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Brand YE, Kluge F, Palmerini L, Paraschiv-Ionescu A, Becker C, Cereatti A, Maetzler W, Sharrack B, Vereijken B, Yarnall AJ, Rochester L, Del Din S, Muller A, Buchman AS, Hausdorff JM, Perlman O. Automated Gait Detection in Older Adults during Daily-Living using Self-Supervised Learning of Wrist-Worn Accelerometer Data: Development and Validation of ElderNet. RESEARCH SQUARE 2024:rs.3.rs-4102403. [PMID: 38559043 PMCID: PMC10980143 DOI: 10.21203/rs.3.rs-4102403/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/04/2024]
Abstract
Progressive gait impairment is common in aging adults. Remote phenotyping of gait during daily living has the potential to quantify gait alterations and evaluate the effects of interventions that may prevent disability in the aging population. Here, we developed ElderNet, a self-supervised learning model for gait detection from wrist-worn accelerometer data. Validation involved two diverse cohorts, including over 1,000 participants without gait labels, as well as 83 participants with labeled data: older adults with Parkinson's disease, proximal femoral fracture, chronic obstructive pulmonary disease, congestive heart failure, and healthy adults. ElderNet presented high accuracy (96.43 ± 2.27), specificity (98.87 ± 2.15), recall (82.32 ± 11.37), precision (86.69 ± 17.61), and F1 score (82.92 ± 13.39). The suggested method yielded superior performance compared to two state-of-the-art gait detection algorithms, with improved accuracy and F1 score (p < 0.05). In an initial evaluation of construct validity, ElderNet identified differences in estimated daily walking durations across cohorts with different clinical characteristics, such as mobility disability (p < 0.001) and parkinsonism (p < 0.001). The proposed self-supervised gait detection method has the potential to serve as a valuable tool for remote phenotyping of gait function during daily living in aging adults.
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2
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Chahine LM, Simuni T. Role of novel endpoints and evaluations of response in Parkinson disease. HANDBOOK OF CLINICAL NEUROLOGY 2023; 193:325-345. [PMID: 36803820 DOI: 10.1016/b978-0-323-85555-6.00010-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/18/2023]
Abstract
With progress in our understanding of Parkinson disease (PD) and other neurodegenerative disorders, from clinical features to imaging, genetic, and molecular characterization comes the opportunity to refine and revise how we measure these diseases and what outcome measures are used as endpoints in clinical trials. While several rater-, patient-, and milestone-based outcomes for PD exist that may serve as clinical trial endpoints, there remains an unmet need for endpoints that are clinically meaningful, patient centric while also being more objective and quantitative, less susceptible to effects of symptomatic therapy (for disease-modification trials), and that can be measured over a short period and yet accurately represent longer-term outcomes. Several novel outcomes that may be used as endpoints in PD clinical trials are in development, including digital measures of signs and symptoms, as well a growing array of imaging and biospecimen biomarkers. This chapter provides an overview of the state of PD outcome measures as of 2022, including considerations for selection of clinical trial endpoints in PD, advantages and limitations of existing measures, and emerging potential novel endpoints.
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Affiliation(s)
- Lana M Chahine
- Department of Neurology, University of Pittsburgh, Pittsburgh, PA, United States
| | - Tanya Simuni
- Department of Neurology, Northwestern University Feinberg School of Medicine, Chicago, IL, United States.
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3
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Xu Z, Shen B, Tang Y, Wu J, Wang J. Deep Clinical Phenotyping of Parkinson's Disease: Towards a New Era of Research and Clinical Care. PHENOMICS (CHAM, SWITZERLAND) 2022; 2:349-361. [PMID: 36939759 PMCID: PMC9590510 DOI: 10.1007/s43657-022-00051-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/24/2021] [Revised: 03/12/2022] [Accepted: 03/28/2022] [Indexed: 11/27/2022]
Abstract
Despite recent advances in technology, clinical phenotyping of Parkinson's disease (PD) has remained relatively limited as current assessments are mainly based on empirical observation and subjective categorical judgment at the clinic. A lack of comprehensive, objective, and quantifiable clinical phenotyping data has hindered our capacity to diagnose, assess patients' conditions, discover pathogenesis, identify preclinical stages and clinical subtypes, and evaluate new therapies. Therefore, deep clinical phenotyping of PD patients is a necessary step towards understanding PD pathology and improving clinical care. In this review, we present a growing community consensus and perspective on how to clinically phenotype this disease, that is, to phenotype the entire course of disease progression by integrating capacity, performance, and perception approaches with state-of-the-art technology. We also explore the most studied aspects of PD deep clinical phenotypes, namely, bradykinesia, tremor, dyskinesia and motor fluctuation, gait impairment, speech impairment, and non-motor phenotypes.
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Affiliation(s)
- Zhiheng Xu
- Department of Neurology and National Research Center for Aging and Medicine & National Center for Neurological Disorders, State Key Laboratory of Medical Neurobiology, Huashan Hospital, Fudan University, Shanghai, 200040 China
| | - Bo Shen
- Department of Neurology and National Research Center for Aging and Medicine & National Center for Neurological Disorders, State Key Laboratory of Medical Neurobiology, Huashan Hospital, Fudan University, Shanghai, 200040 China
| | - Yilin Tang
- Department of Neurology and National Research Center for Aging and Medicine & National Center for Neurological Disorders, State Key Laboratory of Medical Neurobiology, Huashan Hospital, Fudan University, Shanghai, 200040 China
| | - Jianjun Wu
- Department of Neurology and National Research Center for Aging and Medicine & National Center for Neurological Disorders, State Key Laboratory of Medical Neurobiology, Huashan Hospital, Fudan University, Shanghai, 200040 China
| | - Jian Wang
- Department of Neurology and National Research Center for Aging and Medicine & National Center for Neurological Disorders, State Key Laboratory of Medical Neurobiology, Huashan Hospital, Fudan University, Shanghai, 200040 China
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Mirelman A, Siderowf A, Chahine L. Outcome Assessment in Parkinson Disease Prevention Trials: Utility of Clinical and Digital Measures. Neurology 2022; 99:52-60. [PMID: 35970590 DOI: 10.1212/wnl.0000000000200236] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2021] [Accepted: 01/21/2022] [Indexed: 11/15/2022] Open
Abstract
BACKGROUND AND OBJECTIVES The prodromal phase of Parkinson disease (PD) is accompanied by subtle clinical signs that are not sufficient for diagnosis but could potentially be measured in the context of clinical trials of therapies intended to delay or prevent more definitive clinical features. The objective of this study was to review the available literature on the presence and time course of subtle motor features in prodromal PD in the context of planning for possible clinical trials. METHODS We reviewed the available literature based on expert opinion. We considered a range of outcomes including measurement of clinical features, patient-reported outcomes, digital markers, and clinical diagnosis. RESULTS We considered these features and measures in the context of patient stratification, intermediate outcomes, and clinically relevant end points, including phenoconversion. DISCUSSION Substantial progress has been made in understanding how motor features evolve in the period immediately before a PD diagnosis. Digital measures hold substantial progress for measurement precision and may be additionally relevant because they can be used in naturalistic environments outside the clinic. Future studies should focus on advancing digital sensor technology and analysis and developing methods to implement available methods, particularly determination of a clinical diagnosis of PD, in a clinical trial context.
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Affiliation(s)
- Anat Mirelman
- From the Sackler School of Medicine and Sagol School of Neuroscience (A.M.), Tel Aviv University, Israel; Department of Neurology (A.S.), Perelman School of Medicine, University of Pennsylvania, Philadelphia; and Department of Neurology (L.C.), University of Pittsburgh, PA
| | - Andrew Siderowf
- From the Sackler School of Medicine and Sagol School of Neuroscience (A.M.), Tel Aviv University, Israel; Department of Neurology (A.S.), Perelman School of Medicine, University of Pennsylvania, Philadelphia; and Department of Neurology (L.C.), University of Pittsburgh, PA.
| | - Lana Chahine
- From the Sackler School of Medicine and Sagol School of Neuroscience (A.M.), Tel Aviv University, Israel; Department of Neurology (A.S.), Perelman School of Medicine, University of Pennsylvania, Philadelphia; and Department of Neurology (L.C.), University of Pittsburgh, PA
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5
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Buchman AS, Bennett DA. Mixed Neuropathologies, Neural Motor Resilience and Target Discovery for Therapies of Late-Life Motor Impairment. Front Hum Neurosci 2022; 16:853330. [PMID: 35399360 PMCID: PMC8987574 DOI: 10.3389/fnhum.2022.853330] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2022] [Accepted: 02/21/2022] [Indexed: 01/14/2023] Open
Abstract
By age 85, most adults manifest some degree of motor impairment. However, in most individuals a specific etiology for motor decline and treatment to modify its inexorable progression cannot be identified. Recent clinical-pathologic studies provide evidence that mixed-brain pathologies are commonly associated with late-life motor impairment. Yet, while nearly all older adults show some degree of accumulation of Alzheimer's disease and related dementias (ADRD) pathologies, the extent to which these pathologies contribute to motor decline varies widely from person to person. Slower or faster than expected motor decline in the presence of brain injury and/or pathology has been conceptualized as more or less "resilience" relative to the average person This suggests that other factors, such as lifestyles or other neurobiologic indices may offset or exacerbate the negative effects of pathologies via other molecular pathways. The mechanisms underlying neural motor resilience are just beginning to be illuminated. Unlike its cousin, cognitive resilience which is restricted to neural mechanisms above the neck, the motor system extends the total length of the CNS and beyond the CNS to reach muscle and musculoskeletal structures, all of which are crucial for motor function. Building on prior work, we propose that by isolating motor decline unrelated to neuropathologies and degeneration, investigators can identify genes and proteins that may provide neural motor resilience. Elucidating these molecular mechanisms will advance our understanding of the heterogeneity of late-life motor impairment. This approach will also provide high value therapeutic targets for drug discovery of therapies that may offset the negative motor consequences of CNS pathologies that are currently untreatable.
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Affiliation(s)
- Aron S. Buchman
- Rush Alzheimer’s Disease Center, Rush University Medical Center, Chicago, IL, United States,Department of Neurological Sciences, Rush University Medical Center, Chicago, IL, United States,*Correspondence: Aron S. Buchman,
| | - David A. Bennett
- Rush Alzheimer’s Disease Center, Rush University Medical Center, Chicago, IL, United States,Department of Neurological Sciences, Rush University Medical Center, Chicago, IL, United States
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6
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Legaria-Santiago VK, Sánchez-Fernández LP, Sánchez-Pérez LA, Garza-Rodríguez A. Computer models evaluating hand tremors in Parkinson's disease patients. Comput Biol Med 2022; 140:105059. [PMID: 34847385 DOI: 10.1016/j.compbiomed.2021.105059] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2021] [Revised: 11/12/2021] [Accepted: 11/20/2021] [Indexed: 11/03/2022]
Abstract
One of the most characteristic signs of Parkinson's disease (PD) is hand tremor. The MDS-UPDRS scale evaluates different aspects of the disease. The tremor score is a part of the MDS-UPDRS scale, which provides instructions for rating it, by observation, with an integer from 0 to 4. Nevertheless, this form of assessment is subjective and dependent on visual acuity, clinical judgment, and even the mood of the individual examiner. On the other hand, in many cases, existing computational models proposed to resolve the disadvantages of the MDS-UPDRS scale may have uncertainty in differentiating a category of a slight Parkinson tremor from voluntary movements. In this study, 554 measurements from Parkinson's patients, and 60 measurements from healthy subjects, were recorded with inertial sensors placed on the back of each hand. Five biomechanical indicators characterised the hand tremor. With these indicators, the three fuzzy inference models proposed can differentiate, in the first instance, the presence of postural or resting tremor from a normal movement of the hand, and if detected, to determine its severity. The fuzzy inference models allowed following the criteria of the MDS-UPDRS scale, providing an evaluation with an accuracy of two decimal digits and which, due to its simplicity, can be implemented in clinical environments. The assessments of three experts validated the computer model.
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Affiliation(s)
| | - Luis Pastor Sánchez-Fernández
- Instituto Politécnico Nacional, Centro de Investigación en Computación, Juan de Dios Bátiz, 07738 México City, Mexico.
| | - Luis Alejandro Sánchez-Pérez
- Electrical and Computer Engineering Department, University of Michigan, 4901 Evergreen Rd, Dearborn, MI 48128, USA
| | - Alejandro Garza-Rodríguez
- Instituto Politécnico Nacional, Centro de Investigación en Computación, Juan de Dios Bátiz, 07738 México City, Mexico
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7
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Instrumented Timed Up and Go Test Using Inertial Sensors from Consumer Wearable Devices. Artif Intell Med 2022. [DOI: 10.1007/978-3-031-09342-5_14] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
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8
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Buchanan SM, Richards M, Schott JM, Schrag A. Mild Parkinsonian Signs: A Systematic Review of Clinical, Imaging, and Pathological Associations. Mov Disord 2021; 36:2481-2493. [PMID: 34562045 DOI: 10.1002/mds.28777] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2021] [Revised: 07/29/2021] [Accepted: 08/09/2021] [Indexed: 11/07/2022] Open
Abstract
Mild parkinsonian signs (MPS) have been widely studied during the past 3 decades and proposed as a risk marker for neurodegenerative disease. This systematic review explores the epidemiology, clinical and prognostic associations, radiological features, and pathological findings associated with MPS in older adults free from neurodegenerative disease. We find that MPS as currently defined are strongly associated with increasing age and increased risk of development of Parkinson's disease (PD), all-cause dementia, disability, and death. Positive associations with later PD are found mainly in younger populations and those with other features of prodromal PD. There are currently no consistent radiological findings for MPS, and pathological studies have shown that MPS, at least in the oldest old, are often underpinned by mixed neuropathologies, including those associated with Alzheimer's disease, cerebrovascular disease, nigral neuronal loss, and Lewy bodies. Different subcategories of MPS appear to convey varying risk and specificity for PD and other outcomes. MPS overall are not specific for parkinsonian disorders and, although associated with increased risk of PD, can reflect multiple pathologies, particularly in older individuals. "Mild motor signs" appears a more appropriate term to avoid prognostic and pathological implications, and larger future studies to prospectively examine outcomes and associations of specific MPS subcategories are required. © 2021 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.
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Affiliation(s)
- Sarah M Buchanan
- Dementia Research Centre, University College London Institute of Neurology, University College London, London, United Kingdom
- Otago Medical School, University of Otago, Dunedin, New Zealand
| | - Marcus Richards
- Medical Research Council Unit for Lifelong Health and Ageing at UCL, London, United Kingdom
| | - Jonathan M Schott
- Dementia Research Centre, University College London Institute of Neurology, University College London, London, United Kingdom
| | - Anette Schrag
- Department of Clinical Neurosciences, UCL Institute of Neurology University College London, London, United Kingdom
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9
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Dlamini WW, Nielsen S, Ushe M, Nelson G, Racette BA. A Rapid Motor Task-Based Screening Tool for Parkinsonism in Community-Based Studies. Front Neurol 2021; 12:653066. [PMID: 34054697 PMCID: PMC8155367 DOI: 10.3389/fneur.2021.653066] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2021] [Accepted: 04/12/2021] [Indexed: 11/28/2022] Open
Abstract
Background: The prevalence of parkinsonism in developing countries is largely unknown due to difficulty in ascertainment because access to neurologists is often limited. Objective: Develop and validate a parkinsonism screening tool using objective motor task-based tests that can be administered by non-clinicians. Methods: In a cross-sectional population-based sample from South Africa, we evaluated 315 adults, age >40, from an Mn-exposed (smelter) community, using the Unified Parkinson Disease Rating Scale motor subsection 3 (UPDRS3), Purdue grooved pegboard, and kinematic-UPDRS3-based motor tasks. In 275 participants (training dataset), we constructed a linear regression model to predict UPDRS3. We selected motor task summary measures independently associated with UPDRS3 (p < 0.05). We validated the model internally in the remaining 40 participants from the manganese-exposed community (test dataset) using the area under the receiver operating characteristic curve (AUC), and externally in another population-based sample of 90 participants from another South African community with only background levels of environmental Mn exposure. Results: The mean UPDRS3 score in participants from the Mn-exposed community was 9.1 in both the training and test datasets (standard deviation = 6.4 and 6.1, respectively). Together, 57 (18.1%) participants in this community had a UPDRS3 ≥ 15, including three with Parkinson's disease. In the non-exposed community, the mean UPDRS3 was 3.9 (standard deviation = 4.3). Three (3.3%) had a UPDRS3 ≥ 15. Grooved pegboard time and mean velocity for hand rotation and finger tapping tasks were strongly associated with UPDRS3. Using these motor task summary measures and age, the UPDRS3 predictive model performed very well. In the test dataset, AUCs were 0.81 (95% CI 0.68, 0.94) and 0.91 (95% CI 0.81, 1.00) for cut points for neurologist-assessed UPDRS3 ≥ 10 and UPDRS3 ≥ 15, respectively. In the external validation dataset, the AUC was 0.85 (95% CI 0.73, 0.97) for UPDRS3 ≥ 10. AUCs were 0.76–0.82 when excluding age. Conclusion: A predictive model based on a series of objective motor tasks performs very well in assessing severity of parkinsonism in both Mn-exposed and non-exposed population-based cohorts.
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Affiliation(s)
- Wendy W Dlamini
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, United States
| | - Searles Nielsen
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, United States
| | - Mwiza Ushe
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, United States
| | - Gill Nelson
- Faculty of Health Sciences, School of Public Health, University of the Witwatersrand, Parktown, Johannesburg, South Africa.,Institute for Global Health, University College London, London, United Kingdom
| | - Brad A Racette
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, United States.,Faculty of Health Sciences, School of Public Health, University of the Witwatersrand, Parktown, Johannesburg, South Africa
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10
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Mobility impact and well-being in later life: A multidisciplinary systematic review. RESEARCH IN TRANSPORTATION ECONOMICS 2021; 86:100975. [PMCID: PMC7547325 DOI: 10.1016/j.retrec.2020.100975] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/14/2020] [Revised: 09/19/2020] [Accepted: 10/02/2020] [Indexed: 06/01/2023]
Abstract
In modern societies, the understanding of how active mobility affects the elderly's psycho-physical well-being is crucial to design ageing-friendly transport measures. From a multidisciplinary perspective, this systematic review points out the mobility impact on three elements of the EU Active Ageing Index: health, independence and social connectedness. By scanning four databases (Scopus, Web of Science, PubMed, and TRID), 3727 peer-reviewed papers published in the last decade were found, of which 57 met the inclusion criteria. The screening process was conducted following the PRISMA protocol and registered to the database PROSPERO, while the quality assessment was done using the Mixed Methods Appraisal Tool. More than 80% of the papers showed that an active mobility prevents psycho-physical harms, while only few papers study the relation of mobility with independence and social inclusion, to reduce the need for assistance and the related public expenditures. The findings of this review give important information both to transportation researchers and policymakers and companies, underlining the need for further research as well as investments in targeted age-friendly transport systems. The Covid-19 emergency has further underlined the importance of this issue, being the elderly one of the more disadvantaged and frailer social group.
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11
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Maidan I, Mirelman A, Hausdorff JM, Stern Y, Habeck CG. Distinct cortical thickness patterns link disparate cerebral cortex regions to select mobility domains. Sci Rep 2021; 11:6600. [PMID: 33758214 PMCID: PMC7988162 DOI: 10.1038/s41598-021-85058-z] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2020] [Accepted: 02/19/2021] [Indexed: 01/03/2023] Open
Abstract
The cortical control of gait and mobility involves multiple brain regions. Therefore, one could speculate that the association between specific spatial patterns of cortical thickness may be differentially associated with different mobility domains. To test this possibility, 115 healthy participants aged 27–82 (mean 60.5 ± 13.8) underwent a mobility assessment (usual-walk, dual-task walk, Timed Up and Go) and MRI scan. Ten mobility domains of relatively simple (e.g., usual-walking) and complex tasks (i.e., dual task walking, turns, transitions) and cortical thickness of 68 ROIs were extracted. All associations between mobility and cortical thickness were controlled for age and gender. Scaled Subprofile Modelling (SSM), a PCA-regression, identified thickness patterns that were correlated with the individual mobility domains, controlling for multiple comparisons. We found that lower mean global cortical thickness was correlated with worse general mobility (r = − 0.296, p = 0.003), as measured by the time to complete the Timed Up and Go test. Three distinct patterns of cortical thickness were associated with three different gait domains during simple, usual-walking: pace, rhythm, and symmetry. In contrast, cortical thickness patterns were not related to the more complex mobility domains. These findings demonstrate that robust and topographically distinct cortical thickness patterns are linked to select mobility domains during relatively simple walking, but not to more complex aspects of mobility. Functional connectivity may play a larger role in the more complex aspects of mobility.
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Affiliation(s)
- Inbal Maidan
- Laboratory of Early Markers of Neurodegeneration, Center for the Study of Movement, Cognition, and Mobility, Neurological Institute, Tel Aviv Sourasky Medical Center, 6 Weizmann Street, 64239, Tel Aviv, Israel. .,Department of Neurology, Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel. .,Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, Israel.
| | - Anat Mirelman
- Laboratory of Early Markers of Neurodegeneration, Center for the Study of Movement, Cognition, and Mobility, Neurological Institute, Tel Aviv Sourasky Medical Center, 6 Weizmann Street, 64239, Tel Aviv, Israel.,Department of Neurology, Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel.,Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, Israel
| | - Jeffrey M Hausdorff
- Laboratory of Early Markers of Neurodegeneration, Center for the Study of Movement, Cognition, and Mobility, Neurological Institute, Tel Aviv Sourasky Medical Center, 6 Weizmann Street, 64239, Tel Aviv, Israel.,Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, Israel.,Department of Physical Therapy, Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel.,Department of Orthopaedic Surgery, Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL, USA
| | - Yaakov Stern
- Cognitive Neuroscience Division of the Department of Neurology, Taub Institute for Research on Alzheimer's Disease and the Aging Brain and G.H. Sergievsky Center, Columbia University Irving Medical Center, New York, NY, USA
| | - Christian G Habeck
- Cognitive Neuroscience Division of the Department of Neurology, Taub Institute for Research on Alzheimer's Disease and the Aging Brain and G.H. Sergievsky Center, Columbia University Irving Medical Center, New York, NY, USA
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12
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Digital Technology in Movement Disorders: Updates, Applications, and Challenges. Curr Neurol Neurosci Rep 2021; 21:16. [PMID: 33660110 PMCID: PMC7928701 DOI: 10.1007/s11910-021-01101-6] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/21/2021] [Indexed: 12/14/2022]
Abstract
Purpose of Review Digital technology affords the opportunity to provide objective, frequent, and sensitive assessment of disease outside of the clinic environment. This article reviews recent literature on the application of digital technology in movement disorders, with a focus on Parkinson’s disease (PD) and Huntington’s disease. Recent Findings Recent research has demonstrated the ability for digital technology to discriminate between individuals with and without PD, identify those at high risk for PD, quantify specific motor features, predict clinical events in PD, inform clinical management, and generate novel insights. Summary Digital technology has enormous potential to transform clinical research and care in movement disorders. However, more work is needed to better validate existing digital measures, including in new populations, and to develop new more holistic digital measures that move beyond motor features.
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13
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Quantitative mobility measures complement the MDS-UPDRS for characterization of Parkinson's disease heterogeneity. Parkinsonism Relat Disord 2021; 84:105-111. [PMID: 33607526 DOI: 10.1016/j.parkreldis.2021.02.006] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/14/2020] [Revised: 12/28/2020] [Accepted: 02/03/2021] [Indexed: 11/20/2022]
Abstract
INTRODUCTION Emerging technologies show promise for enhanced characterization of Parkinson's Disease (PD) motor manifestations. We evaluated quantitative mobility measures from a wearable device compared to the conventional motor assessment, the Movement Disorders Society-Unified PD Rating Scale part III (motor MDS-UPDRS). METHODS We evaluated 176 PD subjects (mean age 65, 65% male, 66% H&Y stage 2) during routine clinic visits using the motor MDS-UPDRS and a 10-min motor protocol with a body-fixed sensor (DynaPort MT, McRoberts BV), including the 32-ft walk, Timed Up and Go (TUG), and standing posture with eyes closed. Regression models examined 12 quantitative mobility measures for associations with (i) motor MDS-UPDRS, (ii) motor subtype (tremor dominant vs. postural instability/gait difficulty), (iii) Montreal Cognitive Assessment (MoCA), and (iv) physical functioning disability (PROMIS-29). All analyses included age, gender, and disease duration as covariates. Models iii-iv were secondarily adjusted for motor MDS-UPDRS. RESULTS Quantitative mobility measures from gait, TUG transitions, turning, and posture were significantly associated with motor MDS-UPDRS (7 of 12 measures, p < 0.05) and motor subtype (6 of 12 measures, p < 0.05). Compared with motor MDS-UPDRS, several quantitative mobility measures accounted for a 1.5- or 1.9-fold increased variance in either cognition or physical functioning disability, respectively. Among minimally-impaired subjects in the bottom quartile of motor MDS-UPDRS, including subjects with normal gait exam, the measures captured substantial residual motor heterogeneity. CONCLUSION Clinic-based quantitative mobility assessments using a wearable sensor captured features of motor performance beyond those obtained with the motor MDS-UPDRS and may offer enhanced characterization of disease heterogeneity.
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14
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Dibble LE, Ellis TD. The sobering and puzzling reality of rehabilitation referrals for Parkinson disease. Parkinsonism Relat Disord 2021; 83:113-114. [PMID: 33551313 DOI: 10.1016/j.parkreldis.2021.01.016] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/20/2020] [Revised: 01/18/2021] [Accepted: 01/21/2021] [Indexed: 11/17/2022]
Affiliation(s)
- Leland E Dibble
- Department of Physical Therapy and Athletic Training, University of Utah, 520 Wakara Way, Salt Lake City, UT, 84108, USA.
| | - Theresa D Ellis
- Department of Physical Therapy and Athletic Training, Boston University College of Health and Rehabilitation Sciences: Sargent College, 635 Commonwealth Avenue, Boston, MA, 02215, USA.
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15
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Luis-Martínez R, Monje MHG, Antonini A, Sánchez-Ferro Á, Mestre TA. Technology-Enabled Care: Integrating Multidisciplinary Care in Parkinson's Disease Through Digital Technology. Front Neurol 2020; 11:575975. [PMID: 33250846 PMCID: PMC7673441 DOI: 10.3389/fneur.2020.575975] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2020] [Accepted: 08/24/2020] [Indexed: 11/13/2022] Open
Abstract
Parkinson's disease (PD) management requires the involvement of movement disorders experts, other medical specialists, and allied health professionals. Traditionally, multispecialty care has been implemented in the form of a multidisciplinary center, with an inconsistent clinical benefit and health economic impact. With the current capabilities of digital technologies, multispecialty care can be reshaped to reach a broader community of people with PD in their home and community. Digital technologies have the potential to connect patients with the care team beyond the traditional sparse clinical visit, fostering care continuity and accessibility. For example, video conferencing systems can enable the remote delivery of multispecialty care. With big data analyses, wearable and non-wearable technologies using artificial intelligence can enable the remote assessment of patients' conditions in their natural home environment, promoting a more comprehensive clinical evaluation and empowering patients to monitor their disease. These advances have been defined as technology-enabled care (TEC). We present examples of TEC under development and describe the potential challenges to achieve a full integration of technology to address complex care needs in PD.
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Affiliation(s)
- Raquel Luis-Martínez
- Department of Neurosciences, University of Basque Country (UPV/EHU), Leioa, Spain
- Department of Neurosciences (DNS), Padova University, Padova, Italy
| | - Mariana H G Monje
- HM CINAC, Hospital Universitario HM Puerta del Sur, Universidad CEU-San Pablo, Madrid, Spain
| | - Angelo Antonini
- Department of Neurosciences (DNS), Padova University, Padova, Italy
| | - Álvaro Sánchez-Ferro
- HM CINAC, Hospital Universitario HM Puerta del Sur, Universidad CEU-San Pablo, Madrid, Spain
| | - Tiago A Mestre
- Division of Neurology, Department of Medicine, The Ottawa Hospital Research Institute, Parkinson's Disease and Movement Disorders Center, The University of Ottawa Brain Research Institute, Ottawa, ON, Canada
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