scholarly journals Accelerometer output and its association with energy expenditure in persons with mild-to-moderate Parkinson’s disease

PLoS ONE ◽  
2020 ◽  
Vol 15 (11) ◽  
pp. e0242136
Author(s):  
Brenda Jeng ◽  
Katie L. J. Cederberg ◽  
Byron Lai ◽  
Jeffer E. Sasaki ◽  
Marcas M. Bamman ◽  
...  
Keyword(s):  
Physical Activity ◽  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Energy Expenditure ◽  
Vigorous Physical Activity ◽  
Strong Association ◽  
Future Research ◽  
Cut Point ◽  
Actigraph Accelerometer ◽  
Significant Difference

Objective This study examined the association between ActiGraph accelerometer output and energy expenditure across different speeds of walking in persons with Parkinson’s disease (PD), and further generated cut-points that represent a metric for quantifying time spent in moderate-to-vigorous physical activity (MVPA) among persons with PD. Methods The sample included 30 persons with mild-to-moderate PD (Hoehn and Yahr stages 2–3) and 30 adults without PD matched by sex and age. All participants completed 5 minutes of quiet, seated rest and then underwent three, 6-minute bouts of walking on a treadmill at three different speeds relative to the individual’s self-selected pace. Activity counts were measured using an ActiGraph accelerometer worn at the waist level on the least affected side for persons with PD and the 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 (R2 = 0.87) and controls (R2 = 0.89). However, the significant difference in slopes resulted in a lower cut-point of 1,354 counts·min-1 for persons with PD than the cut-point of 2,010 counts·min-1 for controls. Conclusion Our results support the application of the disease-specific cut-point for quantifying the amount of time spent in MVPA using ActiGraph accelerometers among persons with mild-to-moderate PD. Such an application may provide accurate estimates of MVPA in this population, and better inform future research examining the possible determinants and consequences of physical activity as well as testing of interventions for changing MVPA in PD.

scholarly journals Inhibition of Orexin/Hypocretin Neurons Ameliorates Elevated Physical Activity and Energy Expenditure in the A53T Mouse Model of Parkinson’s Disease

2021 ◽  
Vol 22 (2) ◽  
pp. 795
Author(s):  
Milos Stanojlovic ◽  
Jean Pierre Pallais ◽  
Catherine M. Kotz
Keyword(s):  
Physical Activity ◽  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Energy Expenditure ◽  
Transgenic Animal ◽  
Alpha Synuclein ◽  
Behavioral Disturbances ◽  
Spontaneous Physical Activity ◽  
Exploratory Locomotion ◽  
Early Parkinson’S Disease

Aside from the classical motor symptoms, Parkinson’s disease also has various non-classical symptoms. Interestingly, orexin neurons, involved in the regulation of exploratory locomotion, spontaneous physical activity, and energy expenditure, are affected in Parkinson’s. In this study, we hypothesized that Parkinson’s-disease-associated pathology affects orexin neurons and therefore impairs functions they regulate. To test this, we used a transgenic animal model of Parkinson’s, the A53T mouse. We measured body composition, exploratory locomotion, spontaneous physical activity, and energy expenditure. Further, we assessed alpha-synuclein accumulation, inflammation, and astrogliosis. Finally, we hypothesized that chemogenetic inhibition of orexin neurons would ameliorate observed impairments in the A53T mice. We showed that aging in A53T mice was accompanied by reductions in fat mass and increases in exploratory locomotion, spontaneous physical activity, and energy expenditure. We detected the presence of alpha-synuclein accumulations in orexin neurons, increased astrogliosis, and microglial activation. Moreover, loss of inhibitory pre-synaptic terminals and a reduced number of orexin cells were observed in A53T mice. As hypothesized, this chemogenetic intervention mitigated the behavioral disturbances induced by Parkinson’s disease pathology. This study implicates the involvement of orexin in early Parkinson’s-disease-associated impairment of hypothalamic-regulated physiological functions and highlights the importance of orexin neurons in Parkinson’s disease symptomology.

scholarly journals Comparison of Physical Activity Level From Osteoporosis, Parkinson and Healthy Subjects

2021 ◽  
Vol 5 (Supplement_1) ◽  
pp. 940-940
Author(s):  
Seong Hyun Moon ◽  
Thurmon Lockhart ◽  
Krupa Doshi
Keyword(s):  
Physical Activity ◽  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Physical Activity Level ◽  
Healthy Subjects ◽  
Activity Level ◽  
Measurement Unit ◽  
Activity Levels ◽  
Significant Difference ◽  
Physical Activity Levels

Abstract Lifestyle at the habitation immensely affects the progression of various illnesses, such as Osteoporosis and Parkinson’s disease (PD). These disorders lead patients to a sedentary lifestyle and result in significantly less movement compared to the average healthy individual. The combination of these backgrounds escalates the percentage of fall incidents. Quantifying physical activity levels from longitudinal Activities of Daily Living (ADL) data of these disease patients could stipulate intuition of their fall mechanisms. The objective of this study is to compare the osteoporosis, Parkinson's disease, and healthy group’s physical activity level from their ADL. For this study total of eighteen subjects participated (healthy=6, osteoporosis=6, PD=6). The result indicated that the dynamic physical activity level for the healthy subject was 13.2%, the osteoporosis subject was 7.9%, and the PD subject was 7.0%. This indicates that there was a significant decline in physical activity level for the PD compared to healthy subjects (P=0.0024*). Also, a comparison between healthy and osteoporosis subjects showed a significant difference (P=0.0066*). Lastly, the physical activity level of PD and osteoporosis subjects did not have a significant difference among them (P=0.6276). The aim of this study was to evaluate the physical activity level of the osteoporosis, PD, and healthy subjects. The systematic approach of collecting physical activity levels with the Inertial Measurement Unit (IMU) device allowed researchers to collect the quantitative data of ADL. In this experiment, healthy subjects were significantly more physically active compared to osteoporosis and PD patients.

scholarly journals Physical activity profiles in Parkinson’s disease

BMC Neurology ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Philip von Rosen ◽  
Maria Hagströmer ◽  
Erika Franzén ◽  
Breiffni Leavy
Keyword(s):  
Physical Activity ◽  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Physical Function ◽  
Vigorous Physical Activity ◽  
Functional Mobility ◽  
Clinical Test ◽  
Accelerometer Data ◽  
Balance Performance ◽  
Timed Up And Go

Abstract Background Identifying physical activity (PA) profiles of people with Parkinson’s Disease (PD) could provide clinically meaningful knowledge concerning how to tailor PA interventions. Our objectives were therefore to i) identify distinct PA profiles in people with PD based on accelerometer data, ii) explore differences between the profiles regarding personal characteristics and physical function. Methods Accelerometer data from 301 participants (43% women, mean age: 71 years) was analysed using latent profile analyses of 15 derived PA variables. Physical function measurements included balance performance, comfortable gait speed and single and dual-task functional mobility. Results Three distinct profiles were identified; “Sedentary” (N = 68), “Light Movers” (N = 115), “Steady Movers” (N = 118). “Sedentary” included people with PD with high absolute and relative time spent in Sedentary behaviour (SB), little time light intensity physical activity (LIPA) and negligible moderate-to-vigorous physical activity (MVPA). “Light Movers” were people with PD with values close to the mean for all activity variables. “Steady Movers” spent less time in SB during midday, and more time in LIPA and MVPA throughout the day, compared to the other profiles. “Sedentary” people had poorer balance (P = 0.006), poorer functional mobility (P = 0.027) and were more likely to have fallen previously (P = 0.027), compared to “Light Movers. The Timed Up and Go test, an easily performed clinical test of functional mobility, was the only test that could distinguish between all three profiles. Conclusion Distinct PA profiles, with clear differences in how the time awake is spent exist among people with mild-moderate PD.

Daily energy expenditure, physical activity, and weight loss in Parkinson's disease patients

2009 ◽  
Vol 24 (5) ◽  
pp. 667-671 ◽  
Author(s):  
Evangelia Delikanaki-Skaribas ◽  
Marilyn Trail ◽  
William Wai-Lun Wong ◽  
Eugene C. Lai
Keyword(s):  
Physical Activity ◽  
Parkinson’S Disease ◽  
Weight Loss ◽  
Parkinson's Disease ◽  
Energy Expenditure ◽  
Daily Energy Expenditure ◽  
Daily Energy

scholarly journals Comparison of Epoch and Uniaxial Versus Triaxial Accelerometers in the Measurement of Physical Activity in Preschool Children: A Validation Study

2012 ◽  
Vol 24 (3) ◽  
pp. 450-460 ◽  
Author(s):  
Jane F. Hislop ◽  
Cathy Bulley ◽  
Tom H. Mercer ◽  
John J. Reilly
Keyword(s):  
Physical Activity ◽  
Preschool Children ◽  
Rating Scale ◽  
Vigorous Physical Activity ◽  
Free Play ◽  
Video Data ◽  
Activity Data ◽  
Cut Point ◽  
Significant Difference ◽  
Activity Rating

The objectives of this study were to explore whether triaxial is more accurate than uniaxial accelerometry and whether shorter sampling periods (epochs) are more accurate than longer epochs. Physical activity data from uniaxial and triaxial (RT3) devices were collected in 1-s epochs from 31 preschool children (15 males, 16 females, 4.4 ± 0.8 yrs) who were videoed while they engaged in 1-hr of free-play. Video data were coded using the Children’s Activity Rating Scale (CARS). A significant difference (p < .001) in the number of minutes classified as moderate to vigorous physical activity (MVPA) was found between the RT3 and the CARS (p < .002) using the cut point of relaxed walk. No significant difference was found between the GT1M and the CARS or between the RT3 and the CARS using the cut point for light jog. Shorter epochs resulted in significantly greater overestimation of MVPA, with the bias increasing from 0.7 mins at 15-s to 3.2 mins at 60-s epochs for the GT1M and 0 mins to 1.7 mins for the RT3. Results suggest that there was no advantage of a triaxial accelerometer over a uniaxial model. Shorter epochs result in significantly higher number of minutes of MVPA with smaller bias relative to direct observation.

scholarly journals Application of deep learning in detecting neurological disorders from magnetic resonance images: a survey on the detection of Alzheimer’s disease, Parkinson’s disease and schizophrenia

2020 ◽  
Vol 7 (1) ◽  
Author(s):  
Manan Binth Taj Noor ◽  
Nusrat Zerin Zenia ◽  
M Shamim Kaiser ◽  
Shamim Al Mamun ◽  
Mufti Mahmud
Keyword(s):  
Alzheimer’S Disease ◽  
Parkinson’S Disease ◽  
Alzheimer's Disease ◽  
Parkinson's Disease ◽  
Deep Learning ◽  
Magnetic Resonance ◽  
Neurological Disorders ◽  
Magnetic Resonance Images ◽  
Future Research ◽  
Comparative Performance

Abstract Neuroimaging, in particular magnetic resonance imaging (MRI), has been playing an important role in understanding brain functionalities and its disorders during the last couple of decades. These cutting-edge MRI scans, supported by high-performance computational tools and novel ML techniques, have opened up possibilities to unprecedentedly identify neurological disorders. However, similarities in disease phenotypes make it very difficult to detect such disorders accurately from the acquired neuroimaging data. This article critically examines and compares performances of the existing deep learning (DL)-based methods to detect neurological disorders—focusing on Alzheimer’s disease, Parkinson’s disease and schizophrenia—from MRI data acquired using different modalities including functional and structural MRI. The comparative performance analysis of various DL architectures across different disorders and imaging modalities suggests that the Convolutional Neural Network outperforms other methods in detecting neurological disorders. Towards the end, a number of current research challenges are indicated and some possible future research directions are provided.

scholarly journals The Contribution of Microglia to Neuroinflammation in Parkinson’s Disease

2021 ◽  
Vol 22 (9) ◽  
pp. 4676
Author(s):  
Katja Badanjak ◽  
Sonja Fixemer ◽  
Semra Smajić ◽  
Alexander Skupin ◽  
Anne Grünewald
Keyword(s):  
Oxidative Stress ◽  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Inflammatory Cytokine ◽  
Population Ageing ◽  
Future Research ◽  
Cytokine Release ◽  
Vicious Cycle ◽  
Inflammatory Processes ◽  
Great Evidence

With the world’s population ageing, the incidence of Parkinson’s disease (PD) is on the rise. In recent years, inflammatory processes have emerged as prominent contributors to the pathology of PD. There is great evidence that microglia have a significant neuroprotective role, and that impaired and over activated microglial phenotypes are present in brains of PD patients. Thereby, PD progression is potentially driven by a vicious cycle between dying neurons and microglia through the instigation of oxidative stress, mitophagy and autophagy dysfunctions, a-synuclein accumulation, and pro-inflammatory cytokine release. Hence, investigating the involvement of microglia is of great importance for future research and treatment of PD. The purpose of this review is to highlight recent findings concerning the microglia-neuronal interplay in PD with a focus on human postmortem immunohistochemistry and single-cell studies, their relation to animal and iPSC-derived models, newly emerging technologies, and the resulting potential of new anti-inflammatory therapies for PD.

Sign in / Sign up

Export Citation Format

Share Document