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Introduction: Manual materials handling (MMH) remains the professional activity associated with the most work-related musculoskeletal disorders (MSD). Some reviews have observed limited evidence on the effectiveness of MMH training. However, the short format of training without dedicated practice and relevant feedback is often criticized. While real-time biomechanical feedback as shown performance improvements in sports, it has been seldom used in work settings. The objective of this project was to develop a human-machine interface suitable for augmented biomechanical feedback during MMH training. A software provided visual feedback based on MSD risk metrics obtained from inertial motion capture tracking the handler and digital cameras tracking the boxes and the environment.

Methods: The software consists of five modules:

1. The reading and display in near real time of human motion data from full-body inertial sensors (MVN Link, Xsens, Movella) broadcasting in a continuous stream.
2. Capturing three-dimensional object motion from several video cameras (Azure Kinect DK, Microsoft) calibrated and synchronized in time with the sensors, and detecting key events to break down handling cycles.
3. The development of biometrics adapted to MMH activities, allowing the characterization of gesture efficiency and health risks.
4. An interpretation module based on user-selected training objectives, enabling tracking of a group of associated metrics over rehearsals and sessions.
5. A structured database that allows for the reactivation of a trial or session and offers the potential for supplementary analyses.

Results: Preliminary tests of the training were conducted on four novice handlers working in a food distribution centre. An experienced ergonomist guided them through several pedagogical exercises for two and a half days. Additional exercises were achieved in the measurement area where visual feedback was provided.

A sequence of box handling composed of various masses, lift and deposit height and transfer distances was repeated. The first sequence was achieved without instructions at the beginning of the day to serve as reference. The back loading values and risk metrics obtained during this first sequence were set as an objective when practicing in the measurement area after the pedagogical exercises. The four handlers were generally able to reduce the targeted type of back loading after dedicated practice.

Discussion: Progressive objectives were defined based on maximal sagittal L5/S1 moment, maximal asymmetrical L5/S1 moment and cumulative L5/S1 moment. To help the handlers understand their maximal sagittal L5/S1 moment, the trunk inclination and lever arm of the box were provided during the box transfer. Similarly, the maximal asymmetrical L5/S1 moment could be supplemented by values of postural asymmetry of the back, alignment between the box and the body and footprints at lift. The cumulative L5/S1 moment was often associated to the lifting duration and displacement strategy. Many other metrics could be provided as needed such as stability, path of the box or body and inter-joint coordination.

Conclusion: This type of novel MMH training shows potential to reduce MSDs and needs to be further evaluated.