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      Simple Smartphone-Based Assessment of Gait Characteristics in Parkinson Disease: Validation Study

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          Abstract

          Background

          Parkinson disease (PD) is a common movement disorder. Patients with PD have multiple gait impairments that result in an increased risk of falls and diminished quality of life. Therefore, gait measurement is important for the management of PD.

          Objective

          We previously developed a smartphone-based dual-task gait assessment that was validated in healthy adults. The aim of this study was to test the validity of this gait assessment in people with PD, and to examine the association between app-derived gait metrics and the clinical and functional characteristics of PD.

          Methods

          Fifty-two participants with clinically diagnosed PD completed assessments of walking, Movement Disorder Society Unified Parkinson Disease Rating Scale III (UPDRS III), Montreal Cognitive Assessment (MoCA), Hamilton Anxiety (HAM-A), and Hamilton Depression (HAM-D) rating scale tests. Participants followed multimedia instructions provided by the app to complete two 20-meter trials each of walking normally (single task) and walking while performing a serial subtraction dual task (dual task). Gait data were simultaneously collected with the app and gold-standard wearable motion sensors. Stride times and stride time variability were derived from the acceleration and angular velocity signal acquired from the internal motion sensor of the phone and from the wearable sensor system.

          Results

          High correlations were observed between the stride time and stride time variability derived from the app and from the gold-standard system ( r=0.98-0.99, P<.001), revealing excellent validity of the app-based gait assessment in PD. Compared with those from the single-task condition, the stride time ( F 1,103 =14.1, P<.001) and stride time variability ( F 1,103 =6.8, P=.008) in the dual-task condition were significantly greater. Participants who walked with greater stride time variability exhibited a greater UPDRS III total score (single task: β=.39, P<.001; dual task: β=.37, P=.01), HAM-A (single-task: β=.49, P=.007; dual-task: β=.48, P=.009), and HAM-D (single task: β=.44, P=.01; dual task: β=.49, P=.009). Moreover, those with greater dual-task stride time variability (β=.48, P=.001) or dual-task cost of stride time variability (β=.44, P=.004) exhibited lower MoCA scores.

          Conclusions

          A smartphone-based gait assessment can be used to provide meaningful metrics of single- and dual-task gait that are associated with disease severity and functional outcomes in individuals with PD.

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          Most cited references41

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          A RATING SCALE FOR DEPRESSION

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            MDS clinical diagnostic criteria for Parkinson's disease.

            This document presents the Movement Disorder Society Clinical Diagnostic Criteria for Parkinson's disease (PD). The Movement Disorder Society PD Criteria are intended for use in clinical research but also may be used to guide clinical diagnosis. The benchmark for these criteria is expert clinical diagnosis; the criteria aim to systematize the diagnostic process, to make it reproducible across centers and applicable by clinicians with less expertise in PD diagnosis. Although motor abnormalities remain central, increasing recognition has been given to nonmotor manifestations; these are incorporated into both the current criteria and particularly into separate criteria for prodromal PD. Similar to previous criteria, the Movement Disorder Society PD Criteria retain motor parkinsonism as the core feature of the disease, defined as bradykinesia plus rest tremor or rigidity. Explicit instructions for defining these cardinal features are included. After documentation of parkinsonism, determination of PD as the cause of parkinsonism relies on three categories of diagnostic features: absolute exclusion criteria (which rule out PD), red flags (which must be counterbalanced by additional supportive criteria to allow diagnosis of PD), and supportive criteria (positive features that increase confidence of the PD diagnosis). Two levels of certainty are delineated: clinically established PD (maximizing specificity at the expense of reduced sensitivity) and probable PD (which balances sensitivity and specificity). The Movement Disorder Society criteria retain elements proven valuable in previous criteria and omit aspects that are no longer justified, thereby encapsulating diagnosis according to current knowledge. As understanding of PD expands, the Movement Disorder Society criteria will need continuous revision to accommodate these advances.
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              Gait and cognition: a complementary approach to understanding brain function and the risk of falling.

              Until recently, clinicians and researchers have performed gait assessments and cognitive assessments separately when evaluating older adults, but increasing evidence from clinical practice, epidemiological studies, and clinical trials shows that gait and cognition are interrelated in older adults. Quantifiable alterations in gait in older adults are associated with falls, dementia, and disability. At the same time, emerging evidence indicates that early disturbances in cognitive processes such as attention, executive function, and working memory are associated with slower gait and gait instability during single- and dual-task testing and that these cognitive disturbances assist in the prediction of future mobility loss, falls, and progression to dementia. This article reviews the importance of the interrelationship between gait and cognition in aging and presents evidence that gait assessments can provide a window into the understanding of cognitive function and dysfunction and fall risk in older people in clinical practice. To this end, the benefits of dual-task gait assessments (e.g., walking while performing an attention-demanding task) as a marker of fall risk are summarized. A potential complementary approach for reducing the risk of falls by improving certain aspects of cognition through nonpharmacological and pharmacological treatments is also presented. Untangling the relationship between early gait disturbances and early cognitive changes may be helpful in identifying older adults at risk of experiencing mobility decline, falls, and progression to dementia. © 2012, Copyright the Authors Journal compilation © 2012, The American Geriatrics Society.
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                Author and article information

                Contributors
                Journal
                JMIR Mhealth Uhealth
                JMIR Mhealth Uhealth
                JMU
                JMIR mHealth and uHealth
                JMIR Publications (Toronto, Canada )
                2291-5222
                February 2021
                19 February 2021
                : 9
                : 2
                : e25451
                Affiliations
                [1 ] Department of Neurology Beijing Tiantan Hospital Beijing China
                [2 ] The Second Clinical Medical College Jinan University Guangzhou China
                [3 ] Department of Geriatrics Shenzhen People’s Hospital Shenzhen, Guangdong China
                [4 ] The First Affiliated Hospital Southern University of Science and Technology Shenzhen, Guangdong China
                [5 ] Department of Computer Science The University of British Columbia Vancouver, BC Canada
                [6 ] Hinda and Arthur Marcus Institute for Aging Research Hebrew SeniorLife Roslindale, MA United States
                [7 ] Department of Hematology and Oncology Jingxi Campus, Capital Medical University Beijing ChaoYang Hospital Beijing China
                [8 ] Beth Israel Deaconess Medical Center Boston, MA United States
                [9 ] Harvard Medical School Boston, MA United States
                Author notes
                Corresponding Author: Junhong Zhou junhongzhou@ 123456hsl.harvard.edu
                Author information
                https://orcid.org/0000-0003-3609-4224
                https://orcid.org/0000-0003-1160-3678
                https://orcid.org/0000-0003-2670-3188
                https://orcid.org/0000-0003-1633-6265
                https://orcid.org/0000-0002-5241-0891
                https://orcid.org/0000-0002-3845-8020
                https://orcid.org/0000-0002-3145-457X
                https://orcid.org/0000-0002-6712-2286
                https://orcid.org/0000-0002-5191-1301
                https://orcid.org/0000-0002-6289-1748
                https://orcid.org/0000-0002-0776-237X
                https://orcid.org/0000-0002-8530-4622
                https://orcid.org/0000-0002-7931-7646
                Article
                v9i2e25451
                10.2196/25451
                7935653
                33605894
                9858d7a0-3715-43d7-aa41-d598df6bbdb3
                ©Dongning Su, Zhu Liu, Xin Jiang, Fangzhao Zhang, Wanting Yu, Huizi Ma, Chunxue Wang, Zhan Wang, Xuemei Wang, Wanli Hu, Brad Manor, Tao Feng, Junhong Zhou. Originally published in JMIR mHealth and uHealth (http://mhealth.jmir.org), 19.02.2021.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License ( https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR mHealth and uHealth, is properly cited. The complete bibliographic information, a link to the original publication on http://mhealth.jmir.org/, as well as this copyright and license information must be included.

                History
                : 2 November 2020
                : 24 November 2020
                : 8 December 2020
                : 20 January 2021
                Categories
                Original Paper
                Original Paper

                smartphone,gait,stride time (variability),validity,parkinson disease

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