scholarly journals Novel Analytic Approaches to Investigate Minute-Level Actigraphy and Associations With Physical Function

2020 ◽  
Vol 4 (Supplement_1) ◽  
pp. 194-195
Author(s):  
Kaiyuan Hua ◽  
Sheng Luo ◽  
Katherine Hall ◽  
Miriam Morey ◽  
Harvey Cohen
Keyword(s):  
Physical Activity ◽  
Data Analysis ◽  
Physical Function ◽  
Functional Data Analysis ◽  
Functional Data ◽  
Gait Speed ◽  
Community Dwelling ◽  
Accelerometer Data ◽  
Single Leg Stance ◽  
Minute Walk

Abstract Background. Functional decline in conjunction with low levels of physical activity has implications for health risks in older adults. Previous studies have examined the associations between accelerometry-derived activity and physical function, but most of these studies reduced these data into average means of total daily physical activity (e.g., daily step counts). A new method of analysis “functional data analysis” provides more in-depth capability using minute-level accelerometer data. Methods. A secondary analysis of community-dwelling adults ages 30 to 90+ residing in southwest region of North Carolina from the Physical Performance across the Lifespan (PALS) study. PALS assessments were completed in-person at baseline and one-week of accelerometry. Final analysis includes 669 observations at baseline with minute-level accelerometer data from 7:00 to 23:00, after removing non-wear time. A novel scalar-on-function regression analysis was used to explore the associations between baseline physical activity features (minute-by-minute vector magnitude generated from accelerometer) and baseline physical function (gait speed, single leg stance, chair stands, and 6-minute walk test) with control for baseline age, sex, race and body mass index. Results. The functional regressions were significant for specific times of day indicating increased physical activity associated with increased physical function around 8:00, 9:30 and 15:30-17:00 for rapid gait speed; 9:00-10:30 and 15:00-16:30 for normal gait speed; 9:00-10:30 for single leg stance; 9:30-11:30 and 15:00-18:00 for chair stands; 9:00-11:30 and 15:00-18:30 for 6-minute walk. Conclusion. This method of functional data analysis provides news insights into the relationship between minute-by-minute daily activity and health.

Physical Function and Physical Activity in Peritoneal Dialysis Patients

2017 ◽  
Vol 37 (6) ◽  
pp. 598-604 ◽  
Author(s):  
Patricia L. Painter ◽  
Adhish Agarwal ◽  
Micah Drummond
Keyword(s):  
Physical Activity ◽  
Peritoneal Dialysis ◽  
Physical Performance ◽  
Physical Functioning ◽  
Gait Speed ◽  
Community Dwelling ◽  
Moderate Intensity ◽  
Walk Distance ◽  
Diabetes Status ◽  
Minute Walk

BackgroundPhysical functioning (PF) and physical activity (PA) are low in patients treated with maintenance hemodialysis (MHD). Little information exists on this topic in patients treated with peritoneal dialysis (PD). The objective of this study was to compare PF and PA in patients with Stage-5 chronic kidney disease (CKD) treated with PD and in-center MHD.MethodsPhysical functioning was measured in 45 prevalent PD patients using standard physical performance measures that include gait speed, chair stand, standing balance, 6-minute-walk, incremental shuttle walk and self-reported PF using the short form (SF)-36 questionnaire. Physical activity was determined from self-report and using the Community Healthy Activities Model Program for Seniors (CHAMPS) questionnaire. Scores for the short physical performance battery (SPPB) were calculated. In-center MHD patients were matched by age, gender, and diabetes status to the PD patients.ResultsUnadjusted comparisons showed significantly higher 6-minute-walk distance, shuttle-walk distance and hand-grip in the PD patients. Adjustment in multiple regression analysis resulted in only gait speed being significantly different between the groups. All test results in both groups were lower than reference values for age and gender in the general population, and were at the levels indicating impairment. Physical activity was not different between the 2 groups (average age 49 yrs), and both groups had weekly caloric expenditure from all exercise and from moderate-intensity exercise that was similar to older (> 70 yrs) community-dwelling adults. Adjusted association indicated that PA was significantly associated with shuttle-walk distance.ConclusionsPhysical functioning and PA measures were low in both PD and MHD groups. Interventions to improve PA and PF should be strongly considered for both PD and MHD patients.

scholarly journals Classifying smartphone-based accelerometer data to obtain validated measures of subject activity status, step count, and gait speed

2017 ◽  
Author(s):  
Yong Jun Kwon ◽  
Thawda Aung ◽  
Sarah M Synovec ◽  
Anthony D Oberle ◽  
Cassia Rye Hanton ◽  
...  
Keyword(s):  
Physical Activity ◽  
Gait Speed ◽  
Community Dwelling ◽  
Step Count ◽  
Accelerometer Data ◽  
Data Quality Control ◽  
High Physical Activity ◽  
Smartphone Technology ◽  
Behavioral Classification

AbstractBackgroundThe ubiquitous spread of smartphone technology throughout global societies offers an unprecedented opportunity to ethically obtain long-term, highly accurate measurements of individual physical activity. For example, the smartphone intrinsic 3-D accelerometer can be queried during normal phone operation to save time series of acceleration magnitudes (in each of the component directions) for near-real time or post processing.ObjectiveWe describe simple, straightforward algorithms (based on windowed Fourier analysis) for accelerometer data quality control and behavioral classification.MethodsTo maximize the clinical utility of our classifications, we focused on differentiating the following conditions: forgotten phone, subject resting, low physical activity, high physical activity. We further differentiated high physical activity into epochs of walking and climbing stairs, and further quantified walking to infer step count and gait speed.ResultsWe validated these algorithms in 75 individuals, in both laboratory (treadmill) and naturalistic settings. Our algorithm performance was quite satisfactory, with accuracies of 92-99% for all behavioral categories, and 87-90% for gait metrics in naturalistic settings.ConclusionsWe conclude that smartphones are valid and accurate platforms for measuring day-to-day physical activity in ambulatory, community dwelling individuals.

scholarly journals Basis Expansions for Functional Snippets

Biometrika ◽  
2020 ◽  
Author(s):  
Zhenhua Lin ◽  
Jane-Ling Wang ◽  
Qixian Zhong
Keyword(s):  
Data Analysis ◽  
Convergence Rate ◽  
Functional Data Analysis ◽  
Functional Data ◽  
Covariance Function ◽  
Covariance Estimation ◽  
Simulation Studies ◽  
Finite Sample ◽  
Covariance Functions ◽  
The Mean

Summary Estimation of mean and covariance functions is fundamental for functional data analysis. While this topic has been studied extensively in the literature, a key assumption is that there are enough data in the domain of interest to estimate both the mean and covariance functions. In this paper, we investigate mean and covariance estimation for functional snippets in which observations from a subject are available only in an interval of length strictly (and often much) shorter than the length of the whole interval of interest. For such a sampling plan, no data is available for direct estimation of the off-diagonal region of the covariance function. We tackle this challenge via a basis representation of the covariance function. The proposed estimator enjoys a convergence rate that is adaptive to the smoothness of the underlying covariance function, and has superior finite-sample performance in simulation studies.

A kNN procedure in semiparametric functional data analysis

2021 ◽  
pp. 109028
Author(s):  
Silvia Novo ◽  
Germán Aneiros ◽  
Philippe Vieu
Keyword(s):  
Data Analysis ◽  
Functional Data Analysis ◽  
Functional Data
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