BME211: Applied Biomechanics Measurement and evaluation of the biomechanics of a specified human movement from a clinical perspective. Learning Outcomes:- Critically analyze the biomechanical components of selected activities. Evaluate the theory and relevant literature b

Measurement and evaluation of the biomechanics of a specified human movement from a clinical perspective.

Learning Outcomes:-

  • Critically analyze the biomechanical components of selected activities.
  • Evaluate the theory and relevant literature behind biomechanical measurement and instrumentation.
  • Collect and critically analyze experimental data using a range of measurement tools and evaluate their reliability and use.
  • Design and critique relevant research methods for biomechanical analysis of human movement.

In contrast to most peer-reviewed journal articles, the methods section of this report must include justification of the procedures and instrumentation used. A logical and comprehensive description of the protocol design is required. Reference should be made to the sample and equipment used, emphasizing calibration, accuracy, reliability, and validity of testers and tools. Data collection and processing should be described in detail; therefore, the method should easily be replicated in the future, if required. Data processing and statistical analysis is very important and integral part of the method. The selection of statistical tests must be appropriately justified. The presentation should enable a full understanding of research methodology from appropriately designed tables/figures with high-quality succinct written summaries.

Results This section will present the analyzed data. The text should be included to narrate the data presented in relevant figures, tables, and graphs. The selection of results should be in terms of meeting the study aims and objectives. The student should be selective and ensure that the key findings have been addressed. It is usual to present summary statistics first. These descriptive statistics will probably include relevant subject data, e.g. details of age, gender, and so on. Where tables of figures are presented, the student should ensure that each has a table heading and that the units of measurement are clearly indicated. Where inferential statistics are being used to test hypotheses, a clear rationale for the choice of test should be provided. It is rarely enough to simply conclude that the results are “significant” or otherwise.

The statistical significance needs to be described in terms of the hypothesis being tested. Complex data is best presented in a pictorial form, but not simply spread about the report without thinking. Where long and detailed findings are being presented, break up the results into clearly identifiable sub-sections. Students should not be tempted to start discussing the findings at this point and should consider the use of sub-headings to increase the clarity of the presentation. The student should ensure that tables and figures are clear, correct, and adequately labeled. Statistics are appropriate and correctly calculated and cited giving not only the test statistic but also the significance level