College of Education and Human Development

Kinesiology Program Faculty Receive Grant to Determine Effectiveness of AI-Integrated Wearable Sensor in Predicting Fatigue and Risk of Injury in Firefighters

Joel Martin, associate professor in the Kinesiology Program within the College of Education and Human Development (CEHD) at George Mason University, has received an MSD Research to Solutions (R2S) grant in support of a project that will focus on the effectiveness of an artificial intelligence (AI) powered tool, integrated with a wearable technology sensor device, in assessing the quality of the motion and movement of emergency responders and in identifying early biomechanical markers of fatigue that indicate whether they are at risk of musculoskeletal injury.

The Research to Solutions grant program is part of the MSD Solutions Lab, a partnership between the National Safety Council (NSC) and Amazon. Its purpose is to fund innovative, research-driven projects that reduce the risk of musculoskeletal disorders (MSDs) in the workplace by identifying, testing, and scaling solutions that can be implemented rapidly in real-world settings. As Principal Investigator, Martin is leading an interdisciplinary team of researchers from George Mason that includes Marcie Fyock, associate professor in CEHD’s Athletic Training Education and Kinesiology Programs, and Qi Wei, associate professor in the Department of Bioengineering within the College of Engineering and Computing.

Evidence shows that firefighters and emergency responders experience significant rates of musculoskeletal injuries on the job which can negatively impact their health, well-being, and performance readiness. In seeking to minimize some of these occupational risks, the current study is focused on developing and validating an AI–driven movement assessment tool, integrated with a wearable inertial measurement unit (IMU), that will determine how fatigue affects quality of movement and which will identify those biomechanical markers that can best predict the likelihood of MSD injury in emergency responders. The research team is hopeful that the study's findings will contribute to the body of knowledge on practices and strategies that can be implemented to prevent occupational injuries in firefighters.

The project involves the use of an AI-supported wearable IMU placed on the lower back which will capture data in real time on body angle, rotation, orientation, and other movements. Smartphone-based computer vision will be utilized to assess the movement of firefighters in real time as they complete a series of baseline fitness and motion assessments. This will be followed by a simulated occupational fatigue protocol consisting of tasks like victim drags, stair climbs, and loaded walking. Clinicians will independently evaluate the quality of the movement of firefighters, and these assessments will be compared with AI model outputs. In addition, clinicians will be interviewed to gather feedback on what they see as the challenges and opportunities associated with using this AI-supported wearable technology in occupational health settings.

Martin commented on the technology used in the study and elaborated on how it could be effective in reducing musculoskeletal disorders and injury in emergency responders. He stated, “The system uses a standard smartphone camera and a wearable IMU sensor to record movement during occupational tasks. AI models analyze posture, joint angles, and coordination to detect fatigue-related movement changes linked to injury risk. By identifying these changes early, the tool can help guide preventative exercise programs and modifications to work tasks, thereby reducing the likelihood of MSDs.”

In describing how this technology could become a powerful, scalable screening tool for fire departments worldwide, Martin stated, “It allows for rapid, objective assessments without requiring a clinician to be present, making it feasible for large agencies to monitor all personnel regularly. Over time, it could be integrated into routine fitness evaluations, wellness programs, and return-to-duty assessments.”

Throughout his academic career, Martin has sought to expand the knowledge base of the physical on-the-job stress that firefighters are routinely subjected to, and he has devoted his research to finding ways in which their risk of occupational injury can be reduced. He observed, “My research focuses on improving the health, safety, and performance of emergency responders through innovative, evidence-based solutions. I have worked closely with fire departments to understand occupational demands and develop performance assessments. This project aligns with my interest in using wearable technology, AI, and biomechanical analysis to create scalable tools that reduce injury risk in high-strain occupations.”

Martin shared his thoughts on what future research priorities should be as related to the use of AI supported wearable technology to reduce the incidence of musculoskeletal injury in emergency responders. He stated, “Future research should focus on validating these tools in real-world operational environments, integrating them into daily training and wellness programs, and developing predictive models that combine biomechanical, physiological, and workload data. Additionally, studies should explore long-term injury reduction and cost savings from implementing such technology.”

Concluding his remarks, Martin took a moment to acknowledge Yosef (“Yossi”) Shaul who is pursuing a PhD in Education with a Concentration in Kinesiology at George Mason and whose role in the project supports his dissertation research. Martin notes that in parallel with the R2S grant funded project, Shaul is developing a computer vision–based application for movement screening, for which a provisional patent has been filed and funding from the NIH Mid-South REACH program has been applied for.

Please join the CEHD community in congratulating Joel Martin on being awarded the MSD Research to Solutions (R2S) grant from the MSD Solutions Lab. This grant is indicative of his many contributions in researching how technology can play a significant role in improving the occupational health and well-being of emergency responders.