LOWER LIMB ANGULAR KINEMATICS AND HOW IT EFFECTS GAIT SPEED
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This study examined the relationship between lower limb angular kinematics and gait speed. The researcher measured peak knee flexion in the stance and swing phases and peak plantarflexion in a participant walking at various speeds. Results showed no significant correlation between knee flexion in stance and speed. However, there was a strong positive correlation between knee flexion in swing and speed, as well as between plantarflexion and speed. These findings support previous research indicating that knee flexion in swing and plantarflexion are important mechanisms for achieving higher gait velocities.
LOWER LIMB ANGULAR KINEMATICS AND HOW IT EFFECTS GAIT SPEED
- 1. LOWER LIMB ANGULAR KINEMATICS AND HOW IT EFFECTS GAIT SPEED John Joe Magee Applications in Sports Biomechanics, Ulster University, Jordanstown, Northern Ireland INTRODUCTION:In this lab we aim to discover the relationship between lower limb angular kinematics and gait speed. The main variables we will examine are the peak knee flex in both the stance and the swing phases of the Gait cycle and peak plantarflexion. Quantitative analysis of the gait cycle is a very important tool that can be used for quantifying patterns that exist within locomotion (Kadaba et al., 1990). Recent studies have suggested that knee flexion is directly related to gait speed, particularly in the swing phase (Kirtley et al., 1985). Peak knee flexion of up to 60-65% have been recorded. Plantarflexion was also seen as a key mechanism in achieving peak knee flexion and gait velocity (Nene et al., 1999). From a different point of view, limited knee flexion would in fact, negatively affect walking speed, thus once again proving the correlation that exists between the two variables (Cook et al., 1997). It is hopeful that our results will either back up this previous literature or challenge it. I strongly suspect that the results will follow the same trend as the previous literature. However, I do not expect to see any correlation between gait velocity and peak knee angle during the stance phase as it is not a known mechanism essential to speed in locomotion and has not been made reference to in any of the literature I have read. METHODS:A male (21 years old, 180cm, 72kg) with a background in hockey volunteered for the study. The only criteria for the participant was to be wearing tight fitting shorts as to try eliminate noise from the results. The participant was required to complete 10 walks at 5 different speeds; 2 attempts at each. Each of the speeds (very slow, slow, normal, fast, and very fast) were regulated using an app that produced a steady beat at a chosen frequency called Metronome. These were the selected speed requirements as they are the most frequent titles in related articles (Chow and Stokic, 2015) (Harris and Smith, 2007). The performer chose which frequency they felt was reflective of the title given. Each trial lasted 5 seconds with a 1 second static trial recorded as the control. The method for gathering and analysing the results are as follows: the first step is to set up coda. The version we used was CODAmotion CX1 V6.76-UU by Charnwood Dynamics. The setup included the alignment of the system (discovering x, y and z) and the selection of markers. Each marker has a number and these numbers will be key to the placement of the markers on the participant. The markers are to be placed on the following points of the lower extremity (right hand side): superior lateral aspect of greater trochanter, lateral femoral epicondyle, lateral malleolus, calcaneus and 5th metatarsophalangeal. These will be attached using double sided sticky tape. If number 4 is selected to be on the knee it is titled so on coda. This remains constant throughout the procedure. The frame rate used was 40Hz and an allowed time frame of 5 seconds for each speed. Once this has been set up, the data to be measured must be selected. To measure an angle there is a need of at least 3 points. To measure the knee angle, this includes the hip marker, the knee marker and the ankle marker. This is the first deliverable, the next is the ankle angle relative to the knee. The three points to select in this instance is the knee marker, the ankle marker, and the toe marker. Once each of the trails are recorded the toe off times are to be recorded. The data is then cut to 1 cycle and exported to Excel 2013 where it is normalised to the static values gathered in the 1 second trial and to 101 points. From this raw data we find the variables (Peak Knee Flexion during Swing Phase, Peak Knee Flexion during Stance Phase, Peak Plantarflexion). These variables will be correlated against the gait speeds for each trial. Excel was the used to
- 2. R² = 0.0303 0 5 10 15 20 25 30 35 40 0.00 0.50 1.00 1.50 2.00 2.50 Angle(Degrees) Velocity (m/s) Peak Knee Flexion (Stance) (Fig.1): Knee FlexionduringStance phase create graphs to find a correlation and an r² value, r<0.5 is seen as a poor correlation whereas anything fairly close to 1 is very strong. Statistical Package for Social Sciences (SPSS) version 22 was used to obtain the p value. A significance of p<0.05 is seen as acceptable. RESULTS AND DISCUSSION: When all the results were gathered and collated, it was found that no significant correlation was found between the Peak Knee Flexion during the Stance phase and the gait velocity. The Pearson exhibited poor results (0.173) and this is backed up by the Sig (2-tailed) value which is 0.633, as depicted in (fig.1). Considering that for two variables to be expressed as statistically significant to one another this value must be lower than 0.05, we can conclude that there is indeed no significant correlation. This result was to be expected as no previous literature derived at an alternate conclusion. Another reason that this particular outcome was predicted was that the stance phase of the gait cycle is almost completely stationary with very minimal movement which suggests that it could not have any effect on velocity. So regardless of what the knee flexion produces velocity will not be hindered nor enhanced by any significant amount. However, it should be mentioned that although there was no significant correlation between the two variables, a correlation did exist. This correlation is what would be described as a weak positive. Correlations Peak Knee Flexion (Stance) Gait Velocity Peak Knee Flexion (Stance) Pearson Correlation 1 .173 Sig. (2-tailed) .633 N 10 10 Gait Velocity Pearson Correlation .173 1 Sig. (2-tailed) .633 N 10 10
- 3. The next variable to be considered is the Knee Flexion during the Swing phase. As seen in (fig. 2), knee flexion during the swing phase has a significant correlation. The Pearson value reads as 0.846. This is seen as a strong positive correlation as the value is closest to 1. Positive correlation suggests that as on variable increases, as does the other. The Sig (2- tailed) value is 0.002. This value conveys the original assumption that the two variables are statistically significant. Unlike the stance phase, this result was highly expected as almost the entirety of the literature read, suggested that there was in fact a strong correlation existing (Kirtley et al. 1985). This phase is the necessary requirement to ensure sufficient foot clearance in order to swing the leg forward (Kerrigan et al., 2000). Naturally, it would then be considered as relative to gait velocity. The more clearance given to the foot, the larger the swing, the larger the swing the longer the stride. In turn, the longer the stride, the greater the gait speed. Both (Gage, 1990) and (Nene et al., 1999) have suggested that a minimal knee flexion of about 60% is required to provide sufficient clearance. This value is achieved by our participant when his velocity was at the normal speed or above (fig. 3). This suggests that the knee flexion has effected the velocity as when the flexion dropped well below the 60% mark, gait velocity was in the slow and very slow stages. Therefore, our research has proven what has been said by both authors and concluded that knee flexion is a key mechanism in gait speed. Correlations Gait Velocity Peak Knee Flexion (Swing) Gait Velocity Pearson Correlation 1 .846** Sig. (2-tailed) .002 N 10 10 Peak Knee Flexion (Swing) Pearson Correlation .846** 1 Sig. (2-tailed) .002 N 10 10 **. Correlation is significantatthe 0.01 level (2-tailed). Fig. 2: Peak knee flexion during Swing phase R² = 0.7159 0 10 20 30 40 50 60 70 0.00 0.50 1.00 1.50 2.00 2.50 Angle(degrees) Velocity (m/s) Peak Knee Flexion (Swing)
- 4. Speed Gait Velocity (m/s) Pk Knee Flex Swing Fast 2 1.52 58.7984 Fast 1.65 60.5032 Normal 2 0.93 57.1606 Normal 0.86 56.2448 Slow 2 0.65 51.424 Slow 0.61 53.32 Very Fast 2 2.08 59.668 Very Fast 1.82 60.4398 Very Slow 2 0.32 40.224 Very Slow 0.31 40.9886 Fig. 3: Peak Knee Flexion during Swing phase (Raw Data) The final variable to be discussed is the Peak Plantarflexion. Plantarflexion was expected to be strong correlated with gait velocity for a number of reasons. (Nene et al., 1999) described it as a key mechanism in gait velocity. The greater plantarflexion achieved, the longer the foot has to transfer energy to the front of the foot to generate a larger push off force. A larger push off force during the toe off phase provides greater acceleration (F=MA), which in turn leads to a greater velocity. The results gathered backs up this assumption immensely. The Pearson r value for peak plantarflexion was 0.936 (fig. 4), the greatest value of all the phases tested. This shows the strong positive correlation between plantarflexion and gait velocity. With a Sig (2-tailed) value of 0.000068, the plantarflexion phase is proven as extremely statistically significant in relation to gait velocity. Correlations Gait Velocity Peak Plantarflexion Gait Velocity Pearson Correlation 1 .936** Sig. (2-tailed) .000 N 10 10 Peak Plantarflexion Pearson Correlation .936** 1 Sig. (2-tailed) .000 N 10 10 **. Correlation is significantatthe 0.01 level (2-tailed). R² = 0.8749 0 10 20 30 40 0.00 0.50 1.00 1.50 2.00 2.50 Angle(degrees) Velocity (m/s) Peak Planterflexion Fig.4: PeakPlantarflexion
- 5. CHOW, J.W. & STOKIC,D. S.2015. Intersegmental coordinationscaleswithgaitspeedsimilarlyin menand women. Experimentalbrain research. COOK,T. M., FARRELL, K. P.,CAREY,I. A.,GIBBS, J. M. & WIGER, G. E. 1997. Effectsof restrictedknee flexionandwalkingspeedonthe vertical groundreactionforce duringgait. TheJournalof orthopaedicand sportsphysicaltherapy, 25,236-44. GAGE, J. R. 1990. Surgical treatmentof knee dysfunctionincerebral palsy. Clinicalorthopaedicsand related research,45-54. HARRIS,G. F. & SMITH, P.A. 2007. Foot and AnkleMotion Analysis:Clinical Treatmentand Technology,CRCPress. KADABA,M. P.,RAMAKRISHNAN,H.K.& WOOTTEN, M. E. 1990. Measurementof lowerextremity kinematicsduringlevelwalking. Journalof OrthopaedicResearch, 8,383-392. KERRIGAN,D. C.,CROCE, U. D., MARCIELLO, M. & RILEY, P.O. 2000. A refinedview of the determinantsof gait:Significance of heel rise. Archivesof PhysicalMedicineand Rehabilitation, 81, 1077-1080. KIRTLEY, C.,WHITTLE, M. W. & JEFFERSON,R.J. 1985. Influence of walkingspeedongaitparameters. Journalof Biomedical Engineering, 7, 282-288. NENE,A.,MAYAGOITIA,R. & VELTINK,P. 1999. Assessmentof rectusfemorisfunctionduringinitial swingphase. Gait& Posture, 9, 1-9.