Biomechanics-sprint start kinematics repor
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Module SE571: Biomechanics of Sport and Exercise
Practical 1: Sprint Start Kinematics in Faster and Slower Sprinters
Additional Write-up Information
The practical 1 handout given out during the data collection practical session provided a very brief introduction to the sprint start topic area and information on collecting the kinematic data of a sprint start. This document contains some useful information to get you thinking about how best to interpret and present the data.
Firstly, it is essential that you carry out a thorough review of the literature related to the kinematics of sprinting. Your review of the literature should not only aid your understanding of what kinematic parameters have been investigated and the results and findings that have been reported, but also assist you in becoming familiar with the layout of biomechanical journal articles, particularly the manner in which the data is presented and discussed.
Probably the overriding principle related to the practical write-up is that you should base the content and style of each section of your write-up on what is typically found within biomechanical journal articles. Please note that an abstract is not required. In terms of presenting your results, it is important that you consider the best format to present the data. Use published literature as a guide towards the ideal formats to adopt for presentation of results and for the manner in which the results are discussed and the main aspects focussed upon.
Please note that for this practical the hip marker will be used to approximately represent the centre of mass (CM). Therefore when comparing the data collected to the literature, this practical will compare hip marker linear data to CM linear data within the literature. The term “block clearing” or similar is used within the literature, this practical did not use starting blocks, however, the term can still be used, which corresponds to the “instant” of front foot clearance.
Data for lab report
The data for the lab report will use data from a total of TWELVE (or more) subjects collated from different SE571 practical groups. The data for the other subjects will be provided on studentcentral > SE571 > Study Materials > Practicals > Practical 1 once collated. The sharing of data across practical groups will occur in order for practical groups to have sufficient subject numbers to aid the statistical testing of the results. Please note that subject names MUST NOT be used within the practical report, refer to subjects 1, 2, etc.
The Lab Report Data excel file will contain the collated subject data obtained during the practical which was entered into the Practical 1 excel file and e-mailed to s.h.mills@brighton.ac.uk The Lab Report Data excel file will also contain some simple formulae to automatically calculate the key kinematic parameters which have been discussed within the literature, e.g. block pushing time, range of ankle joint dorsi-flexion during first stance, flight and contact time of the first stance. It is recommended that you click on the cells in the calculated data columns to view the formulae, to assist you in creating these formulae in future biomechanical studies.
As stated above, use published literature as a guide towards the ideal formats to adopt for presentation of results and for the manner in which the results are discussed and the main aspects focussed upon. The following section briefly summarises the kinematic data presented in some sprint start articles.
Kinematic Data Presented within the Literature and Guidance for Your Report
Slawinski et al, 2010
Slawinski et al collected both kinematic and kinetic data, so focus only on the kinematic data. The excel files provided do not contain data for the “on your marks position”, so you are unable to present and discuss this data. Tables 3 – 7 are used to present their data for five different “critical instants”: “set position”, “pushing phase”, “block clearing”, “first step”, and “second step”. All tables list the mean and standard deviation (SD) data, as well as indicate with symbols which results are statistically significantly different (independent samples Student’s t-test) between the two groups of sprinters, i.e. statistically significantly different between the elite and well-trained.
Figure 5 presents the “horizontal position of center of mass (XCM) at 5 critical positions” within a format of a column chart. Highlighting a few of the key/most significant, kinematic parameters in figure/chart format is typical within biomechanics journal articles. Notice that the statistical significance is also indicated with the use of a * symbol representing p < 0.05. Figure 6 illustrates the “velocity of the centre of mass during the pushing phase and 2 first steps” with a velocity versus time graph. This particular graph displays the group mean and SD data for both sprinter groups at every time point. You are not able to present a graph for all sprinters as you do not have all of the exported linear data excel files for all sprinters. However, you are able to present a horizontal velocity of the hip marker (represents the CM) versus time graph for your one subject, by plotting a chart within excel using the exported linear “Hip Horizontal Velocity” data. Also indicate on your figure, as shown on figure 5, the different phases of the movement, i.e. pushing phase, flight and contact phase.
Coh et al, 2017
Coh et al also collected both kinematic and kinetic data, so again only focus on the kinematic data. This article presents all of the kinematic data for both groups of sprinters, i.e. faster and slower, within one table, this being table 2. Notice that they also present the actual t-test and p values, obtained from the independent samples (unpaired) Student’s t-test used to test for statistical significance for each parameter, as well as the Cohen’s d effect size. There is no need to calculate effect the effect size, but it is essential that you test for statistical significance using the independent samples (unpaired) Student’s t-test, and present the findings from the statistical test either adopting the format used by Coh et al, or alternatively using the symbols format used by Slawinski et al. Guidance on carrying out independent samples (unpaired) Student’s t-test (which was covered on module SE426) is provided within the additional information folder: studentcentral > Practical Folder > Practical 1.
To examine the relationships between the kinematic variables of the sprint start and sprinting performance, Spearman’s correlation coefficients were calculated and presented within Table 4. This table is referred to as a correlation matrix, where relationships between all variables are presented. Typically, the researcher is more interested in simply the relationship between the kinematic variables and the performance measure, i.e. the sprint time. You may therefore only wish to present the correlation coefficients between the kinematic variables and for your study the main performance measure being the time for the shoulder to reach 2.000 metres. Table 4 has the correlation coefficients presented separately for the faster and slower sprinters. This is one approach used, however, calculating the correlation coefficients for all sprinters, regardless of the sprinter’s group, is the more common approach, as used by Ciacci et al (2017, p1273) “linear regressions (correlations) were used to examine how performance (100m sprint time) affected each kinematic variable in the whole sample of 20 sprinters”. You may therefore wish to calculate the correlation coefficients for all of your subjects together, rather than for the two different groups of fast/slow subjects. Coh et al, don’t state why they used Spearman’s correlation coefficients, rather than the more commonly used Pearson Product correlation coefficient. It may have been due to the nature of their data, e.g. non-parametric data. Presenting either correlation coefficient will be fine, but the Pearson Product correlation coefficient is more common and is the statistical test which was covered on module SE426.
With regards to the correlation coefficients, due to the subject numbers being low, the level of statistical significance could likely be low, i.e. non-statistically significant p values. However, it is probably better to focus on the strength/size of the relationship as indicated by the r-value, adopting the same approach as Coh et al, (2017, p31) which refers to the relationship as “small r = 0.1 – 0.3”, “medium r = 0.3 – 0.5”, and “large r = 0.5 – 1.0”. Bezodis et al, 2015 (see below) defined the strength of the relationship using different criteria: “moderate r = 0.3 – 0.5”, “high r = 0.5 – 0.7”, “very high r = 0.7 – 0.9”, and “practically perfect r = 0.9 – 1.0”. These criteria provide more detail and are therefore probably preferable.
Similar to Slawinski et al above, figure 2 also presents the velocity of the centre of mass throughout the sprint within a velocity versus time graph. Notice the different phases are indicated within the graph, i.e. block phase both feet in contact (red), front foot pushing (blue), flight phase (thin black), and first step and second step contact phases (red then blue). As indicated above you can present your horizontal hip velocity data for your one subject within a velocity versus time graph, by plotting a chart within excel using the exported linear “Hip Horizontal Velocity” data.
Ciacci et al 2017
Although the specific focus of the study by Ciacci et al is on comparing male and female sprinters, the study is still useful in terms of identifying the kinematic parameters they investigated and the format they adopt to present their data. Unfortunately, much of their statistical analysis is a little advanced, however, in agreement with the two previous studies mentioned above they used independent-sample Student t-tests to compare the mean values of female versus male sprinters.
Table 2 presents all of the kinematic parameters within three columns: female mean (SD), male mean (SD) and the male-female difference (95% Confidence Interval), with statistical significance indicated with the # symbol. Adding the third column, i.e. the difference value between the two groups of data, helps convey the size of the difference. The # symbol indicates whether this difference is statistically significant so possibly there is no need to also present the confidence intervals.
Bezodis et al 2015
The specific focus of the study by Bezodis et al, (not the review article), is slightly different to the above studies in that they weren’t comparing data between two data sets, e.g. male versus female, or fast versus slow, but they were focussing on the examination of relationships between specific technique variables and their performance measure, which was external power production during the block phase. As we haven’t yet covered power within the SE571 lectures, we aren’t using power as a performance measure.
The main performance measure we are using is the time taken for the shoulder to reach 2.000 metres from the start line. Other performance measures have also been used within sprint start biomechanics literature, as highlighted by Bezodis et al, 2019. These include: horizontal centre of mass (CM) block clearance velocity, instantaneous CM velocity at a specific timing point e.g. at the 5 metre mark, and block acceleration. It is possible to consider relationships to more than one performance measure, therefore CM block clearance velocity, instantaneous CM velocity at the 2 metre mark, and block acceleration data is also provided within the Lab Report Data excel file. Although these three variables have been considered measures of sprint performance within the literature, they are also kinematic variables which can contribute to the main sprint performance measure. The relationship (r-value) of these three kinematic variables in relation to the time for the shoulder to reach 2.000 metres should therefore also be investigated, along with the relationships of the other kinematic variables you have collected to the performance measure(s) as explained below. (Apologies if this last paragraph is a bit confusing, it is just quite difficult to explain whilst trying to be concise!)
Table 1 presents all of the joint or segment kinematic data within the set position and during the block phase. In addition to the group mean and standard deviation data, also presented are the correlation coefficient values (r-values) for each kinematic variable related to their performance measure (block power). The table also contains other data e.g. ICC and 90% confidence intervals, however this level of statistical analysis was not covered during SE426 so you can ignore this data. Table 2 similarly presents the group mean and standard deviation data, and the correlation coefficient values (r-values) for each kinematic variable, but now for the first flight and stance phases.
Figure 1 contains graphs of the rear and front leg angular velocity versus time for the hip, knee and ankle joints. You will notice that along the x axis times is represented as % of Stance rather than the usual time (seconds). You may wish to present a similar figure of angular velocity versus time (seconds), but for your subject only, (exported angular data from Quintic), as an example subject to illustrate how angular velocity changes with time during a sprint start. Notice that within Figure 1, the correlation coefficient relating the peak angular velocity to their performance measure has been presented as this r-value was not presented in table 1 or 2 and may be a significant variable, especially for the hip joint with r values of 0.49 (moderate, nearly high) being reported.
Results and Discussion – Some suggestions on what to focus on
Looking carefully at the data within the Lab Report Data excel file, one has to decide upon what format is best to present this data and what data is appropriate to present, i.e. figure or table, and the layout of the tables/figures. Referring to the sprint literature provides guidance on the most important data to present and different presentation approaches used, as illustrated with the four studies summarised above. There is no ONE way of presenting data!
Refer back to the practical 1 handout to remind yourself of the focus of the practical. Therefore firstly there is a need to establish if there was a difference in sprint performance for the two different levels of sprint groups, i.e. faster and slower. You will need to test for statistical significance by carrying out an ‘Independent-Samples T-test’ for the performance variable(s). A Sig. (2-tailed) value less than .05 indicates that there is a difference in sprint performance at the two different group sprint levels. But it is also important to identify which kinematic variables also differ between the two different group sprint levels. You therefore also need to test for statistical significance for the key kinematic variables that have been presented in sprint kinematics literature.
As indicated above within three of the four studies summarised, it can also be useful to examine the relationships between the variables you have collected and the main sprint performance measure, i.e. the time for the shoulder to reach 2.000 metres. Although not evident within the four papers summarised above, sometimes significant relationships are illustrated with a scatter diagram. Consider whether this would be effective if you find any significant relationships between kinematic variables and sprint performance time. It is important that you consider the best format to present the data within the results section. Use published literature as a guide towards the ideal formats to adopt.
Practical Write-up
The write-up of this practical can be your assessed piece of work and contributes to 50% of your final grade for SE571. The alternative assessed practical write-up is practical 2. Note: The assessment submission deadline is 11:00am on the 30th of January 2020.
The word guide for the write-up of 1750 words does not include references, tables, and figures. The write-up is to be written in the style of a scientific academic journal article, except it does not include an abstract. Therefore, the write up should contain Introduction, Methods, Results, Discussion, and References. Base the content and style of each section of your write-up on what is typically found within biomechanical journal articles. Please note, an abstract is not required.
The introduction should inform the reader of the purpose of the research including the theoretical framework of the research. The method section should have sufficient detail to enable replication of the study, whilst at the same time written in a concise manner. The results section should lead the reader though the results with appropriate commentary to highlight the key findings. Results should be presented using a combination of figure, table and within text. Typically, only group mean (+ standard deviation) data is presented within the results. A time trace for the linear data of the CM or for angular kinematic data of various joints of one of the subjects is often also included within a results section. Scatter diagrams to illustrate relationships between variables and performance are also sometimes included, as are also sometimes included a Pearson’s correlation matrix/table. Use the most appropriate format to best illustrate your results.
The discussion should discuss your results, not simply be a repeat of your results. You should try to explain why the results occurred, and relate your findings to the theoretical framework and to previous literature. Refer to the literature on the kinematics and if appropriate the kinetics of the sprint start to develop your discussion, ensuring all literature referred to within the write-up is accurately referenced, using the Harvard referencing format, in your reference section. Include a reference section, NOT a bibliography. Therefore, all publications included in your reference section must be referred to within your practical write-up.
IMPORTANT FINAL GUIDANCE
Finally, the 1750-word laboratory practical report is an individual piece of work. The data collection and data analysis were carried out in sub groups. It is essential that all other aspects of the written report are completed individually. It is likely that students will read similar literature, but the introduction and discussion MUST be individually written. Similarly, although the method used by all students is identical, the methods section MUST be individually written. The data provided within the Lab Report Data excel file will be identical for all students within the Practical Group, however this data needs to be presented within the report within appropriate tables and figures. These tables and figures should be individually created and the commentary of the results MUST be individually written.
It is recommended that you do not e-mail draft reports to members of your sub-group. It is good practice to discuss the writing up of the laboratory practical report and to discuss the key findings of the literature review and of the results obtained within practical 1 with fellow students, but the write-up MUST be an individual piece of work.
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