A wearable smartphone-enabled camera-based system for gait assessment

Kim, Albert; Kim, Junyoung; Rietdyk, Shirley; Ziaie, Babak

doi:10.1016/j.gaitpost.2015.05.001

Cited by 38 publications

(13 citation statements)

References 25 publications

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“…Smartphone technology, although equipped with inertial sensors/camera, computing power and display to conduct an interactive assessment, has not been validated as a diagnostic tool for fall prediction [ 14 ]. However, numerous studies have validated its accuracy in balance and mobility tracking [ 12 , 13 ], and several proof-of-concept have been proposed to investigate fall risk/ provide fall prevention intervention [ 42 , 43 ].Other proof-of-concept studies that utilizing depth camera and radar sensing to provide in-home movement monitoring and fall risk assessment have also been reported in recent years [ 6 , 44 – 46 ]. In the long term, such ambient sensing technology may provide an unsupervised, automated fall risk screening tool in a community and/or assisted living settings.…”

Section: Discussionmentioning

confidence: 99%

Novel sensing technology in fall risk assessment in older adults: a systematic review

2018

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BackgroundFalls are a major health problem for older adults with significant physical and psychological consequences. A first step of successful fall prevention is to identify those at risk of falling. Recent advancement in sensing technology offers the possibility of objective, low-cost and easy-to-implement fall risk assessment. The objective of this systematic review is to assess the current state of sensing technology on providing objective fall risk assessment in older adults.MethodsA systematic review was conducted in accordance to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis statement (PRISMA).ResultsTwenty-two studies out of 855 articles were systematically identified and included in this review. Pertinent methodological features (sensing technique, assessment activities, outcome variables, and fall discrimination/prediction models) were extracted from each article. Four major sensing technologies (inertial sensors, video/depth camera, pressure sensing platform and laser sensing) were reported to provide accurate fall risk diagnostic in older adults. Steady state walking, static/dynamic balance, and functional mobility were used as the assessment activity. A diverse range of diagnostic accuracy across studies (47.9% - 100%) were reported, due to variation in measured kinematic/kinetic parameters and modelling techniques.ConclusionsA wide range of sensor technologies have been utilized in fall risk assessment in older adults. Overall, these devices have the potential to provide an accurate, inexpensive, and easy-to-implement fall risk assessment. However, the variation in measured parameters, assessment tools, sensor sites, movement tasks, and modelling techniques, precludes a firm conclusion on their ability to predict future falls. Future work is needed to determine a clinical meaningful and easy to interpret fall risk diagnosis utilizing sensing technology. Additionally, the gap between functional evaluation and user experience to technology should be addressed.

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Section: Discussionmentioning

confidence: 99%

Novel sensing technology in fall risk assessment in older adults: a systematic review

2018

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“…A recent study utilised a smartphone-based camera as a wearable placed on the front waist to quantify gait characteristics, a holistic approach to gait and contextual data recognition [40]. However, that requires additional markers on the feet.…”

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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“…Investigations either quantified the existing gait deficits in the pathological populations that may be used for detecting disease onset and progression or evaluated the improvements of gait due to various therapeutic interventions. Pressuresensing walkway system has also been used as the standardized comparison for the accuracy of gait parameters measured from other techniques, such as body-worn sensors (Hartmann et al 2009;Kim et al 2015;González et al 2016) and markerless motion tracking (Clark et al 2013).…”

Section: Current State Of Clinical and Research Applicationmentioning

confidence: 99%

Low Density Pedoboragraphy as a Gait Analysis Tool

Sun¹,

Wood²,

Sosnoff³

2016

Handbook of Human Motion

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Precise and objective evaluation of gait provides important information about an individual's overall health and can be used to detect symptoms of motor impairment, determine appropriate therapeutic procedures, and monitor rehabilitation progress. There are various gait analysis techniques currently available, including the three-dimensional motion tracking and the low density pedobarography, etc. The relative low cost, high accuracy and consistency, and automated data analysis features make the low density pedobarography technique an ideal platform for quantifying the spatial and temporal gait characteristics in various populations. The following chapter will review the use the low density pedobarography in conducting gait and balance assessment. Topics covered in this chapter will include the primary outcome measures of gait analysis using low density pedobarography, the validity and reliability of the equipment, the applications of the technique in clinical populations, guidelines for use, and the potential applications in future research and clinical environment.

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A wearable smartphone-enabled camera-based system for gait assessment

Cited by 38 publications

References 25 publications

Novel sensing technology in fall risk assessment in older adults: a systematic review

Novel sensing technology in fall risk assessment in older adults: a systematic review

Wearables for independent living in older adults: Gait and falls

Low Density Pedoboragraphy as a Gait Analysis Tool

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