Search Results

You are looking at 1 - 10 of 188 items for :

  • "data processing" x
Clear All
Restricted access

John R. Sirard, Ann Forsyth, J. Michael Oakes and Kathryn H. Schmitz

Background:

The purpose of this study was to determine 1) the test-retest reliability of adult accelerometer-measured physical activity, and 2) how data processing decisions affect physical activity levels and test-retest reliability.

Methods:

143 people wore the ActiGraph accelerometer for 2 7-day periods, 1 to 4 weeks apart. Five algorithms, varying nonwear criteria (20 vs. 60 min of 0 counts) and minimum wear requirements (6 vs. 10 hrs/day for ≥ 4 days) and a separate algorithm requiring ≥ 3 counts per min and ≥ 2 hours per day, were used to process the accelerometer data.

Results:

Processing the accelerometer data with different algorithms resulted in different levels of counts per day, sedentary, and moderate-to-vigorous physical activity. Reliability correlations were very good to excellent (ICC = 0.70−0.90) for almost all algorithms and there were no significant differences between physical activity measures at Time 1 and Time 2.

Conclusions:

This paper presents the first assessment of test-retest reliability of the Actigraph over separate administrations in free-living subjects. The ActiGraph was highly reliable in measuring activity over a 7-day period in natural settings but data were sensitive to the algorithms used to process them.

Restricted access

Heidi R. Thornton, André R. Nelson, Jace A. Delaney, Fabio R. Serpiello and Grant M. Duthie

manufacturers, the interunit reliability and the between-manufacturer variation of variables should be investigated. There are continual improvements in GPS technology occurring, with advancements in microprocessors, software, and data processing techniques, 4 which overall may improve the validity and

Restricted access

Dinesh John, Qu Tang, Fahd Albinali and Stephen Intille

cross-study uniformity in accelerometer data processing, and, thus, limit the interpretation of findings across studies. Raw accelerometer data processing to detect specific activity type, intensity, and duration is an active area of research ( Mannini, Rosenberger, Haskell, Sabatini, & Intille, 2017

Restricted access

John H. Challis

This article presents and evaluates a new procedure that automatically determines the cutoff frequency for the low-pass filtering of biomechanical data. The cutoff frequency was estimated by exploiting the properties of the autocorrelation function of white noise. The new procedure systematically varies the cutoff frequency of a Butterworth filter until the signal representing the difference between the filtered and unfiltered data is the best approximation to white noise as assessed using the autocorrelation function. The procedure was evaluated using signals generated from mathematical functions. Noise was added to these signals so mat they approximated signals arising from me analysis of human movement. The optimal cutoff frequency was computed by finding the cutoff frequency that gave me smallest difference between the estimated and true signal values. The new procedure produced similar cutoff frequencies and root mean square differences to me optimal values, for me zeroth, first and second derivatives of the signals. On the data sets investigated, this new procedure performed very similarly to the generalized cross-validated quintic spline.

Restricted access

Chuhe Chen, Gerald J. Jerome, Daniel LaFerriere, Deborah Rohm Young and William M. Vollmer

Background:

Accelerometers measure intensity, frequency, and duration of physical activity. However, the scarcity of reports on data reduction makes comparing accelerometer results across studies difficult.

Methods:

Participants were asked to wear a triaxial accelerometer (RT3) for ≥10 hours for at least 4 days, including one weekend day. We summarize our data-cleaning procedures and assess the impact of defining a usable day of measurements as at least 6, 8, or 10 hours of wear time, and of standardizing data to a 12-hour day.

Results:

Eighty-two percent of participants met wear time requirements; 93% met requirements when we defined a day as 8-or-more hours of wear time. Normalization of data to a 12-hour day had little impact on estimates of daily moderate-to-vigorous physical activity (MVPA; 16.9 vs. 17.1 minutes); restricting MVPA to activities occurring in bouts of 10 minutes or longer had greater impact (16.9 vs. 6.3 minutes per day).

Conclusion:

Our account of accelerometry quality-control and data-cleaning procedures documents the small impact of variations in daily wear time requirements on MVPA estimates, and the larger impact of evaluating total MVPA vs. MVPA occurring in extended bouts. This paper should allow other researchers to duplicate or revise our methods as needed.

Restricted access

Anna Pulakka, Eric J. Shiroma, Tamara B. Harris, Jaana Pentti, Jussi Vahtera and Sari Stenholm

new challenges to accelerometer data processing ( McVeigh et al., 2016 ; Meredith-Jones, Williams, Galland, Kennedy, & Taylor, 2016 ; Tracy et al., 2014 ; van der Berg et al., 2016 ). Before being able to analyze either sleep or physical activity, one needs to separate non-wear, wake and sleep time

Restricted access

Kate Ridley, Jim Dollman and Tim Olds

The aim was to develop and trial a computer delivered multimedia 1-day physical activity questionnaire (CDPAQ) and to compare this with an equivalent hard copy version (HC). Thirty male and female subjects (11.96 ± 0.53 years) were used to assess the validity of the questionnaires by comparing Caltrac counts and heart rate (HR) data with physical activity recalls. Pearson product-moment correlations between the CDPAQ and HR and Caltrac counts ranged from r = 0.36 to 0.63 (p < .05). For the HC, correlations ranged from r = 0.25 to 0.48 (p < .05). While the CDPAQ displayed consistently higher validity correlations, the differences failed to reach statistical significance. Both questionnaires demonstrated high test-retest reliability (r = 0.98, p = .0001). The multimedia features of the CDPAQ may assist children in remembering and characterizing physical activity. The data processing features of the CDPAQ also provide considerable time-saving benefits.

Restricted access

The authors and publisher regret that incorrect data were reported in JAB Volume 28, No. 2 (May 2012), on pages 222–227, in the article titled “Modeling the Stance Leg in Two-Dimensional Analyses of Sprinting: Inclusion of the MTP Joint Affect Joint Kinetics,” by Neil E. Bezodis, Aki I.T. Salo, and Grant Trewartha. An error in the data-processing script affected some of the calculated joint kinetics. The MTP plantar flexor moments were calculated correctly and are large enough to warrant consideration for a more complete picture of the energetics of sprinting. However, the correct data revealed that choice of foot model has relatively little effect on the calculated kinetics at other joints with the only meaningful differences being present in the ankle joint power and work data. As of November 1, 2012, the online version has been fully corrected and is available at http://journals.humankinetics.com/jab-back-issues/ jab-volume-28-issue-2-may.

Restricted access

Aki Salo and Paul N. Grimshaw

Eight trials each of 7 athletes (4 women and 3 men) were videotaped and digitized in order to investigate the variation sources and kinematic variability of video motion analysis in sprint hurdles. Mean coefficients of variation (CVs) of individuals ranged from 1.0 to 92.2% for women and from 1.2 to 209.7% for men. There were 15 and 14 variables, respectively, in which mean CVs revealed less than 5% variation. In redigitizing, CVs revealed <1.0% for 12 variables for the women's trials and 10 variables for the men's trials. These results, together with variance components (between-subjects, within-subject, and redigitizing), showed that one operator and the analysis system together produced repeatable values for most of the variables. The most repeatable variables by this combination were displacement variables. However, further data processing (e.g., differentiation) appeared to have some unwanted effects on repeatability. Regarding the athletes' skill, CVs showed that athletes can reproduce most parts of their performance within certain (reasonably low) limits.

Restricted access

Nelson Cortes and James Onate

Context:

Clinical assessment tools are needed to identify individual athletes who possess elevated risk for anterior cruciate ligament injury. Existing methods require expensive equipment and the investment of a large amount of time for data processing, which makes them unfeasible for preparticipation screening of a large number of athletes.

Objective:

To assess the extent of agreement between LESS and the iLESS classifications of jump landing performance and the level of agreement between ratings assigned by a novice evaluator and an expert evaluator.

Methods:

Ratings of drop-jump landings from 20 video recordings of NCAA Division I collegiate athletes, which were randomly selected from a large database.

Results:

The dichotomous iLESS score corresponded to the dichotomous classification of LESS score for 15 of 20 cases rated by the expert evaluator and 17 of 20 cases rated by the novice evaluator. For the iLESS, only 2 scores out of 20 differed between the evaluators.

Conclusions:

A high level of agreement was observed between the LESS and iLESS methods for classification of jump- landing performance. Because the iLESS method is inexpensive and efficient, it may prove to be valuable for preparticipation assessment of knee injury risk.