Summary measures for clinical gait analysis: A literature review

Cimolin, Verônica; Galli, Manuela

doi:10.1016/j.gaitpost.2014.02.001

Cited by 235 publications

(121 citation statements)

References 30 publications

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“…Therefore, a dimensionless database could be built so as a set of dimensionless mechanical parameters would correspond to a Modela-w. Although the advantages of using database as reference have already been shown [21,25], a dimensionless database removes anthropometric individual characteristics on referenced parameters and would allow to i) compare species [26] and to ii) detect pathology among elderly [23] and young [27] by using deviation indexes [28]. Given that the dimensionless database would gather bio-markers of healthy walking (kinematic and dynamic), a relevant dimensionless deviation index could be proposed to detect a difference due to fitness, pathology, ageing, etc.…”

Section: Discussionmentioning

confidence: 99%

Walking dynamic similarity induced by a combination of Froude and Strouhal dimensionless numbers: Modela-w

et al. 2015

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Section: Discussionmentioning

confidence: 99%

Walking dynamic similarity induced by a combination of Froude and Strouhal dimensionless numbers: Modela-w

et al. 2015

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“…Realistically any number of possible micro gait outcomes can be quantified due to the range of mathematical permutations which could be applied to wearable data, which has hindered clinical use [46]. In general, micro outcomes can be classed as spatio-temporal and frequency-based (e.g.…”

Section: Activity Recognition: Macro and Micro Gaitmentioning

confidence: 99%

Wearables for independent living in older adults: Gait and falls

Godfrey

2017

Maturitas

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Solutions are needed to satisfy care demands of older adults to live independently. Wearable technology (wearables) are one approach to offer a viable means for ubiquitous, sustainable and scalable monitoring in habitual free-living environments. Gait has been presented as a relevant (bio) marker in ageing and pathological studies, with objective assessment achievable by inertial-based wearables. Commercial wearables have struggled to provide accurate analytics and have been limited by non-clinically oriented gait outcomes. Moreover, some research grade wearables also fail to provide transparent functionality due to limitations in proprietary software. Innovation within this field is often sporadic with large heterogeneity of wearable types and algorithms for gait outcomes leading to a lack of pragmatic use. This review provides a summary of recent wearable gait assessment literature, focusing on the need for an algorithm fusion approach to measurement cumulating in the ability to better detect and classify falls. A brief presentation of wearables in one pathological group is presented, identifying appropriate work for researchers in other cohorts to utilise. Opportunities for how this domain needs to progress are also summarised. Highlights• Wearables can meet older adults' needs for independent living.• Gait assessment is a (bio)marker within ageing and different pathologies.• Measuring gait with wearables has been innovative but fraught with inconsistencies.

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“…Healthcare professionals such as physiotherapists and biomedical engineers perform 3DGA. The examination provides a large amount of complex and interdependent data, which have led to the development of indices that can describe the quality of the gait pattern in a single score [2]. The summary measures most commonly used are the Gait Deviation Index (GDI) [3] and the Gait Profile Score (GPS) [4], which both provide a single score of the quality of the patient's kinematics during gait.…”

Section: Introductionmentioning

confidence: 99%