Brenda Jeng1, Katie L J Cederberg2, Byron Lai3, Jeffer E Sasaki4, Marcas M Bamman5, Robert W Motl6. 1. Department of Physical Therapy, University of Alabama at Birmingham School of Health Professions, 360, 1720 2nd Ave S, Birmingham, AL 35233, United States. Electronic address: bjeng@uab.edu. 2. Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, United States. 3. Division of Pediatric Rehabilitation Medicine, University of Alabama at Birmingham, Birmingham, AL, United States. 4. Graduate Program in Physical Education, Graduate Program in Physical Education, Federal University of Triângulo Mineiro, Uberaba, Minas Gerais, Brazil. 5. University of Alabama at Birmingham Center for Exercise Medicine, University of Alabama at Birmingham, Birmingham, AL, United States; Department of Neurology, University of Alabama at Birmingham, Birmingham, AL, United States; Department of Medicine, University of Alabama at Birmingham, Birmingham, AL, United States; Department of Cell, Developmental, and Integrative Biology, University of Alabama at Birmingham, Birmingham, AL, United States; Geriatric Research Education and Clinical Center, Birmingham VA Medical Center, Birmingham, AL, United States. 6. Department of Physical Therapy, University of Alabama at Birmingham School of Health Professions, 360, 1720 2nd Ave S, Birmingham, AL 35233, United States.
Abstract
BACKGROUND: Persons with Parkinson's disease (PD) participate in low levels of physical activity. This has prompted interest in developing interventions targeting physical activity behavior in PD. However, the current cut-points to quantify moderate-to-vigorous physical activity (MVPA) developed for PD have been derived from a single, vertical axis using hip-worn accelerometers, and this cut-point may not be applicable for wrist-worn devices. Wrist-worn devices might improve accessibility and compliance with physical activity monitoring in PD. RESEARCH QUESTION: What is the relationship between wrist-based activity counts and energy expenditure during treadmill walking in persons with PD? Do cut-points for quantifying time spent in MVPA differ between persons with PD and controls matched by age and sex? METHODS: The sample included 26 persons with mild-to-moderate PD (Hoehn and Yahr stages 2-3) and 27 age- and sex-matched controls. Participants completed three, 6-minute bouts of walking on a treadmill at three increasing speeds. Vector magnitude was measured using ActiGraph GT3X+ accelerometer worn on the more affected side for persons with PD and the non-dominant side for controls. The rate of oxygen consumption, or energy expenditure, was measured using a portable, open-circuit spirometry system. RESULTS: Our results indicated a strong association between activity counts and energy expenditure for persons with PD and controls with R2 values of 0.94(0.07) and 0.95(0.06), respectively. Persons with PD had a cut-point of 2883(871) counts·min-1; this was significantly lower than the cut-point of 4389(1844) counts·min-1 for controls. CONCLUSION: We generated a PD-specific cut-point for wrist-worn ActiGraph accelerometers among persons with PD, and this was lower than controls. This disease-specific cut-point may provide more accurate measurements of time spent in MVPA in PD.
BACKGROUND: Persons with Parkinson's disease (PD) participate in low levels of physical activity. This has prompted interest in developing interventions targeting physical activity behavior in PD. However, the current cut-points to quantify moderate-to-vigorous physical activity (MVPA) developed for PD have been derived from a single, vertical axis using hip-worn accelerometers, and this cut-point may not be applicable for wrist-worn devices. Wrist-worn devices might improve accessibility and compliance with physical activity monitoring in PD. RESEARCH QUESTION: What is the relationship between wrist-based activity counts and energy expenditure during treadmill walking in persons with PD? Do cut-points for quantifying time spent in MVPA differ between persons with PD and controls matched by age and sex? METHODS: The sample included 26 persons with mild-to-moderate PD (Hoehn and Yahr stages 2-3) and 27 age- and sex-matched controls. Participants completed three, 6-minute bouts of walking on a treadmill at three increasing speeds. Vector magnitude was measured using ActiGraph GT3X+ accelerometer worn on the more affected side for persons with PD and the non-dominant side for controls. The rate of oxygen consumption, or energy expenditure, was measured using a portable, open-circuit spirometry system. RESULTS: Our results indicated a strong association between activity counts and energy expenditure for persons with PD and controls with R2 values of 0.94(0.07) and 0.95(0.06), respectively. Persons with PD had a cut-point of 2883(871) counts·min-1; this was significantly lower than the cut-point of 4389(1844) counts·min-1 for controls. CONCLUSION: We generated a PD-specific cut-point for wrist-worn ActiGraph accelerometers among persons with PD, and this was lower than controls. This disease-specific cut-point may provide more accurate measurements of time spent in MVPA in PD.
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Authors: Byron Lai; Jeffer E Sasaki; Brenda Jeng; Katie L Cederberg; Marcas M Bamman; Robert W Motl Journal: JMIR Rehabil Assist Technol Date: 2020-01-16