Effects of load carrying techniques on gait parameters, dynamic balance, and physiological parameters during a manual material handling task

Abstract

PurposeSince construction workers often need to carry various types of loads in their daily routine, they are at risk of sustaining musculoskeletal injuries. Additionally, carrying a load during walking may disturb their walking balance and lead to fall injuries among construction workers. Different load carrying techniques may also cause different extents of physical exertion. Therefore, the purpose of this paper is to examine the effects of different load-carrying techniques on gait parameters, dynamic balance, and physiological parameters in asymptomatic individuals on both stable and unstable surfaces.Design/methodology/approachFifteen asymptomatic male participants (mean age: 31.5 ± 2.6 years) walked along an 8-m walkway on flat and foam surfaces with and without a load thrice using three different techniques (e.g. load carriage on the head, on the dominant shoulder, and in both hands). Temporal gait parameters (e.g. gait speed, cadence, and double support time), gait symmetry (e.g. step time, stance time, and swing time symmetry), and dynamic balance parameters [e.g. anteroposterior and mediolateral center of pressure (CoP) displacement, and CoP velocity] were evaluated. Additionally, the heart rate (HR) and electrodermal activity (EDA) was assessed to estimate physiological parameters.FindingsThe gait speed was significantly higher when the load was carried in both hands compared to other techniques (Hand load, 1.02 ms vs Head load, 0.82 ms vs Shoulder load, 0.78 ms). Stride frequency was significantly decreased during load carrying on the head than the load in both hands (46.5 vs 51.7 strides/m). Step, stance, and swing time symmetry were significantly poorer during load carrying on the shoulder than the load in both hands (Step time symmetry ration, 1.10 vs 1.04; Stance time symmetry ratio, 1.11 vs 1.05; Swing time symmetry ratio, 1.11 vs 1.04). The anteroposterior (Shoulder load, 17.47 mm vs Head load, 21.10 mm vs Hand load, −5.10 mm) and mediolateral CoP displacements (Shoulder load, −0.57 mm vs Head load, −1.53 mm vs Hand load, −3.37 ms) significantly increased during load carrying on the shoulder or head compared to a load in both hands. The HR (Head load, 85.2 beats/m vs Shoulder load, 77.5 beats/m vs No load, 69.5 beats/m) and EDA (Hand load, 14.0 µS vs Head load, 14.3 µS vs Shoulder load, 14.1 µS vs No load, 9.0 µS) were significantly larger during load carrying than no load.Research limitations/implicationsThe findings suggest that carrying loads in both hands yields better gait symmetry and dynamic balance than carrying loads on the dominant shoulder or head. Construction managers/instructors should recommend construction workers to carry loads in both hands to improve their gait symmetry and dynamic balance and to lower their risk of falls.Practical implicationsThe potential changes in gait and balance parameters during various load carrying methods will aid the assessment of fall risk in construction workers during loaded walking. Wearable insole sensors that monitor gait and balance in real-time would enable safety managers to identify workers who are at risk of falling during load carriage due to various reasons (e.g. physical exertion, improper carrying techniques, fatigue). Such technology can also empower them to take the necessary steps to prevent falls.Originality/valueThis is the first study to use wearable insole sensors and a photoplethysmography device to assess the impacts of various load carrying approaches on gait parameters, dynamic balance, and physiological measures (i.e. HR and EDA) while walking on stable and unstable terrains.

Biomechanical Assessments of the Upper Limb for Determining Fatigue, Strain and Effort from the Laboratory to the Industrial Working Place: A Systematic Review

“…In particular, 71% of the laboratory studies enrolled volunteers that did not have working experience related to the topic of the study and only 23% enrolled workers. In a minor number of laboratory studies (6%), the data were simulated starting from real recordings with biomechanical models (as in Brambilla et al [ 109 ]) or completely simulated. Conversely, 99% of the workplace papers had enrolled workers.…”

A Systematic Review of Gait Analysis in the Context of Multimodal Sensing Fusion and AI

“…IMU sensors were used to analyze the total head movement and segment the gait, while an adaptive de-noising framework was built to describe and manage the motion artifact contamination in EEG readings. Using EDA and HR data, Anwer et al [57] investigated the impact of load bearing strategies on gait metrics, which indicated that carrying burdens with both hands increased gait symmetry, dynamic balance, and decreased the chance of falling.…”

Application of Neuroscience Tools in Building Construction – An Interdisciplinary Analysis

“…Wearable biosensors with integrated EDA capabilities are used in construction safety studies to obtain physiological signals from workers to assess their stress levels and the physical demands required for different jobs ( Jebelli et al, 2019 ). For example, studies have found that workers with loads produce higher EDA values than those without loads ( Anwer et al, 2021 ), and EDA can also be used to predict concentration levels by monitoring workers’ biosignals ( Kim et al, 2021 ). EDA is often used in conjunction with VR in architectural design research to investigate the perception of human experience and emotional responses in architectural spaces and built environments ( Ergan et al, 2019 ).…”