Gait Analysis – The How and The Why (Plus 5 Key Benefits)

Part II

by Brie Darcy, PT, DPT

At Moterum Technologies, one of our primary goals is not only to help people move more but to help them move better. This requires a substantial emphasis and understanding on the subject of walking or “gait.” Last month we introduced the important topic of gait analysis. In this article, we will review two critical subtopics: the how and, most importantly, the why of gait analysis.

So, how do we analyze gait, exactly?

Broadly defined, gait analysis is the process of measuring body movement and body mechanics during walking. This process can be accomplished through various methods – some of which include visual observation, while others involve the use of novel technologies.

Observational Gait Analysis
In the medical community, doctors, physical therapists, and other health professionals are trained to provide observational analysis of gait. During observational gait analysis, a clinician will watch an individual walk, carefully assessing for visual deviations from standard gait mechanics. While common in clinical practice (as well as efficient and cost-effective), studies unfortunately reveal substantial inaccuracies with observational gait analysis (even for experienced clinicians).1-3 Additionally, the small subtleties of gait (which can have big impacts) may be overlooked.

Gait Analysis Technologies
As the role and benefits of gait analysis become more acknowledged and well-known in the medical community, novel technologies have been developed to the improve the ease and accuracy of gathering gait information. Importantly, they provide gait information that is objective and measurable (as opposed to the more subjective nature of observational analysis). These gait-focused technologies can be classified into wearable and non-wearable systems.

Non-wearable systems typically involve the usage of controlled scientific environments and are more likely to be used in research facilities or gait-focused clinical trials. These systems typically involve camera systems, lasers, and even infrared sensors which can be used to create digital images for processing and analysis. Another method involves using force platforms or mats to generate gait data which is generated by the force exerted on the ground as an individual walks.

In contrast, wearable systems use sensors placed on various parts of the body to characterize movement patterns. Sensors can be specialized to measure varying types of movement information such as acceleration, muscle activation, or joint positions. Importantly, wearable systems can be used to provide objective data on human movement patterns outside of laboratory environments. This key benefit has led to Moterum’s usage of wearable gait sensors for individuals needing gait treatment from the home environment.

5 Benefits of Objective Gait Analysis

Here are 5 reasons we value the importance of objective gait analysis in clinical practice.

Diagnosing Movement Dysfunction

A thorough gait analysis will help identify the presence of gait dysfunction. To do this, detailed information regards one’s gait (such as speed or symmetry, for example) can be compared to “normal” values of similarly aged individuals. Is having parameters outside of established norms always problematic? Not necessarily! Some impairments are temporary. Perhaps you walk with a limp due to a pulled muscle. As soon as that muscle heals, your gait will likely return to normal. However, a persisting gait abnormality can have negative consequences such as unnatural joint stress which can contribute to pain or joint damage. If more severe, it could affect one’s independence or increase the likelihood of a fall. Analysis of gait patterns (and their severity) can identify the necessity of treatment. Additionally, gait analysis performed with using objective outputs (as done with movement sensors) can provide quantifiable detail regarding the specific and unique factors characterizing the impairment.

Personalized Treatment

Improving walking ability is one of the most commonly cited goals of individuals undergoing rehabilitation. This occurs for good reason. Studies show that walking ability correlates with quality of life, morbidity, and mortality.4 The ability to identify (and effectively treat) gait impairments is a key factor to promoting health. Perhaps your steps are quite small, your timing is asymmetric, or your trunk sways excessively while you are walking. Learning your personal, altered patterns will enable your clinician to identify and target specifically what you need to improve. This can lead to treatment that is more personalized, specific, (and potentially more efficient and effective). Understanding and objectively quantifying your current walking ability can help tailor unique treatment that will help you move more and move better.

Early Detection

Did you know that your gait patterns can also provide early insight into disease detection? Because gait requires a coordinated effort of multiple physiologic systems, the outward presence of gait dysfunction can sometimes reveal trouble with one of the associated physiological systems. The detailed assessment and monitoring of gait patterns has even demonstrated the ability to predict the development of certain diseases including diabetes, dementia, and Parkinson’s Disease sometimes (at times even years before they are diagnosed clinically).4 Specifically focusing on cognitive decline, researchers found that gait pattern changes (measured by gait speed) accelerated 12 years prior to the onset of mild cognitive impairment.5 The benefits of early disease detection (and early introduction of effective therapeutics) could vastly improve the clinical course and progression of these conditions.

Prevention is Key (Especially for Falls!)

Traditional rehabilitation environments are accustomed to treating abnormal gait patterns; however, identification of these altered mechanics often does not occur until after harmful injuries (such as falls) or costly hospitalizations occur. What if we could identify the likelihood of having a fall BEFORE it occurs? Fortunately, researchers have identified certain gait characteristics which are associated with one’s risk of falling. Gait variability is one such factor. Gait variability refers to the stride to stride fluctuations in gait.6 While some variability in gait is considered normal and allows for adaptations and flexibility to changing environmental factors, higher levels of variability are associated with a greater energy cost, decreased balance, cognitive impairment, and, importantly, falls.7 More specifically, a study by Hausdorff, Rios, and Edelberg (2001) found that likelihood of falling increased fivefold with only a moderate increased in stride time variability.8 Early identification of altered gait patterns (and appropriate intervention) could prevent further consequences such as harmful injuries and loss of independence.9

Objective Progress

An additional key benefit of objective gait analysis is progress tracking. Repeated, objective gait assessments throughout the treatment process (in comparison with parameters at the start of treatment) can give specific information to confirm progress. The ability to detect even small subtleties of improvement can enhance motivation and give validation that your treatment is on the right track.

Moterum’s Role

At Moterum Technologies, we believe that top-notch, world-class rehabilitation care can be delivered where people need it the most – at home. Therefore, we have integrated our specialized, wearable, gait sensors, into our Moterum Health Platform. Allowing focused gait measurement and tracking of important gait patterns, we can partner with you to help you achieve your best health.

References 

  1. Williams G, Morris ME, Schache A, McCrory P. Observational gait analysis in traumatic brain injury: accuracy of clinical judgment. Gait Posture. 2009;29(3):454-459.
  2. Krosshaug T, Nakamae A, Boden B, et al. Estimating 3D joint kinematics from video sequences of running and cutting maneuvers–assessing the accuracy of simple visual inspection. Gait Posture. 2007;26(3):378-385.
  3. Saleh M, Murdoch G. In defence of gait analysis. Observation and measurement in gait assessment. J Bone Joint Surg Br. 1985;67(2):237-241.
  4. Horst F, Lapuschkin S, Samek W, Muller KR, Schollhorn WI. Explaining the unique nature of individual gait patterns with deep learning. Sci Rep. 2019;9(1):2391.
  5. Buracchio T, Dodge HH, Howieson D, Wasserman D, Kaye J. The trajectory of gait speed preceding mild cognitive impairment. Arch Neurol. 2010;67(8):980-986.
  6. Hausdorff JM. Gait variability: methods, modeling and meaning. J Neuroeng Rehabil. 2005;2:19.
  7. Bogen B, Aaslund MK, Ranhoff AH, Moe-Nilssen R. Two-year changes in gait variability in community-living older adults. Gait Posture. 2019;72:142-147.
  8. Hausdorff JM, Rios DA, Edelberg HK. Gait variability and fall risk in community-living older adults: a 1-year prospective study. Arch Phys Med Rehabil. 2001;82(8):1050-1056.
  9. Salzman B. Gait and balance disorders in older adults. Am Fam Physician. 2010;82(1):61-68.

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