Research Topics

Research Topics

Current Projects

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Predicting Forearm Muscle Activity in Hand-Intensive Work Tasks

This study aims to develop predictive models of forearm muscle activity in manually intensive work using readily obtainable variables such as age, sex, pain history, maximum grip strength, and self-reported hand force. While previous research has shown moderate success in predicting physical exposures during computer-based tasks, limited attention has been given to modeling muscle activity in manually-intensive jobs, which may involve greater variability and distinct influencing factors. By incorporating both individual characteristics and task-specific demands, this study seeks to assess the accuracy of estimating muscle load without relying on electromyography (EMG), which can be resource-intensive and require specialized expertise. These models could support more scalable ergonomic assessments in field settings where direct measurement is impractical. Ultimately, the goal is to inform exposure assessment and injury prevention strategies in physically demanding work environments.

Comparison of Sampling Strategies to Accurately Quantify the Duration and Frequency of Hand Exertion

Sampling strategies may impact the accuracy of measuring hand exertion frequency and duration, which are critical factors for assessing musculoskeletal disorder (MSD) risk. Using video analysis software, we analyzed short video segments of tasks categorized by pace-type. Repetition rate and duty cycle were calculated across different time intervals and job types, to assess within-subject and between-subject variability

Environmental Conditions and Recovery Strategies on Physiological Responses and Heat Stress Symptoms among Wildland Firefighters in Chile

The research aims to understand how heat, air pollution, and terrain characteristics influence the risk of experiencing heat stress events among wildland firefighters. Wearable devices are used to measure physiological variables such as heart rate, sweating, and body temperature to identify strategies that optimize recovery and prevent heat stress events.  The ultimate goal is to prevent these events, contributing to developing policies that promote a safer and more efficient work environment for wildland firefighters.

AI-based Video Tracking System for Ergonomics Risk Assessment

This study aims to validate an AI-based video tracking system for assessing ergonomic risks. Participants from various job categories will be included. By evaluating the system’s accuracy, reliability, and user acceptance, the research will demonstrate its potential to improve workplace ergonomics and reduce musculoskeletal disorders (MSDs). The findings could support the broader adoption of AI technologies in occupational health, offering an effective and scalable solution to the ongoing issue of MSDs in the workplace.

Prediction of Occupational Physical Activities using Inertial Measurement Units and Deep Learning Models

Machine learning models are applied to inertial measurement unit (IMU) data to predict occupational physical activities to provide a more reliable, informative and cost-effective approach to quantifying the physical demands of a job.

Poultry & Pork Line Speed Evaluation Study (PULSE) 

In conjunction with the USDA FSIS, this study seeks to determine possible health effects to establishment workers of increased evisceration line speeds in young chicken and pork processing plants, including ergonomic hazards in the workplace, measurement of biomechanical risk factors for acute and cumulative work-related musculoskeletal disorders (WRMSDs), medical management, and respiratory hazards from antimicrobial use.

LINK to poultry report: Poultry Processing Line Speed Evaluation Study (PULSE)

(PDF file)

LINK to swine report: Swine Processing Line Speed Evaluation Study (PULSE)

Janitor Workload Study

Janitor Workload Study 

This research study aims to assess workers' experiences with COVID-19 prevention measures at the worksite and how the work rate of janitors has been impacted by the pandemic. The study will determine the impact of work rate on janitor's health and safe and effective workloads for California Janitors. The study includes a qualitative survey and quantitative workload measurements using IMUs, Lumbar Motion Monitor, heart rate monitor and ActivPAL activity monitor.

Find recorded webinars about this project: COEH & California Labor Lab - YouTube

Evaluation of Exoskeletons for Construction Work​

In conjunction with Virginia Tech, we evaluated the use of lower back and shoulder exoskeletons for use in construction work.  This study is presented in a webinar hosted by the Center for Construction Research and Training (CPWR).

ENGLISH RESOURCES:

WATCH a short video about the project (English)

WEBINAR:  45-minutes about this project with more details (English)

​SPANISH RESOURCES:

WATCH a short video about the project (Spanish)