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      Prolonged Walking with a Wearable System Providing Intelligent Auditory Input in People with Parkinson’s Disease

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          Abstract

          Rhythmic auditory cueing is a well-accepted tool for gait rehabilitation in Parkinson’s disease (PD), which can now be applied in a performance-adapted fashion due to technological advance. This study investigated the immediate differences on gait during a prolonged, 30 min, walk with performance-adapted (intelligent) auditory cueing and verbal feedback provided by a wearable sensor-based system as alternatives for traditional cueing. Additionally, potential effects on self-perceived fatigue were assessed. Twenty-eight people with PD and 13 age-matched healthy elderly (HE) performed four 30 min walks with a wearable cue and feedback system. In randomized order, participants received: (1) continuous auditory cueing; (2) intelligent cueing (10 metronome beats triggered by a deviating walking rhythm); (3) intelligent feedback (verbal instructions triggered by a deviating walking rhythm); and (4) no external input. Fatigue was self-scored at rest and after walking during each session. The results showed that while HE were able to maintain cadence for 30 min during all conditions, cadence in PD significantly declined without input. With continuous cueing and intelligent feedback people with PD were able to maintain cadence ( p = 0.04), although they were more physically fatigued than HE. Furthermore, cadence deviated significantly more in people with PD than in HE without input and particularly with intelligent feedback (both: p = 0.04). In PD, continuous and intelligent cueing induced significantly less deviations of cadence ( p = 0.006). Altogether, this suggests that intelligent cueing is a suitable alternative for the continuous mode during prolonged walking in PD, as it induced similar effects on gait without generating levels of fatigue beyond that of HE.

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          Most cited references39

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          Technology in Parkinson's disease: Challenges and opportunities.

          The miniaturization, sophistication, proliferation, and accessibility of technologies are enabling the capture of more and previously inaccessible phenomena in Parkinson's disease (PD). However, more information has not translated into a greater understanding of disease complexity to satisfy diagnostic and therapeutic needs. Challenges include noncompatible technology platforms, the need for wide-scale and long-term deployment of sensor technology (among vulnerable elderly patients in particular), and the gap between the "big data" acquired with sensitive measurement technologies and their limited clinical application. Major opportunities could be realized if new technologies are developed as part of open-source and/or open-hardware platforms that enable multichannel data capture sensitive to the broad range of motor and nonmotor problems that characterize PD and are adaptable into self-adjusting, individualized treatment delivery systems. The International Parkinson and Movement Disorders Society Task Force on Technology is entrusted to convene engineers, clinicians, researchers, and patients to promote the development of integrated measurement and closed-loop therapeutic systems with high patient adherence that also serve to (1) encourage the adoption of clinico-pathophysiologic phenotyping and early detection of critical disease milestones, (2) enhance the tailoring of symptomatic therapy, (3) improve subgroup targeting of patients for future testing of disease-modifying treatments, and (4) identify objective biomarkers to improve the longitudinal tracking of impairments in clinical care and research. This article summarizes the work carried out by the task force toward identifying challenges and opportunities in the development of technologies with potential for improving the clinical management and the quality of life of individuals with PD. © 2016 International Parkinson and Movement Disorder Society.
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            Comparison of the LASA Physical Activity Questionnaire with a 7-day diary and pedometer.

            First, to validate the LASA Physical Activity Questionnaire (LAPAQ) by a 7-day diary and a pedometer in older persons. Second, to assess the repeatability of the LAPAQ. Third, to compare the feasibility of these methods. The study was performed in a subsample (n=439, aged 69-92 years) of the Longitudinal Aging Study Amsterdam (LASA). The LAPAQ was completed twice (1998/1999, 1999/2000). Respondents completed a 7-day activity diary and wore a pedometer for 7 days (1999/2000). The LAPAQ was highly correlated with the 7-day diary (r=0.68, P<.001), and moderately with the pedometer (r=0.56, P<.001). The repeatability of the LAPAQ was reasonably good (weighted kappa: 0.65-0.75). The LAPAQ was completed in 5.7+/-2.7 min, and 0.5% of the respondents had missing values. The LAPAQ appears to be a valid and reliable instrument for classifying physical activity in older people. The LAPAQ was easier to use than the 7-day diary and pedometer.
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              Levodopa Is a Double-Edged Sword for Balance and Gait in People With Parkinson's Disease.

              The effects of levodopa on balance and gait function in people with Parkinson's disease (PD) is controversial. This study compared the relative responsiveness to l-dopa on six domains of balance and gait: postural sway in stance; gait pace; dynamic stability; gait initiation; arm swing; and turning in people with mild and severe PD, with and without dyskinesia.
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                Author and article information

                Contributors
                Journal
                Front Neurol
                Front Neurol
                Front. Neurol.
                Frontiers in Neurology
                Frontiers Media S.A.
                1664-2295
                06 April 2017
                2017
                : 8
                : 128
                Affiliations
                [1] 1Neuromotor Rehabilitation Research Group, Department of Rehabilitation Sciences, KU Leuven , Leuven, Belgium
                [2] 2Department of Electrical, Electronic and Information Engineering – Guglielmo Marconi, University of Bologna , Bologna, Italy
                [3] 3Faculty of Health Sciences, University of Sydney , Sydney, NSW, Australia
                Author notes

                Edited by: Antonio Suppa, Sapienza University of Rome, Italy

                Reviewed by: Angelo Quartarone, University of Messina, Italy; Graziella Madeo, National Institutes of Health (NIH), USA

                *Correspondence: Alice Nieuwboer, alice.nieuwboer@ 123456kuleuven.be

                Specialty section: This article was submitted to Movement Disorders, a section of the journal Frontiers in Neurology

                Article
                10.3389/fneur.2017.00128
                5382170
                28428770
                827e8c36-76f6-46ea-a10a-6f5388003038
                Copyright © 2017 Ginis, Heremans, Ferrari, Dockx, Canning and Nieuwboer.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 17 October 2016
                : 20 March 2017
                Page count
                Figures: 2, Tables: 4, Equations: 0, References: 47, Pages: 9, Words: 6690
                Funding
                Funded by: Seventh Framework Programme 10.13039/501100004963
                Award ID: 288516
                Categories
                Neuroscience
                Original Research

                Neurology
                parkinson’s disease,gait,fatigue,auditory cue,attentional strategy,verbal feedback,wearable sensors

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