Cited by 175Balance, Gait, and Falls PreventionContext-Aware Activity Recognition SystemsStroke Rehabilitation and Recovery

Continuous monitoring of turning in Parkinson’s disease: Rehabilitation potential

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Mancini, Martina, El-Gohary, Mahmoud, Pearson, Sean, McNames, James, Schlueter, Heather, Nutt, John G., King, Laurie A., Horak, Fay B.·2015·NeuroRehabilitation

Abstract

BACKGROUND: Difficulty turning during gait is a major contributor to mobility disability, falls and reduced quality of life in patients with Parkinson's disease (PD). Unfortunately, the assessment of mobility in the clinic may not adequately reflect typical mobility function or its variability during daily life. We hypothesized that quality of turning mobility, rather than overall quantity of activity, would be impaired in people with PD over seven days of continuous recording. METHODS: Thirteen subjects with PD and 8 healthy control subjects of similar age wore three Opal inertial sensors (on their belt and on each foot) throughout seven consecutive days during normal daily activities. Turning metrics included average and coefficient of variation (CV) of: (1) number of turns per hour, (2) turn angle amplitude, (3) turn duration, (4) turn mean velocity, and (5) number of steps per turn. Turning characteristics during continuous monitoring were compared with turning 90 and 180 degrees in a observed gait task. RESULTS: No differences were found between PD and control groups for observed turns. In contrast, subjects with PD showed impaired quality of turning compared to healthy control subjects (Turn Mean Velocity: 43.3 ± 4.8°/s versus 38 ± 5.7°/s, mean number of steps 1.7 ± 1.1 versus 3.2 ± 0.8). In addition, PD patients showed higher variability within the day and across days compared to controls. However, no differences were seen between PD and control subjects in the overall activity (number of steps per day or percent of the day walking) during the seven days. CONCLUSIONS: We show that continuous monitoring of natural turning during daily activities inside or outside the home is feasible for patients with PD and the elderly. This is the first study showing that continuous monitoring of turning was more sensitive to PD than observed turns. In addition, the quality of turning characteristics was more sensitive to PD than quantity of turns. Characterizing functional turning during daily activities will address a critical barrier to rehabilitation practice and clinical trials: objective measures of mobility characteristics in real-life environments.

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References 27 · Cited by 175

Authors
Mancini, M., El-Gohary, M., Pearson, S., McNames, J., Schlueter, H., Nutt, J. G., King, L. A., & Horak, F. B.
Affiliations
  • Oregon Health & Science University (US)
  • APDM, Inc., Portland, OR, USA
  • APDM (United States) (US)
Corresponding author
Mancini, Martina
Venue
NeuroRehabilitation
Published
2015-08-22
Volume
37
Issue
1
Pages
3-10
ISSN
  • 1053-8135 (ISSN-L)
  • 1878-6448
OpenAlex
W2267564478
Cited by
175
References
27
Citations by year
2026: 15 · 2025: 13 · 2024: 15 · 2023: 14 · 2022: 13 · 2021: 18 · 2020: 25 · 2019: 13 · 2018: 20 · 2017: 18 · 2016: 11
FWCI
43.49
Type
journal article
Language
en
Open access
Locations
  • Neurorehabilitation (publishedVersion)
  • PubMed (publishedVersion)
  • PubMed Central (acceptedVersion)
  • PDXScholar (Portland State University) (submittedVersion)
Funders
  • U.S. Department of Veterans Affairs (I01 RX001075)
  • Oregon Health and Science University
  • National Institutes of Health
  • National Institute of Neurological Disorders and Stroke (R41NS076088)
Topics
  • Health Sciences › Health Professions › Physical Therapy, Sports Therapy and Rehabilitation › Balance, Gait, and Falls Prevention
  • Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Context-Aware Activity Recognition Systems
  • Health Sciences › Medicine › Rehabilitation › Stroke Rehabilitation and Recovery
Keywords
Parkinson's disease, gait, inertial sensors, wearable sensors, continuous monitoring, daily activities, falls, rehabilitation
MeSH terms
Aged, Aged, 80 and over, Female, Gait, Humans, Male, Middle Aged, Parkinson Disease, Case-Control Studies, Range of Motion, Articular, Walking, Monitoring, Ambulatory, Remote Sensing Technology

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