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Article summary:

1. Gait analysis refers to the measurement of movement patterns in walking and associated interpretation.

2. The state of the art of optical systems for measuring retro-reflective markers on skin is advanced, but compensating for soft tissue movement remains a challenge.

3. Subject-specific models incorporating 3D imaging data of musculo-skeletal anatomy with kinematic and kinetic data offer promise for clinical applications of gait analysis.

Article analysis:

The article "Gait analysis methods in rehabilitation" provides an overview of the current state of gait analysis in clinical rehabilitation. The author begins by discussing Brand's four reasons for clinical tests and his analysis of the characteristics of valid biomechanical tests for use in orthopaedics. However, it is not clear how relevant this is to gait analysis in rehabilitation.

The article then goes on to discuss measurement methods in clinical gait analysis, stating that optical systems capable of measuring the positions of retro-reflective markers placed on the skin are no longer a significant source of error. However, the author notes that determining the anthropometry of the subject and compensating for soft tissue movement in relation to underlying bones are still challenges. The article also mentions techniques for using functional tests to determine joint centers and axes of rotation, but does not provide any details or evidence to support their effectiveness.

The author then discusses methods for interpreting gait analysis data, noting that there is still not an accepted general theory of why we walk the way we do. The article suggests that a whole new methodology is developing to determine the functions of individual muscles, but again does not provide any evidence or examples to support this claim.

Finally, the article discusses methods for understanding the effects of intervention, stating that clinical gait analysis is limited if it does not allow clinicians to choose between alternative possible interventions or predict outcomes. The author suggests that this can be achieved through rigorously planned clinical trials or using theoretical models. However, there is no discussion about potential risks associated with these interventions or how they might impact patients' quality of life.

Overall, while this article provides some useful information about gait analysis in rehabilitation, it lacks depth and detail in many areas. There are unsupported claims and missing evidence throughout the article, which may lead readers to question its reliability and accuracy. Additionally, there is a lack of exploration into potential counterarguments or alternative perspectives on gait analysis in rehabilitation.