Objectives: Assessing exposure to physical risk factors during variable noncyclic work can be problematic. The purpose of this study was to modify an existing data reduction method for directly quantifying physical exposures during variable noncyclic work.
Methods: Myoelectric activity of the finger flexors of two groups of workers, heavy equipment operators (N=25) and mechanics (N=25), was sampled to determine the intensity and duration of forceful exertions during normal tasks. Data were reduced with a modification of the exposure variation analysis (EVA), called clustered EVA (CEVA), using three intensity and two duration categories. A two-way, mixed-effects, repeated-measures analysis of variance evaluated the percentage of sampled work time in each CEVA category.
Results: CEVA was able to quantify variable noncyclic work, and it contrasted the work of the two groups, with simple effects significantly different for all the exposure categories. The mechanics performed high-intensity short-duration contractions 9.1% of the time, whereas the operators had similar contractions only 1.8% of the time. Conversely, the operators used low-intensity contractions of prolonged duration over 81% of the time, compared with only 43% for the mechanics.
Conclusions: CEVA is a useful modification of EVA for contrasting the noncyclic work typical of understudied industries like construction. A simplification of electromyography with summary measures such as CEVA provides a comprehensible, yet accurate measure of forceful exertions during worktasks.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.5271/sjweh.742 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Divergent patterns of locomotor activity in cave isopods (Oniscidea: Styloniscidae) in Neotropics.
Chronobiol Int
August 2024
Center of Studies on Subterranean Biology, Department of Ecology and Conservation, Federal University of Lavras, Lavras, Brazil.
In cave environments, stable conditions devoid of light-dark cycles and temperature fluctuations sustain circadian clock mechanisms across various species. However, species adapted to these conditions may exhibit disruption of circadian rhythm in locomotor activity. This study examines potential rhythm loss due to convergent evolution in five semi-aquatic troglobitic isopod species (Crustacea: Styloniscidae), focusing on its impact on locomotor activity.
View Article and Find Full Text PDFPrevalence of chronic pelvic pain and associated factors among indigenous women of reproductive age in Ecuador.
BMC Womens Health
July 2024
Department of Obstetrics and Gynecology, Laboratory for Translational Data Science, Ribeirão Preto Medical School of the University of São Paulo USP, Bandeirantes Avenue. Monte Alegre. Ribeirão Preto, Ribeirão Preto, SP, 3900, 049-900, Brazil.
Article Synopsis
- Chronic pelvic pain affects around 4% of reproductive-age women in developed countries, with likely higher prevalence in developing nations, significantly impacting personal and socioeconomic conditions, especially for vulnerable populations like indigenous women.
- *The study aimed to assess the prevalence of chronic pelvic pain types (dysmenorrhea, dyspareunia, non-cyclical pain) in indigenous women from Otavalo, Ecuador, using a cross-sectional survey of 2,429 participants.
- *Results showed that the prevalence rates were 26.6% for dysmenorrhea, 8.9% for non-cyclic pelvic pain, and 3.9% for dyspareunia, with various social and health factors linked to these conditions,
Objective: Real-time measurement of biological joint moment could enhance clinical assessments and generalize exoskeleton control. Accessing joint moments outside clinical and laboratory settings requires harnessing non-invasive wearable sensor data for indirect estimation. Previous approaches have been primarily validated during cyclic tasks, such as walking, but these methods are likely limited when translating to non-cyclic tasks where the mapping from kinematics to moments is not unique.
View Article and Find Full Text PDFSleep-phasic heart rate variability predicts stress severity: Building a machine learning-based stress prediction model.
Stress Health
August 2024
Department of Pharmacology, Shanghai Medical College, Fudan University, Shanghai, China.
We propose a novel approach for predicting stress severity by measuring sleep phasic heart rate variability (HRV) using a smart device. This device can potentially be applied for stress self-screening in large populations. Using a Holter electrocardiogram (ECG) and a Huawei smart device, we conducted 24-h dual recordings of 159 medical workers working regular shifts.
View Article and Find Full Text PDFA thematic synthesis of qualitative studies and surveys of the psychological experience of painful endometriosis.
BMC Womens Health
January 2024
Research Dept of Clinical, Educational & Health Psychology, University College London, Gower St, London, WC1E 6BT, UK.
Background: Endometriosis is a widespread problem in women of reproductive age, causing cyclical and non-cyclical pain in the pelvis and elsewhere, and associated with fatigue, fertility problems, and other symptoms. As a chronic pain problem, psychological variables are important in adjustment and quality of life, but have not been systematically studied.
Methods: A systematic search of multiple databases was conducted to obtain surveys and qualitative studies of women's experience of pain from endometriosis.
Want AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!