Literature DB >> 29614664

Gait in Mild Alzheimer's Disease: Feasibility of Multi-Center Measurement in the Clinic and Home with Body-Worn Sensors: A Pilot Study.

Ríona Mc Ardle1, Rosie Morris1, Aodhán Hickey1, Silvia Del Din1, Ivan Koychev2, Roger N Gunn3,4, Jennifer Lawson2, Giovanna Zamboni2, Basil Ridha5, Barbara J Sahakian6, James B Rowe7, Alan Thomas1, Henrik Zetterberg8,9,10,11, Clare MacKay2, Simon Lovestone2, Lynn Rochesteron1.   

Abstract

Gait is emerging as a potential diagnostic tool for cognitive decline. The 'Deep and Frequent Phenotyping for Experimental Medicine in Dementia Study' (D&FP) is a multicenter feasibility study embedded in the United Kingdom Dementia Platform designed to determine participant acceptability and feasibility of extensive and repeated phenotyping to determine the optimal combination of biomarkers to detect disease progression and identify early risk of Alzheimer's disease (AD). Gait is included as a clinical biomarker. The tools to quantify gait in the clinic and home, and suitability for multi-center application have not been examined. Six centers from the National Institute for Health Research Translational Research Collaboration in Dementia initiative recruited 20 individuals with early onset AD. Participants wore a single wearable (tri-axial accelerometer) and completed both clinic-based and free-living gait assessment. A series of macro (behavioral) and micro (spatiotemporal) characteristics were derived from the resultant data using previously validated algorithms. Results indicate good participant acceptability, and potential for use of body-worn sensors in both the clinic and the home. Recommendations for future studies have been provided. Gait has been demonstrated to be a feasible and suitable measure, and future research should examine its suitability as a biomarker in AD.

Entities:  

Keywords:  Alzheimer’s disease; cognition; free-living; gait; phenotyping; wearables

Mesh:

Year:  2018        PMID: 29614664     DOI: 10.3233/JAD-171116

Source DB:  PubMed          Journal:  J Alzheimers Dis        ISSN: 1387-2877            Impact factor:   4.472


  12 in total

1.  Aβ42/Aβ40 and Aβ42/Aβ38 Ratios Are Associated with Measures of Gait Variability and Activities of Daily Living in Mild Alzheimer's Disease: A Pilot Study.

Authors:  Ivan Koychev; Brook Galna; Henrik Zetterberg; Jennifer Lawson; Giovanna Zamboni; Basil H Ridha; James B Rowe; Alan Thomas; Robert Howard; Paresh Malhotra; Craig Ritchie; Simon Lovestone; Lynn Rochester
Journal:  J Alzheimers Dis       Date:  2018       Impact factor: 4.472

2.  Deep and Frequent Phenotyping study protocol: an observational study in prodromal Alzheimer's disease.

Authors:  Ivan Koychev; Jennifer Lawson; Tharani Chessell; Clare Mackay; Roger Gunn; Barbara Sahakian; James B Rowe; Alan J Thomas; Lynn Rochester; Dennis Chan; Brian Tom; Paresh Malhotra; Clive Ballard; Iain Chessell; Craig W Ritchie; Vanessa Raymont; Iracema Leroi; Imre Lengyel; Matt Murray; David L Thomas; John Gallacher; Simon Lovestone
Journal:  BMJ Open       Date:  2019-03-23       Impact factor: 2.692

Review 3.  The Role of Movement Analysis in Diagnosing and Monitoring Neurodegenerative Conditions: Insights from Gait and Postural Control.

Authors:  Christopher Buckley; Lisa Alcock; Ríona McArdle; Rana Zia Ur Rehman; Silvia Del Din; Claudia Mazzà; Alison J Yarnall; Lynn Rochester
Journal:  Brain Sci       Date:  2019-02-06

Review 4.  IoT Wearable Sensors and Devices in Elderly Care: A Literature Review.

Authors:  Thanos G Stavropoulos; Asterios Papastergiou; Lampros Mpaltadoros; Spiros Nikolopoulos; Ioannis Kompatsiaris
Journal:  Sensors (Basel)       Date:  2020-05-16       Impact factor: 3.576

5.  Gait Disturbances are Associated with Increased Cognitive Impairment and Cerebrospinal Fluid Tau Levels in a Memory Clinic Cohort.

Authors:  Marijn Muurling; Hanneke F M Rhodius-Meester; Juha Pärkkä; Mark van Gils; Kristian S Frederiksen; Marie Bruun; Steen G Hasselbalch; Hilkka Soininen; Sanna-Kaisa Herukka; Merja Hallikainen; Charlotte E Teunissen; Pieter Jelle Visser; Philip Scheltens; Wiesje M van der Flier; Jussi Mattila; Jyrki Lötjönen; Casper de Boer
Journal:  J Alzheimers Dis       Date:  2020       Impact factor: 4.472

6.  The Impact of Environment on Gait Assessment: Considerations from Real-World Gait Analysis in Dementia Subtypes.

Authors:  Ríona Mc Ardle; Silvia Del Din; Paul Donaghy; Brook Galna; Alan J Thomas; Lynn Rochester
Journal:  Sensors (Basel)       Date:  2021-01-26       Impact factor: 3.576

7.  Machine learning classifies predictive kinematic features in a mouse model of neurodegeneration.

Authors:  Ruyi Huang; Ali A Nikooyan; Bo Xu; M Selvan Joseph; Hamidreza Ghasemi Damavandi; Nathan von Trotha; Lilian Li; Ashok Bhattarai; Deeba Zadeh; Yeji Seo; Xingquan Liu; Patrick A Truong; Edward H Koo; J C Leiter; Daniel C Lu
Journal:  Sci Rep       Date:  2021-02-17       Impact factor: 4.379

8.  Continuous gait monitoring discriminates community-dwelling mild Alzheimer's disease from cognitively normal controls.

Authors:  Vijay R Varma; Rahul Ghosal; Inbar Hillel; Dmitri Volfson; Jordan Weiss; Jacek Urbanek; Jeffrey M Hausdorff; Vadim Zipunnikov; Amber Watts
Journal:  Alzheimers Dement (N Y)       Date:  2021-02-05

9.  Detection of Wandering Behaviors Using a Body-Worn Inertial Sensor in Patients With Cognitive Impairment: A Feasibility Study.

Authors:  Rebecca J Kamil; Dara Bakar; Matthew Ehrenburg; Eric X Wei; Alexandra Pletnikova; Grace Xiao; Esther S Oh; Martina Mancini; Yuri Agrawal
Journal:  Front Neurol       Date:  2021-03-11       Impact factor: 4.003

10.  Exhaustive Description of the System Architecture and Prototype Implementation of an IoT-Based eHealth Biometric Monitoring System for Elders in Independent Living.

Authors:  Cristian Vizitiu; Călin Bîră; Adrian Dinculescu; Alexandru Nistorescu; Mihaela Marin
Journal:  Sensors (Basel)       Date:  2021-03-06       Impact factor: 3.576

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