Trunk Flexion Monitoring among Warehouse Workers Using a Single Inertial Sensor and the Influence of Different Sampling Durations

Trunk flexion represents a risk factor for the onset of low-back disorders, yet limited quantitative data exist regarding flexion exposures in actual working conditions. In this study, we evaluated the potential of using a single inertial measurement unit (IMU) to classify trunk flexion, in terms of amplitude, frequency, and duration, and assessed the influence of alternative time durations on exposure results. Twelve warehouse workers were monitored during two hours of an actual shift while wearing a single IMU on their low back. Trunk flexion data were reduced using exposure variation analysis integrated with recommended exposure thresholds. Workers spent 5.1% of their working time with trunk flexion of 30–60° and 2.3% with flexion of 60–90°. Depending on the level of acceptable error, relatively shorter monitoring periods (up to 50 min) might be sufficient to characterize trunk flexion exposures. Future work is needed, however, to determine if these results generalize to other postural exposures and tasks.

The Influence of Pleasure and Attentional Focus on Performance and Pacing Strategies in Elite Individual Time Trials

Recent psychophysiological models of endurance performance explained that pacing strategies and exercise-intensity regulation influence cyclists’ ability to produce high mean power output (PO) during time trials (TTs). However, the relationships between these pacing strategies and psychological parameters of the athletes remain unknown. Purpose: To determine the impact of pacing strategies on cyclists’ mean PO during an elite TT championship and to identify the relationships between these pacing strategies and psychological parameters. Methods: Mean PO, projected frontal area, attentional focus, and pleasure were recorded for 9 male cyclists during an official individual TT national championship. Pacing regulations were quantified from PO using the new exposure variation analysis, which determines times spent at adapted PO for optimal constant-pacing strategy (APO) and inaccurate PO for optimal constant-pacing strategy (IPO). Relationships between mean PO, times spent at APO and IPO, and psychological variables were analyzed. Results: Significant relationships were found between mean PO and exposure variation analysis pacing parameters (r2 .56–.86, P > .05). Time spent at IPO was negatively related to pleasure during the individual TT (r = −.746, P = .016). Conversely, time spent at APO was significantly related to cyclists’ attentional focus (r = .827, P = .006). Conclusions: Mean PO during elite individual TTs is directly related to athletes’ ability to optimally regulate pace throughout the event. This pacing regulation is influenced by attentional focus and pleasure, underlining that coaches and athletes should devote greater attention to these psychological parameters to improve their performances.

Differences in trapezius muscle activation patterns in office workers with and without chronic neck-shoulder pain, as quantified through exposure variation analysis

The purpose of this study was to quantify upper-trapezius muscle activation patterns using exposure variation analysis (EVA) in healthy computer workers and those with chronic neck-shoulder pain. Eight healthy and five chronic pain participants were asked to complete three computer-based tasks (TYPE, CLICK, and FORM) in two pacing conditions (self-paced and control-paced). EVA was used to quantify variation using five amplitude classes and five duration classes. Performance in each task was also quantified. Healthy workers and those with chronic pain did not differ in performance, and they both exhibited similarly low levels of muscle activation amplitude. Pain participants, however, were found to spend less time in lower duration classes across tasks and conditions. These results indicate that individuals with chronic neck-shoulder pain utilize movement strategies involving sustained durations of continuous muscle activation. This may be suggestive of decreased temporal variation in muscle activation patterns in those with chronic pain.

It’s A-bout Time: Detailed Patterns of Physical Activity in Obese Adolescents Participating in a Lifestyle Intervention

Background:The detailed patterns of physical activity and sedentary behaviors of overweight and obese adolescents are unknown, but may be important for health outcomes and targeted intervention design.Methods:Participants completed Curtin University’s Activity, Food and Attitudes Program (CAFAP), an 8-week intervention with 12 months of maintenance intervention. Physical activity and sedentary time were assessed at 6 time periods with accelerometers and were analyzed by 1) time and type of day, 2) intensity bout patterns using exposure variation analysis, and 3) individual case analysis.Results:Participants (n = 56) spent a lower percentage of time at baseline in light activity during school days compared with weekend days (24.4% vs 29.0%, P = .004). The majority of time was in long uninterrupted sedentary bouts of greater than 30 minutes (26.7% of total time, 36.8% of sedentary time at baseline). Moderate activity was accumulated in short bouts of less than 5 minutes (3.1% of total time, 76.0% moderate time). Changes varied by individuals.Conclusions:Exposure variation analysis revealed specific changes in activity patterns in overweight and obese adolescents who participated in a lifestyle intervention. A better understanding of these patterns can help to design interventions that meaningfully affect specific behaviors, with unique health consequences.

Capturing the Pattern of Physical Activity and Sedentary Behavior: Exposure Variation Analysis of Accelerometer Data

Background:Capturing the complex time pattern of physical activity (PA) and sedentary behavior (SB) using accelerometry remains a challenge. Research from occupational health suggests exposure variation analysis (EVA) could provide a meaningful tool. This paper (1) explains the application of EVA to accelerometer data, (2) demonstrates how EVA thresholds and derivatives could be chosen and used to examine adherence to PA and SB guidelines, and (3) explores the validity of EVA outputs.Methods:EVA outputs are compared with accelerometer data from 4 individuals (Study 1a and1b) and 3 occupational groups (Study 2): seated workstation office workers (n = 8), standing workstation office workers (n = 8), and teachers (n = 8).Results:Line graphs and related EVA graphs highlight the use of EVA derivatives for examining compliance with guidelines. EVA derivatives of occupational groups confirm no difference in bouts of activity but clear differences as expected in extended bouts of SB and brief bursts of activity, thus providing evidence of construct validity.Conclusions:EVA offers a unique and comprehensive generic method that is able, for the first time, to capture the time pattern (both frequency and intensity) of PA and SB, which can be tailored for both occupational and public health research.