scholarly journals Cellular telephone use during free-living walking significantly reduces average walking speed

2016 ◽  
Vol 9 (1) ◽  
Author(s):  
Jacob E. Barkley ◽  
Andrew Lepp
Keyword(s):  
Walking Speed ◽  
Cellular Telephone ◽  
Free Living

scholarly journals Is There a Sex Difference in Accelerometer Counts During Walking in Older Adults?

2014 ◽  
Vol 11 (3) ◽  
pp. 626-637 ◽  
Author(s):  
Dane R. Van Domelen ◽  
Paolo Caserotti ◽  
Robert J. Brychta ◽  
Tamara B. Harris ◽  
Kushang V. Patel ◽  
...  
Keyword(s):  
Older Adults ◽  
Sex Difference ◽  
Walking Speed ◽  
Vertical Axis ◽  
Step Length ◽  
Walk Test ◽  
Free Living ◽  
Males And Females ◽  
6 Minute Walk Test ◽  
Minute Walk

Background:Accelerometers have emerged as a useful tool for measuring free-living physical activity in epidemiological studies. Validity of activity estimates depends on the assumption that measurements are equivalent for males and females while performing activities of the same intensity. The primary purpose of this study was to compare accelerometer count values in males and females undergoing a standardized 6-minute walk test.Methods:The study population was older adults (78.6 ± 4.1 years) from the AGES-Reykjavik Study (N = 319). Participants performed a 6-minute walk test at a self-selected fast pace while wearing an ActiGraph GT3X at the hip. Vertical axis counts·s−1 was the primary outcome. Covariates included walking speed, height, weight, BMI, waist circumference, femur length, and step length.Results:On average, males walked 7.2% faster than females (1.31 vs. 1.22 m·s−1, P < .001) and had 32.3% greater vertical axis counts·s−1 (54.6 vs. 39.4 counts·s−1, P < .001). Accounting for walking speed reduced the sex difference to 19.2% and accounting for step length further reduced the difference to 13.4% (P < .001).Conclusion:Vertical axis counts·s−1 were disproportionally greater in males even after adjustment for walking speed. This difference could confound free-living activity estimates.

scholarly journals How Does a Hilly Urban Environment Influence Daily Physical Activity in Obese Individuals?

2013 ◽  
Vol 10 (5) ◽  
pp. 617-625 ◽  
Author(s):  
Dac Minh Tuan Nguyen ◽  
Virgile Lecoultre ◽  
Andrew P. Hills ◽  
Yves Schutz
Keyword(s):  
Physical Activity ◽  
Energy Expenditure ◽  
Urban Environment ◽  
Exercise Intensity ◽  
Walking Speed ◽  
Living Conditions ◽  
Daily Physical Activity ◽  
Outdoor Environment ◽  
Free Living ◽  
Free Living Conditions

Background:Increases in physical activity (PA) are promoted by walking in an outdoor environment. Along with walking speed, slope is a major determinant of exercise intensity, and energy expenditure. The hypothesis was that in free-living conditions, a hilly environment diminishes PA to a greater extent in obese (OB) when compared with control (CO) individuals.Methods:To assess PA types and patterns, 28 CO (22 ± 2 kg/m2) and 14 OB (33 ± 4 kg/m2) individuals wore during an entire day 2 accelerometers and 1 GPS device, around respectively their waist, ankle and shoulder. They performed their usual PA and were asked to walk an additional 60 min per day.Results:The duration of inactivity and activity with OB individuals tended to be, respectively, higher and lower than that of CO individuals (P = .06). Both groups spent less time walking uphill/downhill than on the level (20%, 19%, vs. 61% of total walking duration, respectively, P < .001). However OB individuals spent less time walking uphill/downhill per day than CO (25 ± 15 and 38 ± 15 min/d, respectively, P < 0.05) and covered a shorter distance per day (3.8 km vs 5.2 km, P < 0.01).Conclusions:BMI and outdoor topography should also be considered when prescribing extra walking in free-living conditions.

scholarly journals Association between Walking Speed and Age in Healthy, Free-Living Individuals Using Mobile Accelerometry—A Cross-Sectional Study

PLoS ONE ◽  
2011 ◽  
Vol 6 (8) ◽  
pp. e23299 ◽  
Author(s):  
Michaela Schimpl ◽  
Carmel Moore ◽  
Christian Lederer ◽  
Anneke Neuhaus ◽  
Jennifer Sambrook ◽  
...  
Keyword(s):  
Walking Speed ◽  
Cross Sectional Study ◽  
Sectional Study ◽  
Free Living ◽  
Cross Sectional

scholarly journals Estimating Walking Speed in the Wild

2020 ◽  
Vol 2 ◽  
Author(s):  
Loubna Baroudi ◽  
Mark W. Newman ◽  
Elizabeth A. Jackson ◽  
Kira Barton ◽  
K. Alex Shorter ◽  
...  
Keyword(s):  
Physical Activity ◽  
Clinical Decision Making ◽  
Walking Speed ◽  
Wearable Sensors ◽  
Clinical Decision ◽  
Living Environment ◽  
Activity Level ◽  
Measurement Unit ◽  
Battery Life ◽  
Free Living

An individual's physical activity substantially impacts the potential for prevention and recovery from diverse health issues, including cardiovascular diseases. Precise quantification of a patient's level of day-to-day physical activity, which can be characterized by the type, intensity, and duration of movement, is crucial for clinicians. Walking is a primary and fundamental physical activity for most individuals. Walking speed has been shown to correlate with various heart pathologies and overall function. As such, it is often used as a metric to assess health performance. A range of clinical walking tests exist to evaluate gait and inform clinical decision-making. However, these assessments are often short, provide qualitative movement assessments, and are performed in a clinical setting that is not representative of the real-world. Technological advancements in wearable sensing and associated algorithms enable new opportunities to complement in-clinic evaluations of movement during free-living. However, the use of wearable devices to inform clinical decisions presents several challenges, including lack of subject compliance and limited sensor battery life. To bridge the gap between free-living and clinical environments, we propose an approach in which we utilize different wearable sensors at different temporal scales and resolutions. Here, we present a method to accurately estimate gait speed in the free-living environment from a low-power, lightweight accelerometer-based bio-logging tag secured on the thigh. We use high-resolution measurements of gait kinematics to build subject-specific data-driven models to accurately map stride frequencies extracted from the bio-logging system to stride speeds. The model-based estimates of stride speed were evaluated using a long outdoor walk and compared to stride parameters calculated from a foot-worn inertial measurement unit using the zero-velocity update algorithm. The proposed method presents an average concordance correlation coefficient of 0.80 for all subjects, and 97% of the error is within ±0.2m· s−1. The approach presented here provides promising results that can enable clinicians to complement their existing assessments of activity level and fitness with measurements of movement duration and intensity (walking speed) extracted at a week time scale and in the patients' free-living environment.

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