Medicine and Health Sciences Commons^™

Validity Parameters For Step Counting Wearable Technologies During Treadmill Walking In Young People 6-20 Years Of Age, Zachary Gould

Masters Theses

Introduction: Wearable technologies play an important contemporary role in the measurement of physical activity (PA) and promotion of human health across the lifespan, including for young people (i.e., children, adolescents, and young adults). As new objective wearable technologies continue to develop, standardized approaches to documenting validation parameters (i.e., measures of accuracy, precision, and bias) are needed to ensure confidence and comparability in step-defined PA. Purpose: To produce validity parameters for step counting wearable technologies during treadmill walking in young people 6-20 years of age Methods: 120 participants completed 5-minute treadmill bouts from13.4 to 134.1 m·min^-1. Participants wore eight …

Cadence As An Indicator Of The Walk-To-Run Transition, Colleen Chase

Masters Theses

Humans naturally select a point at which to transition from walking to running when gradually increasing locomotor speed. This point is known as the walk-to-run transition (WRT). The WRT is traditionally expressed in terms of speed and is known to occur within a close range of 2.1 m/s, which is an accepted heuristic (i.e., empirically based, rounded) threshold value. Very little research exists defining the WRT in terms of cadence (steps/min) despite the fact that spatial temporal aspects of gait underlying the WRT include this parameter. Preliminary evidence suggests that the WRT may be associated with a cadence of 140 …

Development And Cross-Validation Of A Cadence-Based Metabolic Equation For Walking, Christopher C. Moore

Masters Theses

The ACSM Metabolic Equation is a widely recognized equation for predicting metabolic intensity from walking speed. However, an equation that uses an observable metric (i.e., cadence [steps/min]), accounts for individual characteristics, and is validated across walking conditions may enable more accessible and accurate predictions of walking intensity. PURPOSE: To develop metabolic equations that predict metabolic intensity (oxygen consumption; mL/kg/min) from cadence using a large treadmill walking dataset (Study One) and cross-validate these equations during overground unconstrained and cadence-constrained walking conditions (Study Two). METHODS: In Study One, 193 adults (21-81 years) completed treadmill walking bouts while oxygen consumption was measured with …

Does Age Influence Dynamic Stability And Muscular Power Following Neuromuscular Fatigue In Women?, Ben J. Hoffmann

Masters Theses

Older adults, especially older women, produce less muscular power than young adults, due primarily to slower maximal contractile velocity. These decrements may lead to increased fall risk in older women and can be exacerbated by fatigue. Recently, a 32 min walking task (32MWT) was shown to elicit fatigue in older women. The purpose of this study was to determine whether knee extensor (KE) maximal velocity is related to dynamic stability (margin of stability, MoS) in young and older women pre- and post-32MWT. METHODS: Nine young (Y; 24.3+1.1years, mean±SE) and 17 older (O; 71.1±1.1years) healthy women completed 2 testing sessions on …

Accuracy Of Physical Activity Monitors In Persons With Class Iii Obesity, Matthew Gregory Browning

Masters Theses

Background Small, wearable monitors are widely used to assess physical activity (PA) in obesity treatment programs ranging from lifestyle interventions to post-bariatric surgical programs. Although wearable monitors can overcome the recall biases often associated with self-reports, the accuracy of these devices may be impacted by anthropometric measures, mode of PA, and wear location. Thus, it is important to examine the accuracy of objective PA monitors during commonly performed activities such as walking.

Methods Fifteen individuals with class III obesity completed a self-paced 6-minute walk while wearing the StepWatch 3 (SW3), Omron, Digiwalker (DW), SenseWear Pro 2 Armband (SWA), and Fitbit …