Wearable Sensor Network for Biomechanical Overload Assessment in Manual Material Handling.

Area of Science:

• Ergonomics and Occupational Health
• Biomechanics
• Wearable Sensor Technology

Background:

• Manual material handling (MMH) risk assessment traditionally relies on subjective observational methods.
• Existing wearable technologies lack full-body coverage and effort evaluation for MMH.
• Standardized guidelines like ISO 11228 require objective and repeatable risk assessment measures.

Purpose of the Study:

• To develop and validate a novel system for comprehensive biomechanical overload assessment in MMH.
• To integrate inertial measurement units (IMU) and electromyography (EMG) sensors for full-body analysis.
• To provide objective, repeatable, and time-effective risk scoring aligned with ISO 11228 and TR 12295.

Main Methods:

• A sensor network combining three IMU systems and two EMG devices was utilized.
• Data processing included activity segmentation and ergonomic risk score calculation.
• The system was tested in a real-world scenario involving container handling on a cargo ship.

Main Results:

• The proposed system demonstrated consistency compared to traditional evaluation methods.
• The system proved to be time-effective for risk assessment.
• The technology enables deeper analyses, including intra- and inter-subject variability and quantitative biomechanical analysis.

Conclusions:

• The novel IMU and EMG-based system provides a robust solution for objective biomechanical overload assessment in MMH.
• This technology enhances the accuracy and efficiency of ergonomic risk evaluation.
• The system has significant potential for advancing occupational health and safety research and practice.