Dataset Information

Virtual Footprints Can Improve Walking Performance in People With Parkinson's Disease.

ABSTRACT: In Parkinson's disease (PD) self-directed movement, such as walking, is often found to be impaired while goal directed movement, such as catching a ball, stays relatively unaltered. This dichotomy is most clearly observed when sensory cueing techniques are used to deliver patterns of sound and/or light which in turn act as an external guide that improves gait performance. In this study we developed visual cues that could be presented in an immersive, interactive virtual reality (VR) environment. By controlling how the visual cues (black footprints) were presented, we created different forms of spatial and temporal information. By presenting the black footprints at a pre-specified distance apart we could recreate different step lengths (spatial cues) and by controlling when the black footprints changed color to red, we could convey information about the timing of the foot placement (temporal cues). A group of healthy controls (HC; N = 10) and a group of idiopathic PD patients (PD, N = 12) were asked to walk using visual cues that were tailored to their own gait performance [two spatial conditions (115% [N] and 130% [L] of an individual's baseline step length) and three different temporal conditions (spatial only condition [NT], 100 and 125% baseline step cadence)]. Both groups were found to be able to match their gait performance (step length and step cadence) to the information presented in all the visual cue conditions apart from the 125% step cadence conditions. In all conditions the PD group showed reduced levels of gait variability (p < 0.05) while the HC group did not decrease. For step velocity there was a significant increase in the temporal conditions, the spatial conditions and of the interaction between the two for both groups of participants (p < 0.05). The coefficient of variation of step length, cadence, and velocity were all significantly reduced for the PD group compared to the HC group. In conclusion, our results show how virtual footsteps presented in an immersive, interactive VR environment can significantly improve gait performance in participants with Parkinson's disease.

SUBMITTER: Gomez-Jordana LI

PROVIDER: S-EPMC6107758 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

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Virtual Footprints Can Improve Walking Performance in People With Parkinson's Disease.

Gómez-Jordana Luis I LI Stafford James J Peper C Lieke E CLE Craig Cathy M CM

Frontiers in neurology 20180817

In Parkinson's disease (PD) self-directed movement, such as walking, is often found to be impaired while goal directed movement, such as catching a ball, stays relatively unaltered. This dichotomy is most clearly observed when sensory cueing techniques are used to deliver patterns of sound and/or light which in turn act as an external guide that improves gait performance. In this study we developed visual cues that could be presented in an immersive, interactive virtual reality (VR) environment. ...[more]

PMID: 30174648

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Project description:RationaleCocoa and its major flavanol component, epicatechin, have therapeutic properties that may improve limb perfusion and increase calf muscle mitochondrial activity in people with lower extremity peripheral artery disease (PAD).ObjectiveIn a phase II randomized clinical trial, to assess whether 6 months of cocoa improved walking performance in people with PAD, compared with placebo.Methods and resultsSix-month double-blind, randomized clinical trial in which participants with PAD were randomized to either cocoa beverage versus placebo beverage. The cocoa beverage contained 15 g of cocoa and 75 mg of epicatechin daily. The identical appearing placebo contained neither cocoa nor epicatechin. The 2 primary outcomes were 6-month change in 6-minute walk distance measured 2.5 hours after a study beverage at 6-month follow-up and 24 hours after a study beverage at 6-month follow-up, respectively. A 1-sided P<0.10 was considered statistically significant. Of 44 PAD participants randomized (mean age, 72.3 years [±7.1]; mean ankle brachial index, 0.66 [±0.15]), 40 (91%) completed follow-up. Adjusting for smoking, race, and body mass index, cocoa improved 6-minute walk distance at 6-month follow-up by 42.6 m ([90% CI, +22.2 to +∞] P=0.005) at 2.5 hours after a final study beverage and by 18.0 m ([90% CI, -1.7 to +∞] P=0.12) at 24 hours after a study beverage, compared with placebo. In calf muscle biopsies, cocoa improved mitochondrial COX (cytochrome c oxidase) activity (P=0.013), increased capillary density (P=0.014), improved calf muscle perfusion (P=0.098), and reduced central nuclei (P=0.033), compared with placebo.ConclusionsThese preliminary results suggest a therapeutic effect of cocoa on walking performance in people with PAD. Further study is needed to definitively determine whether cocoa significantly improves walking performance in people with PAD.Clinical trial registrationURL: http://www.clinicaltrials.gov. Unique identifier: NCT02876887. Visual Overview: An online visual overview is available for this article.

Project description:Freezing-of-gait (FOG) and impaired walking are common features of Parkinson's disease (PD). Provision of external stimuli (cueing) can improve gait, however, many cueing methods are simplistic, increase task loading or have limited utility in a real-world setting. Closed-loop (automated) somatosensory cueing systems have the potential to deliver personalised, discrete cues at the appropriate time, without requiring user input. Further development of cue delivery methods and FOG-detection are required to achieve this. In this feasibility study, we aimed to test if FOG-initiated vibration cues applied to the lower-leg via wearable devices can improve gait in PD, and to develop real-time FOG-detection algorithms. 17 participants with Parkinson's disease and daily FOG were recruited. During 1 h study sessions, participants undertook 4 complex walking circuits, each with a different intervention: continuous rhythmic vibration cueing (CC), responsive cueing (RC; cues initiated by the research team in response to FOG), device worn with no cueing (NC), or no device (ND). Study sessions were grouped into 3 stages/blocks (A-C), separated by a gap of several weeks, enabling improvements to circuit design and the cueing device to be implemented. Video and onboard inertial measurement unit (IMU) data were analyzed for FOG events and gait metrics. RC significantly improved circuit completion times demonstrating improved overall performance across a range of walking activities. Step frequency was significantly enhanced by RC during stages B and C. During stage C, > 10 FOG events were recorded in 45% of participants without cueing (NC), which was significantly reduced by RC. A machine learning framework achieved 83% sensitivity and 80% specificity for FOG detection using IMU data. Together, these data support the feasibility of closed-loop cueing approaches coupling real-time FOG detection with responsive somatosensory lower-leg cueing to improve gait in PD.

Project description:BackgroundPostural instability and gait disability threaten the independence and well-being of people with Parkinson's disease and increase the risk of falls and fall-related injuries. Prospective research has shown that commonly-used clinical assessments of balance and walking lack the sensitivity to accurately and consistently identify those people with Parkinson's disease who are at a higher risk of falling. Wearable sensors provide a portable and affordable alternative for researchers and clinicians who are seeking to objectively assess movements and falls risk in the clinical setting. However, no consensus currently exists on the optimal placements for sensors and the best outcome measures to use for assessing standing balance and walking stability in Parkinson's disease patients. Hence, this systematic review aimed to examine the available literature to establish the best sensor types, locations and outcomes to assess standing balance and walking stability in this population.MethodsPapers listed in three electronic databases were searched by title and abstract to identify articles measuring standing balance or walking stability with any kind of wearable sensor among adults diagnosed with PD. To be eligible for inclusion, papers were required to be full-text articles published in English between January 1994 and December 2014 that assessed measures of standing balance or walking stability with wearable sensors in people with PD. Articles were excluded if they; i) did not use any form of wearable sensor to measure variables associated with standing balance or walking stability; ii) did not include a control group or control condition; iii) were an abstract and/or included in the proceedings of a conference; or iv) were a review article or case study. The targeted search of the three electronic databases identified 340 articles that were potentially eligible for inclusion, but following title, abstract and full-text review only 26 articles were deemed to meet the inclusion criteria. Included articles were assessed for methodological quality and relevant data from the papers were extracted and synthesized.ResultsQuality assessment of these included articles indicated that 31% were of low methodological quality, while 58% were of moderate methodological quality and 11% were of high methodological quality. All studies adopted a cross-sectional design and used a variety of sensor types and outcome measures to assess standing balance or walking stability in people with Parkinson's disease. Despite the typically low to moderate methodological quality, 81% of the studies reported differences in sensor-based measures of standing balance or walking stability between different groups of Parkinson's disease patients and/or healthy controls.ConclusionThese data support the use of wearable sensors for detecting differences in standing balance and walking stability between people with PD and controls. Further high-quality research is needed to better understand the utility of wearable sensors for the early identification of Parkinson's disease symptoms and for assessing falls risk in this population.Prospero registrationCRD42014010838.

Dataset Information

Virtual Footprints Can Improve Walking Performance in People With Parkinson's Disease.

Publications

Virtual Footprints Can Improve Walking Performance in People With Parkinson's Disease.

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