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N.B. Researchers Put Caregiver Strain Under AI Motion Capture

A new four-year program led by Université de Moncton and UNB kinesiologists will study injuries in long-term care. The same team is already using camera-based AI motion capture to test a powered bed that turns residents.

Closing card: a caregiver standing upright beside a powered bed with motion-tracking lines over her joints, the Université de Moncton and UNB logos, and a New Brunswick outline with pins on Moncton and Fredericton

Two New Brunswick kinesiologists who measure how caregivers' bodies move have a new four-year research program. WorkSafeNB announced on Oct. 15 that more than $1.6 million in combined funding from WorkSafeNB, Mitacs, the New Brunswick Continuing Care Safety Association (NBCCSA) and ResearchNB will support a program on the physical demands of caregiving in the province's long-term care homes.

It is led by Michelle Cardoso, associate professor and Research Chair in Healthcare and Ergonomics at the Université de Moncton, and Wayne Albert, full professor of kinesiology at the University of New Brunswick.

Why it matters

Health-care workers have some of the highest rates of work-related musculoskeletal injuries of any occupation in Canada. WorkSafeNB says previous research estimates those injuries cost New Brunswick's long-term care sector about $8 million a year, through lost work time, staffing pressures and added strain on the health system.

The program sets four goals:

  • Find patterns and causes of workplace injuries through province-wide epidemiological research.
  • Measure the physical demands of caregiving with advanced biomechanical and ergonomic assessments, in the lab and in real care settings.
  • Develop and evaluate innovative technologies, ergonomic interventions and training techniques that reduce injury risk.
  • Work with health-care organizations across New Brunswick to put the findings into practice.

Rather than one study, it is meant to be a long-term research platform. Planned work includes resident handling, transfers, toileting, injury surveillance, and what helps or hinders the adoption of new equipment and technologies. Through Mitacs, it will train 23 undergraduate, graduate and postdoctoral researchers.

"Our vision extends beyond individual projects," Cardoso said in the release. "We are building a sustainable research program that will continue generating solutions for years to come."

The announcement does not name any specific device or technology. The team's recent work shows the kind of tools it brings.

Motion capture without markers

Cardoso and Albert's team is using Theia3D, an AI-powered markerless motion capture platform made by Theia, to study how caregivers move when they reposition a patient in bed. The software turns video from standard cameras into full-body 3D movement data, with no reflective markers or body sensors. Theia announced the project on Aug. 11.

That matters in a crowded bedside scene. According to Theia's release, the team's earlier marker-based setup needed about 72 markers on the caregiver, 15 on the simulated patient and another 8 to 10 on the bed.

"Without the need for reflective markers, we can collect and process data much more efficiently, reducing both experimental setup and data processing time," Cardoso said in Theia's release. She added that the approach "has the potential to bring motion analysis into real-world clinical settings."

"These measurements provide the evidence we need to evaluate new technologies and determine which approaches can reduce the physical demands placed on caregivers," Albert said.

A bed that does the turning

The device under test is the Vendlet, a powered repositioning system that uses motorized side rails and special sheets to turn and reposition a patient in bed. The team is comparing manual patient handling with and without it across nearly 550 lab trials with simulated patients. Theia's release says the team is the first in North America to evaluate the system, and that its lab houses the only Vendlet available for research on the continent.

The researchers shared preliminary results at the 2026 World Congress of Biomechanics in July. Compared with trained manual techniques, the Vendlet was associated with more neutral caregiver postures, lower joint and spinal forces, less cumulative loading, and lower perceived discomfort and effort during simulated repositioning tasks. The team plans to publish further results.

Theia's release also reports that on June 25, ResearchNB, the Research and Productivity Council and NBCCSA visited the lab. They discussed developing a bracket system to make the Vendlet compatible with North American medical beds, and explored pursuing patent protection for the design.

The sensor trial behind it

The work builds on an earlier lab study registered as NCT06285786, sponsored by UNB and run at the Université de Moncton from September 2023 to April 2024. Twenty-eight nursing students performed four repositioning tasks on a long-term care bed with and without the Vendlet, before and after training in safe patient handling.

The lab measured them with marker-based motion capture, surface electromyography on eight pairs of muscles, galvanic skin response and heart-rate monitors for stress, and pressure mats on the bed and under their feet. One stated goal was to measure how far a markerless system's results differ from the marker-based standard, to judge whether such studies could later be done in real care settings.

Earlier Vendlet work was funded in part through Mitacs Accelerate, with ResearchNB as partner. Albert's Occupational Performance Lab at UNB lists graduate projects on cumulative shoulder and back loads with patient-transfer aids, injury rates among care providers, and the barriers to bringing technology into long-term care.

Sources

ChronologyUNB· 44 stories since Nov 20, 2024

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