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SCIENCE LAB REPORT ON A 2D VIDEO & FORCE ANALYSIS OF THE EFFECTS OF SHOES ON RUNNING

MSPMD1BSE: Introduction to Biomechanics in Sport and Exercise

 

SCIENCE LAB REPORT ON A 2D VIDEO & FORCE ANALYSIS OF THE EFFECTS OF SHOES ON RUNNING

 

WORD COUNT: (2481 Words)

 

Abstract

Biomechanical analysis use in physiological systems modelling has in the recent past become quite popular. This is mainly because it enables investigation of activities of man while in motion as well as recording of the entire body’s and/or its segments’ motions, especially during exercise or sports. The aim of this practical was to demonstrate the correct methodology for the set-up of a 2D video and ground reaction force analysis of a sporting movement, and collect 2D video and ground reaction force data on athletes to determine whether there was significant difference in Loading Rate (load_rate) and Impact Forces Peaks (ifp) experienced in barefoot and shod trial conditions.

The findings of this practical show significance values in the Shapiro-Wilks normality tests for Loading Rate (load_rate) and Impact Forces Peaks (ifp) on both sprint trials (i.e. barefoot and shod) are above 0.05, an indication of normally distributed and parametric data for the two shoe conditions i.e. barefoot and shod trials. This implies that Paired Samples T-Test was used. However, the Paired Difference of the Mean between the two variables is -74.959, which suggests that ifp_bf was greater than load-rate 74.956 N.  Again, the statistics demonstrates that the Paired Difference of the Mean is empirically significant given that the Pearson and probability value is less than 5%.  Implicitly, respondents experienced a significantly greater Impact Force Peaks abbreviated as (IFP) in the barefoot (BF) running circumstances (M=76.18 N, 10.979) than the load-rate barefoot condition (M=1.22 N, 0.098), t (9) = -21.984, p= 0.000.

In conclusion, the load_rate and ifp data for both barefoot and shod shoe conditions is normally distributed and parametric, but ifp data for both conditions is significantly greater than that of load_rate. These findings are important in sports kinesiology analysis and biomechanical modelling. However, due to time limitation encountered during the practical sufficient time should be allocated when carrying out these kinds of research.

Introduction

Biomechanical analysis use in physiological systems modelling in sports has in the recent past become quite popular. This is mainly because biomechanical modelling and analysis is used in the investigation of activities of man while in motion while at the same time requiring recording of the entire body’s and/or its segments’ motions (Watkins, 2007). Therefore, biomechanics have been a key pillar to kinesiology analysis hence making it quite important to devise more improved methods and techniques for recording and quantifying human movement. Thus, kinesiology is mostly involved in the human kinetics in order to human movements, especially in sports. According to Payton and Bartlett (2008) kinesiology and biomechanics are essential addressing mechanical, physiological, and psychological mechanisms of the human body. Hence, the sports field has found immense applications of kinesiology and biomechanics not only to sport and exercise, but also to physical and occupational therapy (Whittle, 2003; Fellin, Manal and Davis, 2010). Among the most crucial methods and techniques that have been used in the study of biomechanics involve force analysis as well as 2D and 3D video analysis.

The history of motion analysis traces its roots from the Ancient Egyptians and Greeks where the analysis was conducted using the eye. However, technical advances have significantly improved this field including the invention of photography by Daquerre in 1839 which was used in the study of human and animal motion by Eadweard Muybridge in 1878 (Sasaki and Neptune, 2006). Moreover, cine film (series of stills taken at regular intervals) invented by Eddison in 1880 was another crucial invention that improved motion analysis, especially in the qualitative analysis of sporting movement in 1930s. Furthermore, the invention of computers in the1960s and ‘70s led to a rapid development in motion analysis (Novacheck, 1998).

However, there has also been an importance in recording human movements which facilitates detailed study of the movement pattern. It has also addressed the difficulty encountered in the observation of high-speed events mainly through slow speed recording in a frame by frame sequence (Fellin, Manal and Davis, 2010). Moreover, it also has the benefit of enabling permanent recording of performance through qualitative technique analysis in order to allow early performance versus progress evaluation. Additionally, motion analysis techniques ensure that there is minimal disturbance to performer in case of competitive events as well as significantly reducing the number of trials needed (Whittle, 2003).

Furthermore, biomechanics through various motion analysis methods and techniques such as force analysis and 2D analysis considered in this practical offer a number of benefits such as: enabling detailed study of the movement pattern; ability to transfer to detailed kinematic analysis; time and displacement measures; joint angles; quantitative analysis; inter and intra subject comparison; and also can calculate kinetic parameters and inverse dynamics using force data (Sasaki and Neptune, 2006). This implies that such studies are aimed at obtaining a record which enables an accurate measurement of the position vector of the centre of rotation of each of the moving body segments and the time lapse between successive pictures (Payton and Bartlett, 2008).

Aim

The aim of this practical was to demonstrate the correct methodology for the set-up of a 2D video and ground reaction force analysis of a sporting movement, and collect 2D video and ground reaction force data on athletes to determine whether there was significant difference in Loading Rate (load_rate) and Impact Forces Peaks (ifp) experienced in barefoot and shod trial conditions.

Objectives

To video subjects performing 3 short indoor runs of moderate pace, barefoot and shod, and to record, using timing lights, the intermediate and total time taken to complete each run.

To record the mediolateral (Fx), anteroposterior (Fy), and vertical (Fz) components of the ground reaction force (GRF) acting on a runner during the stance phase of moderate pace running barefoot and shod.

Method

Requirements

During the practical the following equipments were used: Monark cycle ergometers (Model 814E, Monark Exercise AB, Sweden); Timing Lights (in house, Canterbury Christ Church University) – placed 10 m apart; Stadiometer (Model 220, Seca Gmbh, Germany) – to measure mass and height; Digital Video Camera (Exilim EX-FH100, Casio Computer Co. Ltd., Tokyo, Japan) – sample rate 120 Hz, shutter speed 1/500 s; Spot lights (Double Tripod Site Light, 400W, Screwfix, UK); Tripod (SLIK Master, SLIK PRO 330 DX, SLIK); Metre ruler (Invicta, England); 19mm retro-reflective markers (in house, Canterbury Christ Church University); BioWare software (v5.0.3.0, Kistler Instruments Ltd, Switzerland); Piezoelectric Force Platform (Kistler, Model 9287BA, Kistler Instruments Ltd, Switzerland); and Quintic Biomechanics software (v17, Quintic Consultancy Ltd., UK).

Procedure

Subject preparation

  • A normal setting was provided for the subjects and it was ensured that the subject understood clearly what was expected of them (for the familiarisation of the subjects with the motion).
  • It was also ensured that the subject had the opportunity to warm up as well as making sure that the practical subjects wore suitable/minimal clothing.
  • Contrasting markers were positioned to show segment endpoints and axes of rotation.

Camera Setup 

  • A rigid camera support (tripod) was provided in addition to ensuring that the camera was level (spirit level on tripod was used).
  • A camera was positioned at centre of action, at height of subject of interest (in order to reduce obliquity error), the position of camera was ensured to be as far back as possible and zoomed in (to minimise parallex error).
  • Subjects images that were as large as possible were but with the field of view to accommodate complete movement pattern (increased focal length) followed by selection of the appropriate shutter speed (higher/shutter open for short time for fast motion, but more light required, min of 1/250s).

Laboratory Preparation

  • A plain, uncluttered background was used that was non-shiny and in contrast with the subject.
  • The plane of movement was held at perpendicular to the optical axis of the camera (3, 4, 5 triangle).
  • A vertical and horizontal reference (plumbline) was located in the field of view and a reference scale (e.g. meter rule) in the plane of motion and film for a few frames.
  • Each sequence was labelled with suitable information such as the date, group, subject, condition, and trial number

Actual Practical Procedure

  • The students were put in groups of 4 or 5, followed by recording of the subject’s information, mass and height (with and without shoes), and it was ensured that the subjects warmed up on the stationary bike as well as performing the necessary stretching.
  • The markers were attached at joint centres for the right shoulder, hip, knee, ankle using the guidelines provided.
  • The subjects were then allowed to stand behind the start line and upon instructions, then run through the timing lights barefooted, ensuring that the force platform was contacted with the right foot only at a velocity between 3.5 – 4.5 m.s-1, ensuring that the same pace was maintained by the subjects throughout the trial.
  • Upon completion, the subjects repeated the same process in the shod condition, in three successful shod trials. Intermediate and total time taken was recorded for all trials.

After the necessary data was collected from the practical subjects, the raw data was subjected to Quintic Biomechanics and Bioware Software Analysis, Excel Analysis and SPSS Software Analysis and the results are presented in the subsequent parts of this laboratory report.

 

 

 

 

 

 

 

Results

Table1: Practical Results

Table 1 above presents the overall data collected during the practical session and after subjecting it to Quintic Biomechanic and Bioware software as well as Excel analysis. Moreover, the above indicate some description of the data, but descriptive statistics are in the appendix. This data was then subjected to SPSS analysis in order to make sure that the meaning of the data was determined. This was essential since it enabled comparisons to be made between the two data sets obtained between the two sprint trials i.e. barefoot trials and shod trials. However, the data presented in the above table was collected from ten (10) subjects only.

Table 2: Average Distance-time for all sprint trials

Figure 1: Average Distance-time for all sprint trials

 

Table 2 and Figure 1 above show that the average step distance made by the practical subjects progressively increased with time in all the trials. For instance, it is evident that in all the barefoot trials (i.e. BF1, BF2 and BF3) as well as all shod trials (i.e. SH1, SH2 and SH3) the step distance in meters made after 10 minutes was generally bigger than that made after 5 minutes.
Table 3: Test of Normality

Tests of Normalityb,c
Kolmogorov-Smirnova Shapiro-Wilk
Statistic df Sig. Statistic df Sig.
load_rate_bf .245 10 .092 .918 10 .342
Ifp_bf .216 10 .200* .942 10 .577
rtd_knee_bf .107 10 .200* .979 10 .958
rtd_hip_bf .211 10 .200* .884 10 .145
step_length_bf .197 10 .200* .927 10 .414
rom_stance_knee_bf .168 10 .200* .918 10 .338
rom_swing_knee_bf .174 10 .200* .952 10 .691
rom_stance_hip_bf .139 10 .200* .957 10 .756
rom_swing_hip_bf .193 10 .200* .908 10 .269
load_rate_shod .156 10 .200* .922 10 .371
ifp_shod .216 10 .200* .942 10 .577
rtd_knee_shod .232 10 .135 .936 10 .512
rtd_hip_shod .215 10 .200* .925 10 .398
step_length_shod .263 10 .048 .789 10 .011
rom_stance_knee_shod .214 10 .200* .926 10 .411
rom_swing_knee_shod .223 10 .173 .945 10 .610
rom_stance_hip_shod .182 10 .200* .947 10 .630
rom_swing_hip_shod .188 10 .200* .917 10 .330
  1. Lilliefors Significance Correction
*. This is a lower bound of the true significance.
  1. contact_ time_bf is constant. It has been omitted.
  2. contact_time_shod is constant. It has been omitted.

 

The significance values from the Shapiro-Wilks test of the Loading Rate (load_rate) and Impact Force Peaks (ifp) of both barefoot and shod trials are above 0.05; this suggests that the data is normally distributed and parametric. This therefore indicates that there’s no significant difference between Loading Rate (load_rate) and Impact Force Peaks (ifp) experienced in the two shoe conditions i.e. barefoot and shod trials. Thus, a Paired Samples T-test was used to determine if there is a significant difference between the Loading Rate (load_rate) and Impact Force Peaks (ifp) experienced in the two shoe conditions.

Table 4, 5&6: T-test Analysis

 

Paired Samples Statistics
Mean N Std. Deviation Std. Error Mean
Pair 1 load_rate_bf 1.22 10 .098 .031
Ifp_bf 76.18 10 10.797 3.414

 

 

Paired Samples Correlations
N Correlation Sig.
Pair 1 load_rate_bf & Ifp_bf 10 .151 .678

 

 

Paired Samples Test
Paired Differences t df Sig. (2-tailed)
Mean Std. Deviation Std. Error Mean 95% Confidence Interval of the Difference
Lower Upper
Pair 1 load_rate_bf – Ifp_bf -74.959 10.782 3.410 -82.672 -67.246 -21.984 9 .000

 

 

Discussion

Since the research question was to determine whether there was significant difference between Loading Rate (load_rate) and Impact Force Peaks (ifp) in barefoot and shod trials using both Force and 2D Video analysis, the research findings obtained confirms the difference. For instance, considering the data analysis output from various analysis techniques adopted in this research, it is evident that the Loading Rate (load_rate) and Impact Force Peaks (ifp) data for each of the two shoe conditions is varied even though the differences were not significant. For example, the Excel analysis shown in Table 2 and Figure 1 showing the average step distance recorded from practical subjects indicates that there was a progressive increase with time in all the sprint trials both in barefoot and shod i.e. BF1, BF2, BF3, SH1, SH2 and SH3. The significance values in the Shapiro-Wilks normality tests for Loading Rate (load_rate) and Impact Forces Peaks (ifp) on both sprint trials (i.e. barefoot and shod) are above 0.05; this suggests a normally distributed and parametric data. This therefore indicates that there is no significant difference between Loading Rate (load_rate) experienced in the two shoe conditions i.e. barefoot and shod trials as well as those experienced in the Impact Force Peaks (ifp).

Moreover, the Paired Difference of the Mean between the two variables is -74.959, which suggests that ifp_bf was greater than load-rate 74.956 N.  Again, the statistics demonstrates that the Paired Difference of the Mean is empirically significant given that the Pearson and probability value is less than 5%.  Implicitly, respondents experienced a significantly greater Impact Force Peaks abbreviated as (IFP) in the barefoot (BF) running circumstances (M=76.18 N, 10.979) than the load-rate barefoot condition (M=1.22 N, 0.098),                         t (9) = -21.984, p= 0.000.

However, during the research lack of sufficient time to finalize with all procedures in the laboratory practical was a major limitation. Also lack of cooperation among all group members was another limitation. Therefore, it is recommended that adequate time be allocated to all procedures and the group members be reduced to a maximum of three in order to ensure all of the take part in the practical through active participation.

 

 

Conclusion

The load_rate and ifp data for both barefoot and shod shoe conditions is normally distributed and parametric, but ifp data for both conditions is significantly greater than that of load_rate. These findings are important in sports kinesiology analysis and biomechanical modelling. However, sufficient time should be allocated when carrying out these kinds of research.

 

References

Fellin, R. E., Manal, K. and Davis, I. S. (2010) “Comparison of Lower Extremity Kinematic Curves during Overground and Treadmill Running”, Journal of Applied Biomechanics, 26, pp. 407-414.

Novacheck, T. F. (1998) “The biomechanics of running”, Gait & Posture, 7, pp. 77-95.

Payton, C. and Bartlett, R. (2008) Biomechanical Analysis of Movement in Sport and Exercise.  Leeds, UK: British Association of Sport and Exercise Sciences.

Sasaki, K. and Neptune, R.R. (2006) “Differences in muscle function during walking and running at the same speed”, Journal of Biomechanics, 39, pp. 2005–2013.

Watkins, J. (2007) An Introduction to Biomechanics of Sport and Exercise.  Philadelphia, PA: Churchill Livingstone Elsevier Ltd.

Whittle, M.W. (2003) Gait Analysis: An introduction, 3rd edition. Edinburgh, UK: Butterworth Heinemann.

 

 

 

 

 


Appendices

Table 1: Descriptive Analysis

 

Descriptivesa,b
Statistic Std. Error
load_rate_bf Mean 1.22 .031
95% Confidence Interval for Mean Lower Bound 1.15
Upper Bound 1.29
5% Trimmed Mean 1.22
Median 1.20
Variance .010
Std. Deviation .098
Minimum 1
Maximum 1
Range 0
Interquartile Range 0
Skewness .717 .687
Kurtosis -.061 1.334
Ifp_bf Mean 76.18 3.414
95% Confidence Interval for Mean Lower Bound 68.46
Upper Bound 83.90
5% Trimmed Mean 76.14
Median 74.00
Variance 116.568
Std. Deviation 10.797
Minimum 60
Maximum 93
Range 33
Interquartile Range 19
Skewness .188 .687
Kurtosis -1.209 1.334
rtd_knee_bf Mean 50.70 .943
95% Confidence Interval for Mean Lower Bound 48.57
Upper Bound 52.83
5% Trimmed Mean 50.78
Median 50.50
Variance 8.900
Std. Deviation 2.983
Minimum 45
Maximum 55
Range 10
Interquartile Range 5
Skewness -.422 .687
Kurtosis .094 1.334
rtd_hip_bf Mean 63.40 .670
95% Confidence Interval for Mean Lower Bound 61.88
Upper Bound 64.92
5% Trimmed Mean 63.44
Median 64.00
Variance 4.489
Std. Deviation 2.119
Minimum 60
Maximum 66
Range 6
Interquartile Range 4
Skewness -.747 .687
Kurtosis -.692 1.334
step_length_bf Mean 1.25 .038
95% Confidence Interval for Mean Lower Bound 1.17
Upper Bound 1.34
5% Trimmed Mean 1.25
Median 1.23
Variance .014
Std. Deviation .120
Minimum 1
Maximum 1
Range 0
Interquartile Range 0
Skewness .561 .687
Kurtosis -.867 1.334
rom_stance_knee_bf Mean 52.40 .562
95% Confidence Interval for Mean Lower Bound 51.13
Upper Bound 53.67
5% Trimmed Mean 52.39
Median 52.50
Variance 3.156
Std. Deviation 1.776
Minimum 50
Maximum 55
Range 5
Interquartile Range 3
Skewness .131 .687
Kurtosis -.788 1.334
rom_swing_knee_bf Mean 55.90 .379
95% Confidence Interval for Mean Lower Bound 55.04
Upper Bound 56.76
5% Trimmed Mean 55.89
Median 56.00
Variance 1.433
Std. Deviation 1.197
Minimum 54
Maximum 58
Range 4
Interquartile Range 2
Skewness .233 .687
Kurtosis -.369 1.334
rom_stance_hip_bf Mean 65.50 1.025
95% Confidence Interval for Mean Lower Bound 63.18
Upper Bound 67.82
5% Trimmed Mean 65.56
Median 65.50
Variance 10.500
Std. Deviation 3.240
Minimum 60
Maximum 70
Range 10
Interquartile Range 5
Skewness -.441 .687
Kurtosis -.509 1.334
rom_swing_hip_bf Mean 68.80 .929
95% Confidence Interval for Mean Lower Bound 66.70
Upper Bound 70.90
5% Trimmed Mean 68.94
Median 69.50
Variance 8.622
Std. Deviation 2.936
Minimum 63
Maximum 72
Range 9
Interquartile Range 4
Skewness -.940 .687
Kurtosis .294 1.334
load_rate_shod Mean 1.21 .046
95% Confidence Interval for Mean Lower Bound 1.10
Upper Bound 1.31
5% Trimmed Mean 1.21
Median 1.18
Variance .022
Std. Deviation .147
Minimum 1
Maximum 1
Range 0
Interquartile Range 0
Skewness .125 .687
Kurtosis -1.319 1.334
ifp_shod Mean 76.18 3.414
95% Confidence Interval for Mean Lower Bound 68.46
Upper Bound 83.90
5% Trimmed Mean 76.14
Median 74.00
Variance 116.568
Std. Deviation 10.797
Minimum 60
Maximum 93
Range 33
Interquartile Range 19
Skewness .188 .687
Kurtosis -1.209 1.334
rtd_knee_shod Mean 55.20 .786
95% Confidence Interval for Mean Lower Bound 53.42
Upper Bound 56.98
5% Trimmed Mean 55.11
Median 55.00
Variance 6.178
Std. Deviation 2.486
Minimum 52
Maximum 60
Range 8
Interquartile Range 4
Skewness .747 .687
Kurtosis -.013 1.334
rtd_hip_shod Mean 62.50 .543
95% Confidence Interval for Mean Lower Bound 61.27
Upper Bound 63.73
5% Trimmed Mean 62.50
Median 62.00
Variance 2.944
Std. Deviation 1.716
Minimum 60
Maximum 65
Range 5
Interquartile Range 3
Skewness .330 .687
Kurtosis -1.001 1.334
step_length_shod Mean 2.416000 .0481941
95% Confidence Interval for Mean Lower Bound 2.306977
Upper Bound 2.525023
5% Trimmed Mean 2.404444
Median 2.355000
Variance .023
Std. Deviation .1524030
Minimum 2.2800
Maximum 2.7600
Range .4800
Interquartile Range .1575
Skewness 1.665 .687
Kurtosis 2.152 1.334
rom_stance_knee_shod Mean 61.60 .897
95% Confidence Interval for Mean Lower Bound 59.57
Upper Bound 63.63
5% Trimmed Mean 61.50
Median 60.50
Variance 8.044
Std. Deviation 2.836
Minimum 58
Maximum 67
Range 9
Interquartile Range 4
Skewness .764 .687
Kurtosis -.208 1.334
rom_swing_knee_shod Mean 75.20 1.104
95% Confidence Interval for Mean Lower Bound 72.70
Upper Bound 77.70
5% Trimmed Mean 75.17
Median 74.50
Variance 12.178
Std. Deviation 3.490
Minimum 70
Maximum 81
Range 11
Interquartile Range 6
Skewness .458 .687
Kurtosis -.531 1.334
rom_stance_hip_shod Mean 71.10 .737
95% Confidence Interval for Mean Lower Bound 69.43
Upper Bound 72.77
5% Trimmed Mean 71.06
Median 70.50
Variance 5.433
Std. Deviation 2.331
Minimum 68
Maximum 75
Range 7
Interquartile Range 4
Skewness .442 .687
Kurtosis -1.013 1.334
rom_swing_hip_shod Mean 81.90 1.027
95% Confidence Interval for Mean Lower Bound 79.58
Upper Bound 84.22
5% Trimmed Mean 81.83
Median 82.00
Variance 10.544
Std. Deviation 3.247
Minimum 78
Maximum 87
Range 9
Interquartile Range 7
Skewness .331 .687
Kurtosis -1.203 1.334
  1. contact_ time_bf is constant. It has been omitted.
  2. contact_time_shod is constant. It has been omitted.

 

 

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