Managing Gait Disorders in Older Persons Residing in Nursing Homes: A Review of Literature

Canavan, Paul K.; Cahalin, Lawrence P.; Lowe, Susan; Fitzpatrick, D.; Harris, Meredith; Plummer, Prudence

doi:10.1016/j.jamda.2009.02.008

Cited by 23 publications

(13 citation statements)

References 60 publications

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“…However, it is known that institutionalization weakens and undermines the health of older people, and their reduced mobility is one of the most frequent causes of disability. In such a scenario, balance disorders occur [14]. In the present study, this association was not observed, perhaps because of the small size of the sample group.…”

Section: Discussioncontrasting

confidence: 71%

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Risk Factors of Dizziness among Institutionalized Elderly Persons: A Case Control Study

Ferreira¹

2016

J Gerontol Geriatr Res

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Section: Discussioncontrasting

confidence: 71%

“…Other important risk factors are the presence of cognitive disorders such as dementia, anxiety and depression; locomotor deficits; visual, vestibular and proprioceptive disorders [6,[13][14][15].…”

Section: Introductionmentioning

confidence: 99%

Risk Factors of Dizziness among Institutionalized Elderly Persons: A Case Control Study

Ferreira¹

2016

J Gerontol Geriatr Res

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“…Overview articles have repeatedly discussed the potential of WS training paradigms for improving clinically relevant motor performances such as postural stability or gait, which are important for safe ambulation and mobility-related quality of life [7,9,17] . However, to our knowledge, a systematic review and meta-analysis of WS balance and gait training programs does not exist.…”

Section: Introductionmentioning

confidence: 99%

Effects of Wearable Sensor-Based Balance and Gait Training on Balance, Gait, and Functional Performance in Healthy and Patient Populations: A Systematic Review and Meta-Analysis of Randomized Controlled Trials

et al. 2017

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n = 1, type 3: n = 3) or combined different types of training paradigms within their intervention (type 1 and 2: n = 2; all types: n = 2). The meta-analyses revealed significant overall effects of WS training on static steady-state balance outcomes including mediolateral (eyes open: Hedges' g = 0.82, CI: 0.43-1.21; eyes closed: g = 0.57, CI: 0.14-0.99) and anterior-posterior sway (eyes open: g = 0.55, CI: 0.01-1.10; eyes closed: g = 0.44, CI: 0.02-0.86). No effects on habitual gait speed were found in the meta-analysis ( g = -0.19, CI: -0.68 to 0.29). Two RCTs reported significant improvements for selected gait variables including single support time, and fast gait speed. One study identified effects on proactive balance (Alternate Step Test), but no effects were found for the Timed Up and Go test and the Berg Balance Scale. Two studies reported positive results on feasibility and usability. Only one study was performed in an unsupervised setting. Conclusion: This review provides evidence for a positive effect of WS training on static steady-state balance in studies with usual care controls and studies with conventional balance training controls. Specific gait parameters and proactive balance measures may also be improved by WS training, yet limited evidence is available. Heterogeneous training paradigms, small sample sizes, and short intervention durations limit the validity of our findings. Larger studies are required for estimating the true potential of WS technology. © 2017 S. Karger AG, Basel KeywordsInertial measurement unit · Force sensor · Postural balance · Gait · Biofeedback · Exergame · Systematic review Abstract Background: Wearable sensors (WS) can accurately measure body motion and provide interactive feedback for supporting motor learning. Objective: This review aims to summarize current evidence for the effectiveness of WS training for improving balance, gait and functional performance. Methods: A systematic literature search was performed in PubMed, Cochrane, Web of Science, and CINAHL. Randomized controlled trials (RCTs) using a WS exercise program were included. Study quality was examined by the PEDro scale. Metaanalyses were conducted to estimate the effects of WS balance training on the most frequently reported outcome parameters. Results: Eight RCTs were included (Parkinson n = 2, stroke n = 1, Parkinson/stroke n = 1, peripheral neuropathy n = 2, frail older adults n = 1, healthy older adults n = 1). The sample size ranged from n = 20 to 40. Three types of training paradigms were used: (1) static steady-state balance training, (2) dynamic steady-state balance training, which includes gait training, and (3) proactive balance training. RCTs either used one type of training paradigm (type 2:

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“…These factors produce kinematic changes on the gait patterns, including slower velocity and decreased stride and step length with increased stride frequency [3].…”

Section: Introductionmentioning

confidence: 99%

Sensor fusion to control a robotic walker based on upper-limbs reaction forces and gait kinematics

Cifuentes

Rodríguez

Frizera

et al. 2014

5th IEEE RAS/EMBS International Conference on Biomedical Robotics and Biomechatronics

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This work proposes the implementation and validation of a new sensor fusion strategy based on force sensors and LRF (Laser Range Finder) to control a robotic walker. This approach combines user information about forearm reaction forces and gait kinematics from the legs scanning localization, to develop a more natural, safer and adaptable human-walker interaction. The work was carried out in four phases. First, a robotic walker platform was developed and the sensor subsystems were integrated. Second, a sensor fusion strategy to obtain the control parameters are defined. Third, the control strategy is presented. Finally, an experimental study to evaluate the sensor architecture and control was developed. One of the advantages of the humanwalker interaction here proposed is the computational efficiency. The sensor processing algorithms and the control strategy are executed in real-time, showing stable performance with human speed changes.

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Managing Gait Disorders in Older Persons Residing in Nursing Homes: A Review of Literature

Cited by 23 publications

References 60 publications

Risk Factors of Dizziness among Institutionalized Elderly Persons: A Case Control Study

Risk Factors of Dizziness among Institutionalized Elderly Persons: A Case Control Study

Effects of Wearable Sensor-Based Balance and Gait Training on Balance, Gait, and Functional Performance in Healthy and Patient Populations: A Systematic Review and Meta-Analysis of Randomized Controlled Trials

Sensor fusion to control a robotic walker based on upper-limbs reaction forces and gait kinematics

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