Comparative Analysis of Walking Kinetics and Running Kinetics of Three Participants

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Comparative Analysis of Walking Kinetics and Running Kinetics of Three Participants

Summary

This is a study comparing the walking kinetics and running kinetics of three participants. Different components were measured for each participant; these were the forces from each foot acting on X, Y, and Z and the overall ground reaction force of the right limb and left limb.

Introduction

Walking requires the coordination of hundreds of muscles, each activated to a precise degree at a precise time. It is initiated by allowing the body to fall forward in an unstable position and then moving one leg forward to support (Vander, Sherman, and Luciano, 2001, p. 326). The gait cycle is a repetitive pattern that is not exclusive to steps or strides, it encompasses the whole ambulation and involves the total body, primarily the lower limbs however at faster speeds the more the body depends on the upper body and torso for propulsion, balance, and stability (Shultz SJ et al, 2005). The bodys center of gravity is also at play during walking and running as it moves laterally and vertically during gait which we see the influence of during the analysis of the data. Occasionally gait is disrupted with the higher levels of the motor control hierarchy that are necessary for voluntary overrides such as breaking stride or walking over uneven surfaces. The importance of the sensorimotor cortex is that small damage somewhere along the system can cause marked disturbances in the gait. Walking gait is recognized as six phases; heel strike, foot flat, mid-stance, heel off, toe off, and mid-swing. Shown in Figure 1.

The research objectives of the study were to discover the forces exerted by running and walking kinematics, to then draw similarities and comparisons of each participant and collectively. Show understanding of the VICON motion capture system and Kissler force plates. After data collection, analyze and export data to excel to be formatted for abstract use.

Methods

A total of 3 male participants voluntarily took part in the experimental study, aged 20-30 years, weighing between 68-93kg. Each participant had no recognized injury that may compromise gait. The study was conducted over four hours in the Biomechanics Laboratory, University of the West of Scotland, UK, the subjects were only required over one testing day and had a time slot so participated separately. The VICON MX Plug-in gait system used composed of 10 Vantage V8 cameras of 8 megapixels running at 2000htz, the floor was composed of 4 Kissler force plates and 1 Active Wand was used for calibration. To begin there was a subject node created based on the chosen template, in this instance it was walking gait and then running gait, there was a dynamic calibration walking whilst following a figure of 8 patterns with the wand in the air followed by setting the origin, or a static calibration, placing the wand in the center of the area and recording 0,0. Then ascertained participant anthropometric data and added subject measurements to the subject node, attached markers to the participant, capture a static trial to find zero for the participant and reconstructed markers, ran the static plug-in gait model, and calibrated a Vicon skeleton for the participant based on the chosen .vst file and then manually labeled the markers where there was then a dynamic trial captured, participants walked and ran up and down 3 times to ensure adequate data recording and clean strikes on the force plates. The 16 anatomical markers were placed at 8 points on each side beginning at the anterior superior iliac, the top of the sacrum, and laterally on the thigh, knee, tibia, ankle, and heel and toe.

Results and discussion

As seen in table 1 we can identify strong correlations through p values with all the data sets for both walking and running for all participants. We can identify that there are greater correlations in the Fy lateral axis for both walking and running for all three participants, and also no significant difference in Ground Reaction Forces (GRF) axis. Observing the Fx column from Table 1 the values for walking and subsequently running showing that although these also show no significant values in terms of between participants, and although weaker than the other axes described we can still see in the results in the fore and aft portion of the force plate data during running (P = 0.055) are more marginal during walking (P = 0.201). Further depth of results is located in the appendices.

Upon looking at the graphs shown as appendices E-J we see that the ground reaction force shows two force peaks and a valley in between, this can be described during the walking gait cycle as the heel strike and heel off portions, with the valley indicating mid-stance seen in figure 1. From these graphs, we can premise if a person is a significant heel striker or if it shows midfoot to forefoot strikers between the participants. Observing appendix E, participant A strikes high in terms of force with his heel and shows a sharper decrease toward the mid-stance showing an indication of a prominent heel strike, for both the left and right foot. Contrasting this to participant B we see an almost flattening line between peaks although still with a decrease showing he is also a heel striker but not as prominent as A and imparts onto the midstride (Williams, 1985). Participant B shows a middling between participants A and C but a sharper transition into the heel off force peak, a higher second peak has a probable explanation of propulsion as more force is associated with propulsion than with impact, thus indicating more power being generated (Williams, 1985). Using the data to compare between left and right foot any similarities that may occur in GRF may be noticeable, as when looking at participant B in appendix F we see that both feet are almost identical, bar a slightly higher recording of force during heel off phase in the left foot. An explanation of this could be a right-footed subject utilizing the left foot more for balance and stability during mid-swing so the center of mass in the individual shifts as the left side of his pelvis tilts downwards creating a more stable base for the right foot to lift from the ground. Or, that of the right foot being the dominant foot and having greater autonomous control of placement than the left, producing a more even weight distribution. With the data collected from all three participants, they record higher figures of force shown during the heel-off phase of the gait cycle. However, Participant A that he has a significantly higher force on his left foot heel strike in relation to his right which shows the biggest difference between all participants. Does this then show an indication of a hip drop, a unilateral weakness of the hip abductor, predominantly in the gluteal musculoskeletal makeup may lead to a compensation of the trunk and pelvis, and thus the center of mass is mostly on the stance leg? This would require further testing and analysis of the participant. Again, it is crucial to remember the entire body moves whilst walking, a weak link in the chain can have consequences on a persons gait and strike pattern.

Analyzing the graphs of running we notice similarities between participants B and C, Appendices I and J, in that we have an initial spike followed by a dip and further spike before dissipating in the toe-off phase of the running gait cycle. This initial spike could be explained by a toe strike before the weight is shifted onto the ball of the foot before lifting off again. Participant A in Appendix H, shows a more stable curve of force, landing more so onto the ball of his foot having a more fluid running efficiency. He also has a shorter strike time during the running gait recordings, showing on the graph slightly over 0.2 seconds and a greater flight time whereas participant B records an estimated 0.3 per foot strike and a shorter flight time between steps and participant C records a similar to B in strike time and flight time. Equally, the walking recordings of Fy show similar lateral foot rolling patterns during the strike from each foot of each participant as they ran with participants A and B differing in foot roll from C. The difference between gait and run cycle we notice is the time passed when completing, the data showing walking cycling recorded between 1.2 and 1.4 seconds whereas the run cycle shows 0.6 to 0.7 seconds, this is in corroboration with literature, also that the GR force is smaller in walking gait meaning the load on the participant or athlete is lower (Chan and Rudins, 1994). We also notice that there are two impact force phases of a step, compared to just one during the running gait, this explains why runners tend to have more injuries in comparison to walking as the shock abortion is much larger, placing more stress on the lower limb joints, and muscles as seen by the higher number of forces between running graphs than walking.

Conclusion

This collected data is useful and provides insight into the forces produced during walking and running whilst also evaluating gait. Although, this study group is limited to only three participants, to further develop this study it is suggested to include more population groups, including female participants and different age groups. Including differing sports groups to see any imbalance or similarities between gait cycles of walking and running. To balance all results between future participants the removal of footwear would be beneficial to standardize results. Despite the limited sample size, the analysis is useful to further understand walking and running kinematics, the differences, and similarities between individuals, and gain vital experience in using the highly technical VICON system.

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