Table of contentsIntroductionReadable of the articleScientific validity of the articleConclusion and recommendationA group of researchers discovered a way to detect fasciculation in muscles, which serves detect early signs of motor neuron disease (MND). ). The paper, Ultrasound-based detection of fasciculations in healthy and diseased muscles, was published by IEEE Xplore. This article has been peer-reviewed and can be found in Transactions on Biomedical Engineering or online, where they also publish other articles monthly. The intended audience for their article is other researchers, engineers and scientists, and even students who are looking for articles to analyze to complete their work. The four authors, Peter John Harding, Ian D. Loram, Nicholas Combes and Emma Hodson-Tole, live in the United Kingdom, where they all received their degrees. Harding is a member of the Cognitive and Motor Function Research Group at Manchester Metropolitan University, where he works with two of his co-authors, Loram and Hodson-Tole. Some of his academic interests include biomedical imaging, medical diagnostics, and computer optimization and parallelism. Additionally, he is a STEM Ambassador. Say no to plagiarism. Get a tailor-made essay on “Why violent video games should not be banned”? Get an original essay In addition to this article, he has made many other publications with other authors, such as gesture recognition based on mutual information and automated measurement of the human skeleton. Calf muscle contraction. Loram received his Ph.D. from the University of Birmingham and currently teaches neuromuscular control of human movement at Manchester Metropolitan University. His academic interests include optimizing human performance, fear of falling, stress and human performance, and muscle coordination and synergies. His research interests range from visual hand tracking, postural control, muscle proprioception, muscle and tendon interactions, and real-time muscle ultrasound. He was awarded the Leverhulme Early Career Fellowship in 2004 and was appointed Reader in Neuromuscular Control of Human Movement, Institute for Biomedical Research in Human Movement and Health. Hodson-Tole is a member of numerous professional associations, the editorial board, and received his Ph.D. in physiology and biomechanics of skeletal muscles. The Wellcome Trust awarded him a Sir Henry Wellcome Postdoctoral Fellowship. She is also principal investigator for two projects: MND diagnosis: utility of standard frame rate B-mode ultrasound imaging and models of imaging motor unit recruitment. His academic interests include the diagnosis of neurodegenerative diseases, the structure and function of motor units, and the spatial and temporal dynamics of skeletal muscle activation. Combes received his Bachelor of Medicine and Bachelor of Surgery degrees from the University of Birmingham and consults in neurophysiology at the Royal Preston Hospital.IntroductionMotor neuron disease (MND) is a neurodegenerative disease in which the motor neuron begins to die or become unstable, causing involuntary contractions known as fasciculation (Harding, 2016). The process of identifying these fasciculations is called electromyography (EMG). It involves inserting needles into several different places on the body, making the process invasive and painful. In addition, the electrodes detect these muscle movements in a small part of the muscles, which leads to inaccuracy of thedetector, which means that the practitioner risks “missing” the fasciculation (Harding, 2016). As an alternative, ultrasound (US) imaging has been proposed for the detection of MND. Ultrasound can evaluate multiple layers and areas of the skin and is very sensitive to movements as small as 5 micrometers (Harding, 2016). To prove this hypothesis, the article presents the process of collecting data collected in the United States on muscle fasciculation and compares these data to those extracted from EMG. The article's organization, diction, use of visuals and sentence structure contributed to the understanding of its content. Yet there are also sentence structure errors and repetitions that make for confusing reading. However, the validity of the methodology used showed that the experiment put real science into practice: measurement, formulation and modification of hypotheses. The methodology proved the author's thesis that ultrasound imaging allows for more accurate detection of fasciculation in MND. Readability of the article The article has strong points as well as weak points. First, analyze the organization of the content: the authors construct the article in chronological order, which is the best option for the article. It shows the steps of their experiment, what steps were followed, how the data was analyzed, etc. The article was divided into subsections, and these subsections were then divided into sections with subheadings. The subsections helped readers identify the steps of the experiment, while the subheadings added details to the steps. These subsections make it easy for readers to navigate the article because they know what each section is about. Second, the use of professional diction is adapted to the target audience: engineers, scientists and researchers. The article used words relating to their target audience such as “hypothesis”, “magnitude”, identified”, “accuracy” and “dataset”. Additionally, they gave enough details about the process and used precise words. The article gave very specific details about their experiment, such as the age, gender, and muscle health of their participants. To judge the quality of the experience, these details are important for readers' knowledge. The word "operator" was chosen instead of "machine" or "instrument", which specifies what type of equipment was used in the experiment. Additionally, the article used gender-neutral language. For example, in the sentence “To assess the accuracy and level of agreement between operators, operator ratings were combined in several ways” (Harding, 2016), no gender role was imposed on the operator. 'object. Thus, the operator was not sexualized. Third, using visuals helps readers understand content more clearly; they used colors effectively, chose appropriate graphics, and created effective tables. Since the experiment compares two muscle areas between two different types of muscles (healthy and diseased), the article used line graphs to help readers visualize the data. As shown below, two line graphs are shown to compare the data from the two muscles tested in the experiment. The location of the graphs shows the visible difference between the data. Legends and colors also help readers identify data on graphs. In addition to line graphs, tables were created to display the data, which also made for an effective visual. As shown in Figure 2, the data between different muscle areas and their health status is displayed digitally. Unlike the.