forearm, and ii) to quantify the distribution of the cross-talk in the MMG signal to determine if it appears due to the signal component of intramuscular pressure waves produced by the muscle fibers geometrical changes or due to the limb tremor. METHODS: Twenty, right-handed healthy men (mean ± SD: age = 26.7±3.83 y; height = 174.47±6.3 cm; mass = 72.79±14.36 kg) performed isometric muscle actions in 20% increment from 20% to 100% of the maximum voluntary isometric contraction (MVIC). During each muscle action, MMG signals generated by each muscle were detected using three separate accelerometers. The peak cross-correlations were used to quantify the cross-talk between two muscles. RESULTS: The magnitude of cross-talk in the MMG signals among the muscle groups ranged from, R2(x, y) = 2.45-62.28%. Linear regression analysis showed that the magnitude of cross-talk increased linearly (r2 = 0.857-0.90) with the levels of grip force for all the muscle groups. The amount of cross-talk showed weak positive and negative correlations (r2 = 0.016-0.216) with the circumference and length of the forearm respectively, between the muscles at 100% MVIC. The cross-talk values significantly differed among the MMG signals due to: limb tremor (MMGTF), slow firing motor unit fibers (MMGSF) and fast firing motor unit fibers (MMGFF) between the muscles at 100% MVIC (p<0.05, η2 = 0.47-0.80). SIGNIFICANCE: The results of this study may be used to improve our understanding of the mechanics of the forearm muscles during different levels of the grip force.

The Impact of Software Fault Prediction in Real-World Application: An Automated Approach for Software Engineering

Abstract: Software fault prediction and proneness has long been considered as a critical issue for the tech industry and software professionals. In the traditional techniques, it requires previous experience of faults or a faulty module while detecting the software faults inside an application. An automated software fault recovery models enable the software to significantly predict and recover software faults using machine learning techniques. Such ability of the feature makes the software to run more effectively and reduce the faults, time and cost. In this paper, we proposed a software defect predictive development models using machine learning techniques that can enable the software to continue its projected task. Moreover, we used different prominent evaluation benchmark to evaluate the model's performance such as ten-fold cross-validation techniques, precision, recall, specificity, f 1 measure, and accuracy. This study reports a significant classification performance of 98-100% using SVM on three defect datasets in terms of f1 measure. However, software practitioners and researchers can attain independent understanding from this study while selecting automated task for their intended application.

Gray's Anatomy

Abstract: MEDICAL LITERATURE has been deluged during the past few years with books and papers on penicillin; but a book which has been produced under the general editorship of Sir Alexander Fleming himself represents a complete and authoritative summary of penicillin therapy as it stands today.' The book contains a series of independent contributions by \"experienced and eminent men who have worked with penicillin in Great Britain\". Their opinions and practical methods differ slightly, and there is some overlapping; but these are not disadvantageous, comparison and contrast lending interest to the reading. In the first or general section of the book Fleming contributes two chapters, one on the history and development of penicillin, introducing some interesting sidelights in the romance of discovery, the other on the bacteriological control of penicillin therapy. In both chapters the information is set out in meticulous detail and with a clarity and simplicity which can be enjoyed by all readers. Fleming also gives the right perspective to the place of penicillin amongst the antibiotics and lays down the principles of treatment. Both chapters are well illustrated and are the most outstanding in the book. Included in this first section also are chapters on the chemistry and manufacture of penicillin and its pharmacy, pharmacology and methods of administration. The second section of the book is entirely clinical, giving each author's view on the use of penicillin therapy in a disease or an infection of some particular region of the body. The entire range of peniCillin-sensitive conditions is considered in twenty authoritative and clearly written chapters; these contain many references and illustrations. Dental and veterinary diseases are also given fairly full consideration. The final section is a condensed resume of much of the preceding chapters and is written for. the general practttioner. This chapter is superttuous: it does not contain enough detall to be of much practical value. The book as a Whole, however, will undoubtedly be considered a classical contribution to medical literature and is strongly recommended, not only because of the general interest of its topic, but as a reference book on penicillin therapy of hitherto unequalled excellence. The typography, although conforming to war economy standards, is clear and the paper is good. There is an excellent list of references and the index is satisfactory.

A Review on Technical and Clinical Impact of Microsoft Kinect on Physical Therapy and Rehabilitation

Abstract: This paper reviews technical and clinical impact of the Microsoft Kinect in physical therapy and rehabilitation. It covers the studies on patients with neurological disorders including stroke, Parkinson’s, cerebral palsy, and MS as well as the elderly patients. Search results in Pubmed and Google scholar reveal increasing interest in using Kinect in medical application. Relevant papers are reviewed and divided into three groups: (1) papers which evaluated Kinect’s accuracy and reliability, (2) papers which used Kinect for a rehabilitation system and provided clinical evaluation involving patients, and (3) papers which proposed a Kinect-based system for rehabilitation but fell short of providing clinical validation. At last, to serve as technical comparison to help future rehabilitation design other sensors similar to Kinect are reviewed.

Toward an Enhanced Human–Machine Interface for Upper-Limb Prosthesis Control With Combined EMG and NIRS Signals

Abstract: Advanced myoelectric prosthetic hands are currently limited due to the lack of sufficient signal sources on amputation residual muscles and inadequate real-time control performance. This paper presents a novel human–machine interface for prosthetic manipulation that combines the advantages of surface electromyography (EMG) and near-infrared spectroscopy (NIRS) to overcome the limitations of myoelectric control. Experiments including 13 able-bodied and three amputee subjects were carried out to evaluate both offline classification accuracy (CA) and online performance of the forearm motion recognition system based on three types of sensors (EMG-only, NIRS-only, and hybrid EMG-NIRS). The experimental results showed that both the offline CA and real-time performance for controlling a virtual prosthetic hand were significantly ( p $ 0.05) improved by combining EMG and NIRS. These findings suggest that fusion of EMG and NIRS is feasible to improve the control of upper-limb prostheses, without increasing the number of sensor nodes or complexity of signal processing. The outcomes of this study have great potential to promote the development of dexterous prosthetic hands for transradial amputees.

An eccentric- and concentric-strength profile of shoulder external and internal rotator muscles in professional baseball pitchers

Abstract: The purpose of this study was to establish a data base on the isokinetic eccentric muscular performance characteristics of external and internal rotator muscles in the shoulders of professional baseball pitchers. Concentric data are also included and compared with previously published concentric studies. Twenty-five professional baseball pitchers were evaluated with a Kin-Com isokinetic dynamometer. The subjects tested had a mean age of 23.5 years and a mean body weight of 199 pounds. Eccentric and concentric isokinetic tests were performed at 60 and 120 deg/sec. The testing protocol was standardized for each subject. Test results indicated no statistically significant difference in mean torque between throwing and nonthrowing shoulders for either external or internal rotator muscle groups. Eccentric strength was significantly greater than concentric strength for all muscle groups tested. The external-to-internal rotator muscle strength ratios were well above those previously published for high school through professional pitchers. Mean torque-to-lean body weight ratios were also included to establish a data base. This study establishes one of the first data bases for eccentric isokinetic muscle strength of shoulder rotator muscles in professional baseball pitchers. The data may help clinicians prevent and rehabilitate shoulder injuries in professional throwing athletes.

A Review of Force Myography Research and Development

Abstract: Information about limb movements can be used for monitoring physical activities or for human-machine-interface applications. In recent years, a technique called Force Myography (FMG) has gained ever-increasing traction among researchers to extract such information. FMG uses force sensors to register the variation of muscle stiffness patterns around a limb during different movements. Using machine learning algorithms, researchers are able to predict many different limb activities. This review paper presents state-of-art research and development on FMG technology in the past 20 years. It summarizes the research progress in both the hardware design and the signal processing techniques. It also discusses the challenges that need to be solved before FMG can be used in an everyday scenario. This paper aims to provide new insight into FMG technology and contribute to its advancement.