Advanced Gait, Balance and Falls Risk Assessment
Instrumented gait analysis (IGA), can provide accurate and precise quantitative measurement of gait patterns and characteristics, has long been the gold standard for gait assessment in research. In the practical field it is far superior to general observation.
IGA, can provide accurate and precise quantitative measurement of gait patterns and characteristics.
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Instrumented walkway associated sensors + balance tasks to quantify speed, cadence, stride length, variability, symmetry, stability.
Targets falls risk reduction and mobility coaching.
Kinetics and Agility Coordination Testing.
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Several short walks at usual pace; timed balance holds; dual-task variants if safe; rests provided.
Prep: comfortable shoes; bring usual aid (cane/frame).
Instrumented Gait Analysis
The walking ability of a person is typically based on two main aspects: how far can an individual walk and what is his/her tolerance level [1]. For example, for post stroke gait assessment, 4-, 6-, or 10-meter walk tests are used, in addition to Functional Ambulation Category (FAC), Short Physical Performance Battery (SPPB), and/or Motor Assessment Scale (MAS).
The quality of gait or “how” the person walks, on the other hand, highly depends on the quantification of gait patterns and accurate identification of specific gait characteristics.
With an increase in age, physiologically characterised by a decrease in lean mass, bone mineral density and, to a lesser extent, fat mass disturbances in either one of these functions affect parameters of gait (i.e. speed, stride length, and swing time), thus resulting in abnormal gait [2]. Gait speed for example has been described as the ‘sixth vital sign’ because it is a core indicator of health and function in aging and disease [3] In clinical gait assessment, both a person's “ability” to walk and “how” the individual walks are highly relevant.
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Falls risk; post-event de-conditioning; neuro/ortho history; return-to-activity planning.
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Pinpoints falls risk and mobility limits with objective numbers.
Converts results into simple home drills and confidence-building targets.
Clear before/after view at re-test.
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Spatiotemporal indices: gait speed (m/s), cadence (steps/min), stride length (m), variability (%), symmetry (%), stability index.
Flags: traffic-light summary (e.g., speed <0.8 m/s; variability ↑).
Plan: translate to home drills (step width, cadence cues, sit-to-stand sets), and pair with Strength & ROM results.
Follow-up: re-test 6–8 weeks; show delta on a simple bar/line plot.
Delivery: Clinician PDF in 2–3 business days (priority 24 h); CSV for audit/trend on request.
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This has been successfully used to quantify and improve gait dysfunction associated with ageing and assess the risk of falling [1]. Spatiotemporal gait parameters such as velocity, swing time, stride length, stride time- and double support time variability, as well as heel strike and toe off angles, and foot clearance, have been suggested as plausible indicative quantitative measures , to assess the risk of falling in elderly subjects. [1].
However also in 2009 INTERNATIONAL ACADEMY ON NUTRITION AND AGING (IANA) TASK FORCE -gait speed, as a single-item tool, to be at least as sensible as the composite tools in predicting most of these outcomes over time. As such an “easy-to-remember” cutpoint for high falls risk, based on literature is 0.8 ms-1 [2]. But other parameters including balance tests can provide additional relative risk definition.
Multi-component exercise therapy which consisted of strength, range of motion (ROM) exercise, balance, flexibility and stretching exercises, circuit exercise training, and gait training was found to enhance gait function for individuals suffering with diabetic peripheral neuropathy compared to control groups using spatiotemporal gait parameters like velocity, cadence, step length, step time, double support time, stride length, stride time, ankle ROM. Gait assessment has potential to develop patient training paradigms for overcoming gait disorders [3].
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Post-operative Assessment
Researchers have investigated the evaluation of ambulatory systems for gait analysis post hip replacement [5]. They found gait characteristics such as stride length and velocity, as well as thigh and shank rotations different from healthy individuals and recommended their use to monitor post-surgical rehabilitation efficacy.
Stroke Patients
Spatiotemporal characteristics of post-stroke gait include reduced step or stride length, increased step length on the hemiparetic side, wider base of support, greater toe-out angle, reduced walking speed and cadence. Stride time, stance period on both lower limb, and double support time are also increased, in addition to less time in stance and more time in swing phase for the paretic side, as well as asymmetries in spatial and temporal factors. So easily observable factors include; decreased plantarflexion of the ankle at toe-off, a significant decrease in peak hip and knee flexion during the swing phase, reduced knee extension prior to initial contact, as well as decreased ankle dorsiflexion during swing) [6].
Falls Risk
For falls risk in elderly the test-retest reliability of an accelerometer-based system for measuring spatiotemporal parameters, including walking speed, step length, and cadence, as well as other parameters, including gait symmetry, gait regularity are excellent. There is a consensus on the definition of physical frailty [7]. Almost all of the studies in a recent 18 study meta-analysis of gait identified slowness as one of the most prevalent criterions in the definition of frailty status and observed that walking speed in the frail population was significantly lower than healthy controls [8]. A meaningful change in gait speed has been established at 0.1 ms-1 (at usual pace in a 4-meter walk), and it has been proven that increases in gait speed due to intervention increases survival, as high as a reduction of 17.7% in absolute risk of death [9].
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Aminian K, Trevisan C, Najafi B, Dejnabadi H, Frigo C, Pavan E, et al. Evaluation of an ambulatory system for gait analysis in hip osteoarthritis and after total hip replacement. Gait Posture. (2004) 20:102–7. 10.1016/S0966-6362(03)00093-6.
Nadeau S, Betschart M, Bethoux F. Gait analysis for poststroke rehabilitation: the relevance of biomechanical analysis and the impact of gait speed. Phys Med Rehabil Clin N Am. (2013) 24:265–76. 10.1016/j.pmr.2012.11.007.
Fried LP, Tangen CM, Walston J, Newman AB, Hirsch C, Gottdiener J, et al. Frailty in older adults: evidence for a phenotype. J Gerontol A Biol Sci Med Sci 2001;56: M146–M156.
Bortone, I., Sardone, R., Lampignano, L., Castellana, F., Zupo, R., Lozupone, M., Moretti, B., Giannelli, G., & Panza, F. (2021). How gait influences frailty models and health-related outcomes in clinical-based and population-based studies: a systematic review. J Cachexia Sarcopenia Muscle, 12(2), 274-297.
Hardy SE, Perera S, Roumani YF, Chandler JM, Studenski SA. Improvement in usual gait speed predicts better survival in older adults. J Am Geriatr Soc. 2007; 55:1727-1734.
Schülein S, Barth J, Rampp A, Rupprecht R, Eskofier BM, Winkler J, et al. Instrumented gait analysis: a measure of gait improvement by a wheeled walker in hospitalized geriatric patients. J Neuroeng Rehabil. (2017) 14:18.
Yen SC, Schmit BD, Wu M. Using swing resistance and assistance to improve gait symmetry in individuals post-stroke. Hum Mov Sci. (2015) 42:212–24.
Abellan van Kan, G., Rolland, Y., Andrieu, S., Bauer, J., Beauchet, O., Bonnefoy, M., Cesari, M., Donini, L. M., Gillette Guyonnet, S., Inzitari, M., Nourhashemi, F., Onder, G., Ritz, P., Salva, A., Visser, M., & Vellas, B. (2009). Gait speed at usual pace as a predictor of adverse outcomes in community-dwelling older people an International Academy on Nutrition and Aging (IANA) Task Force. J Nutr Health Aging, 13(10), 881-889. https://doi.org/10.1007/s12603-009-0246-z.