The effectiveness of using Q1-Q2 angles comparing with SFI in walking analysis on Results Consistency
For decades, scholars have been using the sciatic function index (SFI) in walking analysis. The SFI is applicable in assessing the function of the nerve through footprints in the walking analysis. (1) In most studies, researchers have been using rat sciatic nerve model to explore the functional outcome. The methodology they depicted is used progressively by the specialists who manage neuroscience. It consolidates walk investigation and the transient and spatial relationship of one impression to another during walking. (2) The numerical estimation of the equation is named the SFI. This model of estimating useful recuperation has been utilized by various scholars with predictable results. The sciatic function index has received considerable attention from researchers in their studies focusing on walking analysis (1-4). The importance of walking analysis is based the medical application where peripheral nerve injury is associated with huge expenses and a long span of hospitalization. (1)
However, SFI is a questionable method since it is affected by several factors such as auto-mutilation, muscle contracture, and the speed that a rat walks. For example, Margiana et al. (1) argue that auto-mutilation and muscle contraction, as well as the speed of the rat walk, affect the accuracy of the SFI method. On the same note, evidence shows a strong correlation between SFI and Q1-Q4 angles allowing investigators to use the angles as predictors of walking functions. (3) Therefore, the current study explores the advantages and disadvantages of using Q1-Q2 angles comparing with SFI in walking analysis.
The current study employs a systematic review to explore the advantages and disadvantages of using Q1-Q2 angles comparing with SFI in walking analysis. According to the review of the literature, walking analysis has received considerable attention from scholars around the world. Therefore, a systematic literature review provided the much-needed platform for the comparison of the findings to show the effectiveness of using Q1-Q2 angles comparing with SFI in walking analysis.
The current study is based on secondary data from previously conducted studies. Therefore, the collection of data involved the review of relevant findings from previous studies. As part of data collection inclusion and exclusion criteria were applied to ensure uniformity of data, which, in turn, facilitated comparison. Also, the inclusion criteria ensured that only articles with relevant data were included.
Inclusion and Exclusion Criteria
Three inclusion criteria were used when identifying the most relevant data. First, only studies on SFI in the walking analysis were included. This facilitated the research by ensuring that data collected were relevant to the study. Second, only articles that focused on experiments involving rats were included. This criterion was crucial in ensuring uniformity where the outcomes on rats were compared to draw conclusive evidence. Thirdly, only peer-reviewed articles conducted later than the year 2000 were included. This criterion was meant to ensure relevance by availing updated findings.
Data Collection Procedure
As Figure 1 illustrates, the selection of articles was done in a four-step process in line with the inclusion criteria. The first step involved the identification of data from PROQUEST and other sources. This was followed by screening which was crucial in eliminating articles whose full-texts were not accessible. The next step focused on assessing the articles against the inclusion criteria to ensure that they meet all of them. Finally, the articles that met all the criteria were analyzed by focusing on common themes.
As Figure 1 shows, the analysis is based on findings from five studies that met all the inclusion criteria. A study by Margiana et al. (3) explored the correlation between the parameters used in walking analysis and the Q1-Q4 angles. The findings revealed a strong correlation between SFI and Q1-Q4 angles; thus, researchers can use the angles as predictors of walking functions. (3) As the need to understand Sciatic Nerve Injury increases in the medical field, there is a need to understand the merits and demerits of using Q1-Q2 angles.
Studies on peripheral nerve damage treatment fundamentally in the sciatic nerve, tibial nerve, and regular fibular nerve wounds for the most part use SFI to find the impact of treatment. Axotomy of sciatic nerve executed by complete transection at mid-thigh of rodents or mice is the most seasoned creature trial model of fringe nerve damage. (4) A specific parameter is expected to quantify the impact of treatment given. Institutionalized estimations ought to have the option to quantify what ought to be estimated and ought to be solid. Estimations can be performed utilizing certain instruments. Research instruments can be as a particular device or an exceptional instrument such as a poll or a specific instrument.
Table 1: Comparison between SFI and Q1-Q2 angles summary findings
SFI Q1-Q2 angles
SFI results are affected by muscle contracture and auto mutilation muscle contracture and auto mutilation do not affect the outcomes when this parameter is used
The way that the speed that a rat walks affects the results of SFI The way and speed does not affect the results when the angles are measured as the parameter.
The parameter presents varying results depending on various factors; for example, speed of walking and muscle contracture. The parameters presented consistent results that show the difference between a normal and pathological hind limp of a rat.
Can be used as the main parameter in walking analysis The angles can be used as references to compare normal and sciatic nerve injured hind limb; therefore, Can be used as an additional method for confirming the results of SFI
In summary, the systematic review provides crucial insights regarding the differences between Q1-Q2 angles and SFI in walking analysis. The findings show the benefits of using the angles compared to SFI. For example, SFI results are affected by muscle contracture and auto mutilation. This problem is not reported in the case of Q1-Q2 angles. Also, the way that a rat walks and the walking speed affect the results of SFI in walking analysis. In contrast, measuring Q1-Q2 angles gives a consistent outcome. Based on these findings, the former presents varying results depending on various factors while latter leads to consistent results that show the difference between a normal and pathological hind limp of a rat. However, the results show that SFI is still an effective parameter for walking analysis. Also, the findings show a strong positive correlation between Q1-Q2 angles and SFI. Therefore, the former can be applied as the main parameter in walking analysis while the latter can be used as references to compare normal and sciatic nerve injured hind limb. This makes the Q1-Q2 angles a promising parameter that can be used as an additional method for confirming the results of SFI.
The approval of sciatic nerve damage recuperation assessment estimations in rodents that are generally utilized has been addressed in all the studies reviewed in this systematic review. These scientists think about the impact of strong contracture, auto-mutilation, speed and course of strolling against SFI estimation results. Subsequently, an inquiry emerges on whether the created parameter is very reliable and has positive relationship between a few parameters. Hence, this exploration shows the many drawbacks associated with SFI and the important role that Q1-Q2 plays in supporting the model.
In summary, the systematic review provides crucial insights regarding models for walking analysis, their advantages, and disadvantage. First, the findings shows the merits of using Q1-Q2 angles to overcome the limitations and drawbacks associated with SFI in walking analysis. In particular, SFI results are affected by muscle contracture and auto mutilation, while the results of Q1-Q2 angles remain constant. Also, the way that a rat walks and the walking speed affect the results of SFI unlike the Q1-Q2 angles, which give a consistent outcome. Therefore, SFI presents varying results depending on various factors while Q1-Q2 angles presents results on the difference between a normal and pathological hind limp of a rat. Based on these findings, the former can be applied as the main parameter in walking analysis while the latter can be used as references to confirm the outcome. Although the overall topic of walking analysis is well-covered, there are limited findings regarding the Q1-Q4 angles and their significance in walking analysis. Therefore, studies are required to provide more primary data to make a systematic review a viable research approach to compare the findings.
Margiana R, Jusuf AA, Aman RA, Kurnia I. A new method in walking analysis using the angles around the midpoint between print length and toe spread by four different color footprints. Int J Sci: Basic Appl Res (IJSBAR). 2015;21(1):117...
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