Research and Publications - Department of Health Science

Permanent URI for this collection

https://ir.ua.edu/handle/123456789/2882

Browse

Browsing Research and Publications - Department of Health Science by Subject "accelerometry"

Now showing 1 - 2 of 2
  • Thumbnail Image
    Item
    Cadence-based Classification of Minimally Moderate Intensity During Overground Walking in 21-to 40-Year-Old Adults
    (Human Kinetics, 2019) Aguiar, Elroy J.; Gould, Zachary R.; Ducharme, Scott W.; Moore, Chris C.; McCullough, Aston K.; Tudor-Locke, Catrine; University of Alabama Tuscaloosa; University of Massachusetts Amherst; California State University Long Beach; University of North Carolina; University of North Carolina Charlotte
    Background: A walking cadence of >= 100 steps/min corresponds to minimally moderate intensity, absolutely defined as >= 3 metabolic equivalents (METs). This threshold has primarily been calibrated during treadmill walking. There is a need to determine the classification accuracy of this cadence threshold to predict intensity during overground walking. Methods: In this laboratory-based cross-sectional investigation, participants (N = 75, 49.3% women, age 21-40 y) performed a single 5-minute overground (hallway) walking trial at a self-selected preferred pace. Steps accumulated during each trial were hand tallied and converted to cadence (steps/min). Oxygen uptake was measured using indirect calorimetry and converted to METs. The classification accuracy (sensitivity, specificity, overall accuracy, and positive predictive value) of >= 100 steps/min to predict >= 3METs was calculated. Results: A cadence threshold of =100 steps/min yielded an overall accuracy (combined sensitivity and specificity) of 73.3% for predicting minimally moderate intensity. Moreover, for individuals walking at a cadence >= 100 steps/min, the probability (positive predictive value) of achieving minimally moderate intensity was 80.3%. Conclusions: Although primarily developed using treadmill-based protocols, a cadence threshold of >= 100 steps/min for young adults appears to be a valid heuristic value (evidence-based, rounded, practical) associated with minimally moderate intensity during overground walking performed at a self-selected preferred pace.
  • Thumbnail Image
    Item
    Toward Harmonized Treadmill-Based Validation of Step-Counting Wearable Technologies: A Scoping Review
    (Human Kinetics, 2020) Moore, Christopher C.; McCullough, Aston K.; Aguiar, Elroy J.; Ducharme, Scott W.; Tudor-Locke, Catrine; University of North Carolina; University of North Carolina Chapel Hill; University of Massachusetts Amherst; University of Alabama Tuscaloosa; California State University Long Beach; University of North Carolina Charlotte
    The authors conducted a scoping review as a first step toward establishing harmonized (ie, consistent and compatible), empirically based best practices for validating step-counting wearable technologies. Purpose: To catalog studies validating step-counting wearable technologies during treadmill ambulation. Methods: The authors searched PubMed and SPORTDiscus in August 2019 to identify treadmill-based validation studies that employed the criterion of directly observed (including video recorded) steps and cataloged study sample characteristics, protocol details, and analytical procedures. Where reported, speed- and wear location-specific mean absolute percentage error (MAPE) values were tabulated. Weighted median MAPE values were calculated by wear location and a 0.2-m/s speed increment. Results: Seventy-seven eligible studies were identified: most had samples averaging 54% (SD = 5%) female and 27 (5) years of age, treadmill protocols consisting of 3 to 5 bouts at speeds of 0.8 (0.1) to 1.6 (0.2) m/s, and reported measures of bias. Eleven studies provided MAPE values at treadmill speeds of 1.1 to 1.8m/s; their weighted medianMAPE values were 7% to 11% for wrist-worn, 1% to 4% for waist-worn, and <= 1% for thigh-worn devices. Conclusions: Despite divergent study methodologies, the authors identified common practices and summarized MAPE values representing device step-count accuracy during treadmill walking. These initial empirical findings should be further refined to ultimately establish harmonized best practices for validating wearable technologies.