Wearable Sensor Network for Biomechanical Overload Assessment in Manual Material Handling

Abstract

The assessment of risks due to biomechanical overload in manual material handling is nowadays mainly based on observational methods in which an expert rater visually inspects videos of the working activity. Currently available sensing wearable technologies for motion and muscular activity capture enables to advance the risk assessment by providing reliable, repeatable, and objective measures. However, existing solutions do not address either a full body assessment or the inclusion of measures for the evaluation of the effort. This article proposes a novel system for the assessment of biomechanical overload, capable of covering all areas of ISO 11228, that uses a sensor network composed of inertial measurement units (IMU) and electromyography (EMG) sensors. The proposed method is capable of gathering and processing data from three IMU-based motion capture systems and two EMG capture devices. Data are processed to provide both segmentation of the activity and ergonomic risk score according to the methods reported in the ISO 11228 and the TR 12295. The system has been tested on a challenging outdoor scenario such as lift-on/lift-off of containers on a cargo ship. A comparison of the traditional evaluation method and the proposed one shows the consistency of the proposed system, its time effectiveness, and its potential for deeper analyses that include intra-subject and inter-subjects variability as well as a quantitative biomechanical analysis.

Wearable Devices for Ergonomics: A Systematic Literature Review

“…We identified head, upper extremity, hand, trunk, lower extremity, foot as the relevant parts of the body, mainly based on the International Standard ISO 11226 [ 65 ]. Giannini et al [ 52 ] present the only wearable device that can be worn on all the six considered body segments: it is a sensor system composed of 17 IMUs placed on head, sternum, shoulder blades, upper arms, lower arms, hands, pelvis, upper legs, lower legs, and feet thanks to elastic bands and connected to a central unit, which in turn is connected to the battery pack that can last until 9.5 h.…”

“…All these 5 studies both monitoring a risk factor and guiding users towards more ergonomic conditions permit assessing or estimating the risk factor itself or a parameter correlated to it in real time. Besides them, other wearable devices give real-time outputs, such as sensor systems [ 43 , 44 , 50 , 52 , 58 ] and smart glasses [ 45 ]. However, most of the studies (13 out of 24) focus on wearable solutions recognising or detecting the risk factor itself or a parameter correlated to it only after the occurrence of the exposure.…”

“…Note that the ISO 11228-3 [ 68 ] establishes ergonomic recommendations for repetitive work tasks involving the manual handling of low loads at high frequency. The papers retrieved by this systematic literature review that mention this International Standard are Giannini et al [ 52 ] and Lenzi et al [ 55 ]. Both propose a sensor system for assessing the physical load of workers.…”

Classifier-Based Data Transmission Reduction in Wearable Sensor Network for Human Activity Monitoring

“…. n, where n corresponds to the total number of sensor nodes and meaning of the d i,t values was explained above for Equation (1).…”

“…Wireless wearable sensor networks are usually composed of several sensor nodes attached to human body or embedded in clothing [ 1 , 2 , 3 ]. The sensor nodes can monitor parameters of the body as well as its environment.…”