Assessment of physical function following total hip arthroplasty: Inertial sensor based gait analysis is supplementary to patient-reported outcome measures

Wearable sensors, in particular inertial measurement units (IMUs) allow the objective, valid, discriminative and responsive assessment of physical function during functional tests such as gait, stair climbing or sit-to-stand.Applied to various body segments, precise capture of time-to-task achievement, spatiotemporal gait and kinematic parameters of demanding tests or specific to an affected limb are the most used measures.In activity monitoring (AM), accelerometry has mainly been used to derive energy expenditure or general health related parameters such as total step counts.In orthopaedics and the elderly, counting specific events such as stairs or high intensity activities were clinimetrically most powerful; as were qualitative parameters at the ‘micro-level’ of activity such as step frequency or sit-stand duration.Low cost and ease of use allow routine clinical application but with many options for sensors, algorithms, test and parameter definitions, choice and comparability remain difficult, calling for consensus or standardisation.Cite this article: Grimm B, Bolink S. Evaluating physical function and activity in the elderly patient using wearable motion sensors. EFORT Open Rev 2016;1:112–120. DOI: 10.1302/2058-5241.1.160022.

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“…Therefore, IMU-based gait analysis is a feasible and sophisticated tool for routine functional outcome assessment in orthopaedics. 20 …”

Section: Physical Functionmentioning

confidence: 99%

Evaluating physical function and activity in the elderly patient using wearable motion sensors

Grimm

Bolink

2016

EFORT Open Reviews

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“…Another strength of this trial is the 12-month follow-up period, which will allow assessment of the long-term impact of physiotherapy on patient outcomes and resource use. However, in addition to patient-reported outcome measures, the trial may have benefitted from the inclusion of more objective measures of function, such as muscle strength or gait analysis, as these capture different dimensions of function [ 57 ]. Another limitation of the trial which warrants acknowledgement is the lack of blinding, because of the group-based nature of the physiotherapy intervention.…”

Section: Discussionmentioning

confidence: 99%

Effectiveness and cost-effectiveness of outpatient physiotherapy after knee replacement for osteoarthritis: study protocol for a randomised controlled trial

Wylde

Artz

Marques

et al. 2016

Trials

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BackgroundPrimary total knee replacement is a common operation that is performed to provide pain relief and restore functional ability. Inpatient physiotherapy is routinely provided after surgery to enhance recovery prior to hospital discharge. However, international variation exists in the provision of outpatient physiotherapy after hospital discharge. While evidence indicates that outpatient physiotherapy can improve short-term function, the longer term benefits are unknown. The aim of this randomised controlled trial is to evaluate the long-term clinical effectiveness and cost-effectiveness of a 6-week group-based outpatient physiotherapy intervention following knee replacement.Methods/designTwo hundred and fifty-six patients waiting for knee replacement because of osteoarthritis will be recruited from two orthopaedic centres. Participants randomised to the usual-care group (n = 128) will be given a booklet about exercise and referred for physiotherapy if deemed appropriate by the clinical care team. The intervention group (n = 128) will receive the same usual care and additionally be invited to attend a group-based outpatient physiotherapy class starting 6 weeks after surgery. The 1-hour class will be run on a weekly basis over 6 weeks and will involve task-orientated and individualised exercises.The primary outcome will be the Lower Extremity Functional Scale at 12 months post-operative. Secondary outcomes include: quality of life, knee pain and function, depression, anxiety and satisfaction. Data collection will be by questionnaire prior to surgery and 3, 6 and 12 months after surgery and will include a resource-use questionnaire to enable a trial-based economic evaluation. Trial participation and satisfaction with the classes will be evaluated through structured telephone interviews. The primary statistical and economic analyses will be conducted on an intention-to-treat basis with and without imputation of missing data. The primary economic result will estimate the incremental cost per quality-adjusted life year gained from this intervention from a National Health Services (NHS) and personal social services perspective.DiscussionThis research aims to benefit patients and the NHS by providing evidence on the long-term effectiveness and cost-effectiveness of outpatient physiotherapy after knee replacement. If the intervention is found to be effective and cost-effective, implementation into clinical practice could lead to improvement in patients’ outcomes and improved health care resource efficiency.Trial registrationISRCTN32087234, registered on 11 February 2015.

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“…Gaits are important to know any developmental progress during some diseases or after some surgeries. Some important health and medical-related terminologies that can be addressed by gait characteristics are patients with cerebral palsy, cerebellar ataxia, knee arthroplasty, hip arthroplasty, Charcot-Marie-Tooth disease, idiopathic arthritis, idiopathic Parkinson's disease, atypical Parkinson's disease, bipolar disorder, dementia, Pick's disease, idiopathic normal pressure hydrocephalus, ankle osteoarthritis, Alzheimer's disease, postural instability, and gait difficulty, and to improve the life-quality of patients and elderly people who are suffering due to gait-related or walking pattern-related problems [13,21,22].…”

Section: Related Workmentioning

confidence: 99%

Wearable Sensor-Based Gait Analysis for Age and Gender Estimation

Ahad

Ngo

Antar

et al. 2020

Sensors

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Wearable sensor-based systems and devices have been expanded in different application domains, especially in the healthcare arena. Automatic age and gender estimation has several important applications. Gait has been demonstrated as a profound motion cue for various applications. A gait-based age and gender estimation challenge was launched in the 12th IAPR International Conference on Biometrics (ICB), 2019. In this competition, 18 teams initially registered from 14 countries. The goal of this challenge was to find some smart approaches to deal with age and gender estimation from sensor-based gait data. For this purpose, we employed a large wearable sensor-based gait dataset, which has 745 subjects (357 females and 388 males), from 2 to 78 years old in the training dataset; and 58 subjects (19 females and 39 males) in the test dataset. It has several walking patterns. The gait data sequences were collected from three IMUZ sensors, which were placed on waist-belt or at the top of a backpack. There were 67 solutions from ten teams—for age and gender estimation. This paper extensively analyzes the methods and achieved-results from various approaches. Based on analysis, we found that deep learning-based solutions lead the competitions compared with conventional handcrafted methods. We found that the best result achieved 24.23% prediction error for gender estimation, and 5.39 mean absolute error for age estimation by employing angle embedded gait dynamic image and temporal convolution network.

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Assessment of physical function following total hip arthroplasty: Inertial sensor based gait analysis is supplementary to patient-reported outcome measures

Cited by 39 publications

References 41 publications

Evaluating physical function and activity in the elderly patient using wearable motion sensors

Evaluating physical function and activity in the elderly patient using wearable motion sensors

Effectiveness and cost-effectiveness of outpatient physiotherapy after knee replacement for osteoarthritis: study protocol for a randomised controlled trial

Wearable Sensor-Based Gait Analysis for Age and Gender Estimation

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