Step Count Validation of a Tri-Axial Accelerometer During Walking and Jogging

2012 ◽  
Author(s):  
Emma Fortune ◽  
Vipul Lugade ◽  
Melissa Morrow ◽  
Kenton Kaufman
Keyword(s):  
Physical Activity ◽  
Wearable Sensors ◽  
Living Environment ◽  
Activity Levels ◽  
Light Weight ◽  
Free Living ◽  
Step Counts ◽  
Step Counting ◽  
High Level ◽  
Very High

Gait analysis is an important tool in assessing the health and activity levels of patients and regular physical activity has been associated with health improvements in a number of populations. Step counting is one of the most commonly used measures of physical activity [1] and many studies have investigated the use of wearable sensors for step counts [2–4]. Their small size and light weight mean that they may be used in a free living environment and are suitable for home deployment. One of the main issues associated with step counts as a measure of physical activity is that a very high level of accuracy in step detection is needed.

scholarly journals Objective measurement of physical activity in Macaca fascicularis

1982 ◽  
Vol 16 (3) ◽  
pp. 240-243
Author(s):  
Wayne T. Corbett ◽  
Harry M. Schey ◽  
A. W. Green
Keyword(s):  
Physical Activity ◽  
Standard Deviation ◽  
Macaca Fascicularis ◽  
Living Environment ◽  
Activity Levels ◽  
Free Living ◽  
Activity Measurements ◽  
Active Intermediate ◽  
The Mean ◽  
The Relationship

The mean and standard deviation over 24 h for 3 groups of animals - active, intermediate and inactive - in physical activity units were 10948 ± 3360, 2611 ± 1973 and 484 ± 316 respectively. The differences were significant ( P = 0·004), demonstrating the ability of the method to distinguish between groups that can be visibly differentiated. The small within-animal physical activity standard deviation (18·85 PAU) obtained in another group, suggests that it also yields reliable physical activity measurements for non-human primates. The monitoring device used can discriminate between individual nonhuman primate physical activity levels in a free-living environment and does not alter daily behaviour. This makes possible the study of the relationship between physical activity and atherosclerosis in nonhuman primates.

Measuring Children’s Activity Levels: The Association Between Step-Counts and Activity Time

2006 ◽  
Vol 3 (2) ◽  
pp. 221-229 ◽  
Author(s):  
Aaron Beighle ◽  
Robert P. Pangrazi
Keyword(s):  
Physical Activity ◽  
Strong Association ◽  
Activity Levels ◽  
Activity Time ◽  
Free Living ◽  
Step Counts ◽  
Steps Per Day

Background:The primary purpose of this study was to describe the association between activity time and step counts in children.Methods:Subjects were 590 students (334 girls, 256 boys) with each gender having a mean age of 9.2 ± 1.8 y. All subjects wore the Walk4Life 2505 pedometer for four consecutive weekdays. This pedometer simultaneously measures both step counts and activity time.Results:Boys accumulated significantly more minutes of activity time/day (140.9 ± 39.6 vs. 126.3 ± 38.1), steps/day (13,348 ± 4131 vs. 11,702 ± 3923), and steps per min (93.99 ± 5.8 vs. 91.85 ± 5.8) than girls (P < 0.001) Steps/day was a significant predictor of activity time/day (P < 0.0001).Conclusions:Boys accumulate more steps per day and more activity time per day than girls. There is a strong association between steps per day and activity time in children. Daily steps per minute as a measure of free living physical activity in children is explored

Objectively measuring children's physical activity levels in a free living environment

2017 ◽  
Vol 20 ◽  
pp. e104 ◽  
Author(s):  
C. Desmet ◽  
R. Sutherland ◽  
L. Davies ◽  
L. Wolfenden ◽  
P. Butler ◽  
...  
Keyword(s):  
Physical Activity ◽  
Living Environment ◽  
Activity Levels ◽  
Free Living ◽  
Physical Activity Levels ◽  
Children’S Physical Activity

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.

scholarly journals An empirical example of analysis using a two-stage modeling approach: within-subject association of outdoor context and physical activity predicts future daily physical activity levels

2020 ◽  
Author(s):  
Chih-Hsiang Yang ◽  
Jaclyn P Maher ◽  
Aditya Ponnada ◽  
Eldin Dzubur ◽  
Rachel Nordgren ◽  
...  
Keyword(s):  
Physical Activity ◽  
Vigorous Physical Activity ◽  
Wearable Sensors ◽  
Activity Levels ◽  
Two Stage ◽  
Modeling Approach ◽  
Source Program ◽  
Modeling Strategy ◽  
Stage Modeling

Abstract People differ from each other to the extent to which momentary factors, such as context, mood, and cognitions, influence momentary health behaviors. However, statistical models to date are limited in their ability to test whether the association between two momentary variables (i.e., subject-level slopes) predicts a subject-level outcome. This study demonstrates a novel two-stage statistical modeling strategy that is capable of testing whether subject-level slopes between two momentary variables predict subject-level outcomes. An empirical case study application is presented to examine whether there are differences in momentary moderate-to-vigorous physical activity (MVPA) levels between the outdoor and indoor context in adults and whether these momentary differences predict mean daily MVPA levels 6 months later. One hundred and eight adults from a multiwave longitudinal study provided 4 days of ecological momentary assessment (during baseline) and accelerometry data (both at baseline and 6 month follow-up). Multilevel data were analyzed using an open-source program (MixWILD) to test whether momentary strength between outdoor context and MVPA during baseline was associated with average daily MVPA levels measured 6 months later. During baseline, momentary MVPA levels were higher in outdoor contexts as compared to indoor contexts (b = 0.07, p &lt; .001). Participants who had more momentary MVPA when outdoors (vs. indoors) during baseline (i.e., a greater subject-level slope) had higher daily MVPA at the 6 month follow-up (b = 0.09, p &lt; .05). This empirical example shows that the subject-level momentary association between specific context (i.e., outdoors) and health behavior (i.e., physical activity) may contribute to overall engagement in that behavior in the future. The demonstrated two-stage modeling approach has extensive applications in behavioral medicine to analyze intensive longitudinal data collected from wearable sensors and mobile devices.

An Examination of the Activity Patterns of Elementary School Children

2002 ◽  
Vol 14 (4) ◽  
pp. 432-441 ◽  
Author(s):  
Susan D. Vincent ◽  
Robert P. Pangrazi
Keyword(s):  
Physical Activity ◽  
Activity Patterns ◽  
Individual Variability ◽  
Activity Levels ◽  
Same Sex ◽  
Factorial Anova ◽  
Step Counts ◽  
Meaningful Activity ◽  
Significant Difference ◽  
Steps Per Day

Research has suggested a trend of decreasing activity with age necessitating a renewed emphasis on promoting physical activity for children. The purpose of this study was to assess current physical activity levels of children and to establish initial standards for comparison in determining appropriate activity levels of children based on pedometer counts. Children, 6–12 years old (N = 711), wore sealed pedometers for 4 consecutive days. Mean step counts ranged from 10,479–11,274 and 12300–13989 for girls and boys respectively. Factorial ANOVA found a significant difference between sex (F = 90.16, p < .01) but not among age (F = 0.78, p = .587). Great individual variability existed among children of the same sex. Further analysis found significant differences among children of the same sex above the 80th percentile and below the 20th percentile. A reasonable activity standard might be approximately 11,000 and 13,000 steps per day for girls and boys respectively, although further discussion of this is warranted. The descriptive nature of this study provides insights into the activity patterns of children and the mean step counts for boys and girls at each age can serve as a preliminary guide for determining meaningful activity levels for children based on pedometer counts.

scholarly journals Pedometer-determined physical activity among primary schoolchildren in Kuala Lumpur

2019 ◽  
Vol 28 (2) ◽  
pp. 115-123
Author(s):  
Bee Suan Wee ◽  
Awang Bulgiba ◽  
Abd. Talib Ruzita ◽  
Mohd. Noor Ismail ◽  
Bee Koon Poh
Keyword(s):  
Physical Activity ◽  
Primary School ◽  
Sociodemographic Factors ◽  
Activity Level ◽  
Activity Levels ◽  
Kuala Lumpur ◽  
Daily Step ◽  
Step Counts ◽  
Primary Schoolchildren ◽  
Physical Activity Levels

Objective: The aim of this study was to objectively measure physical activity and its association with sociodemographic factors among Malaysian primary school-age children. Methods: A total of 111 primary school children in Kuala Lumpur were selected through random sampling. Activity pattern was determined using pedometers and differences by sex, ethnicity and body mass index categories were analysed. The relationship between pedometer-determined physical activity and sociodemographic factors were also studied. Results: Overall, boys attained significantly higher daily step counts than girls (9573 ± 4145 vs 7313 ± 2697). Significant difference in daily step counts between boys and girls were observed during weekdays ( p<0.01), weekends ( p<0.05) and total mean step counts ( p<0.01). Malay ethnicity showed higher daily step counts during weekdays than weekends ( p<0.05). Compared with boys, girls had higher odds (OR=5.58; 95% CI 1.12, 27.77) of not meeting the recommended daily step counts. Those who had low physical activity levels had higher odds (OR=15.75; 95% CI 1.78, 139.33) of not meeting recommended daily step counts than children who had moderate physical activity level. Conclusion: Boys were significantly more active than girls and physical activity was greater during weekdays than on weekends. The primary schoolchildren in Kuala Lumpur were sedentary, with minimum physical activity being observed. Differences in sexes and physical activity levels influenced pedometer step counts in children.

scholarly journals Laboratory-Assessed Markers of Cardiometabolic Health and Associations with GIS-Based Measures of Active-Living Environments

2018 ◽  
Vol 15 (10) ◽  
pp. 2079 ◽  
Author(s):  
Samantha Hajna ◽  
Kaberi Dasgupta ◽  
Nancy Ross
Keyword(s):  
Physical Activity ◽  
Sociodemographic Factors ◽  
Living Environment ◽  
Cardiometabolic Health ◽  
Active Living ◽  
Daily Step ◽  
Step Counts ◽  
Mediating Role ◽  
Intensity Physical Activity ◽  
Living Environments

Active-living-friendly environments have been linked to physical activity, but their relationships with specific markers of cardiometabolic health remain unclear. We estimated the associations between active-living environments and markers of cardiometabolic health, and explored the potential mediating role of physical activity in these associations. We used data collected on 2809 middle-aged adults who participated in the Canadian Health Measures Survey (2007–2009; 41.5 years, SD = 15.1). Environments were assessed using an index that combined GIS-derived measures of street connectivity, land use mix, and population density. Body mass index (BMI), systolic blood pressure (SBP), hemoglobin A1c, and cholesterol were assessed in a laboratory setting. Daily step counts and moderate-to-vigorous intensity physical activity (MVPA) were assessed for seven days using accelerometers. Associations were estimated using robust multivariable linear regressions adjusted for sociodemographic factors that were assessed via questionnaire. BMI was 0.79 kg/m2 lower (95% confidence interval (CI) −1.31, −0.27) and SBP was 1.65 mmHg lower (95% CI −3.10, −0.20) in participants living in the most active-living-friendly environments compared to the least, independent of daily step counts or MVPA. A 35.4 min/week difference in MPVA (95% CI 24.2, 46.6) was observed between residents of neighborhoods in the highest compared to the lowest active-living-environment quartiles. Cycling to work rates were also the highest in participants living in the highest living-environment quartiles (e.g., Q4 vs. Q1: 10.4% vs. 4.9%). Although active-living environments are associated with lower BMI and SBP, and higher MVPA and cycling rates, neither daily step counts nor MVPA appear to account for environment–BMI/SBP relationships. This suggests that other factors not assessed in this study (e.g., food environment or unmeasured features of the social environment) may explain this relationship.

Physical Activity Monitor Accuracy for Overground Walking and Free-Living Conditions Among Pregnant Women

2020 ◽  
Vol 3 (2) ◽  
pp. 100-109
Author(s):  
Christopher P. Connolly ◽  
Jordana Dahmen ◽  
Robert D. Catena ◽  
Nigel Campbell ◽  
Alexander H.K. Montoye
Keyword(s):  
Physical Activity ◽  
Pregnant Women ◽  
Living Conditions ◽  
Overground Walking ◽  
Third Trimester ◽  
Free Living ◽  
Activity Monitors ◽  
Step Counting ◽  
Physical Activity Monitors ◽  
Free Living Conditions

Purpose: We aimed to determine the step-count validity of commonly used physical activity monitors for pregnancy overground walking and during free-living conditions. Methods: Participants (n = 39, 12–38 weeks gestational age) completed six 100-step overground walking trials (three self-selected “normal pace”, three “brisk pace”) while wearing five physical activity monitors: Omron HJ-720 (OM), New Lifestyles 2000 (NL), Fitbit Flex (FF), ActiGraph Link (AG), and Modus StepWatch (SW). For each walking trial, monitor-recorded steps and criterion-measured steps were assessed. Participants also wore all activity monitors for an extended free-living period (72 hours), with the SW used as the criterion device. Mean absolute percent error (MAPE) was calculated for overground walking and free-living protocols and compared across monitors. Results: For overground walking, the OM, NL, and SW performed well (<5% MAPE) for normal and brisk pace walking trials, and also when trials were analyzed by actual speeds. The AG and FF had significantly greater MAPE for overground walking trials (11.9–14.7%). Trimester did affect device accuracy to some degree for the AG, FF, and SW, with error being lower in the third trimester compared to the second. For the free-living period, the OM, NL, AG, and FF significantly underestimated (>32% MAPE) actual steps taken per day as measured by the criterion SW (M [SD] = 9,350 [3,910]). MAPE for the OM was particularly high (45.3%). Conclusion: The OM, NL, and SW monitors are valid measures for overground step-counting during pregnancy walking. However, the OM and NL significantly underestimate steps by second and third trimester pregnant women in free-living conditions.

scholarly journals Wearable Sensor System to Monitor Physical Activity and the Physiological Effects of Heat Exposure

Sensors ◽  
2020 ◽  
Vol 20 (3) ◽  
pp. 855 ◽  
Author(s):  
Sean Pham ◽  
Danny Yeap ◽  
Gisela Escalera ◽  
Rupa Basu ◽  
Xiangmei Wu ◽  
...  
Keyword(s):  
Physical Activity ◽  
Environmental Conditions ◽  
Wearable Sensors ◽  
Heat Exposure ◽  
Extreme Heat ◽  
Mobile Systems ◽  
Physiological Data ◽  
Activity Levels ◽  
Integrated Sensor ◽  
Healthcare Facilities

Mobile health monitoring via non-invasive wearable sensors is poised to advance telehealth for older adults and other vulnerable populations. Extreme heat and other environmental conditions raise serious health challenges that warrant monitoring of real-time physiological data as people go about their normal activities. Mobile systems could be beneficial for many communities, including elite athletes, military special forces, and at-home geriatric monitoring. While some commercial monitors exist, they are bulky, require reconfiguration, and do not fit seamlessly as a simple wearable device. We designed, prototyped and tested an integrated sensor platform that records heart rate, oxygen saturation, physical activity levels, skin temperature, and galvanic skin response. The device uses a small microcontroller to integrate the measurements and store data directly on the device for up to 48+ h. continuously. The device was compared to clinical standards for calibration and performance benchmarking. We found that our system compared favorably with clinical measures, such as fingertip pulse oximetry and infrared thermometry, with high accuracy and correlation. Our novel platform would facilitate an individualized approach to care, particularly those whose access to healthcare facilities is limited. The platform also can be used as a research tool to study physiological responses to a variety of environmental conditions, such as extreme heat, and can be customized to incorporate new sensors to explore other lines of inquiry.

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