Modeling Heart Rate of Individual and Team Manual Handling with One Hand Using Generalized Additive Mixed Models

Overview

Journal BMC Med Res Methodol

Publisher Biomed Central

Specialties General Medicine
Health Services

Date 2024 Feb 15

PMID 38360533

Authors

Mohammad Hamed Hosseini

Rashid Heidarimoghaddam

Mehrdad Anbarian

Saeed Ilbeigi

Leili Tapak

Affiliations

Soon will be listed here.

Abstract

Objectives: Despite the fact that team manual handling is common in different working environments, the previous studies in this regard, particularly those with a physiological approach are quite limited. The present study is an attempt to model the heart rate (HR) of individual and team manual handling with one hand.

Methods: Twenty-five young men (aged 21.24±1.42 year) volunteered for this study. The experiments included individual and two-person handling of the load with three different weights with and without height difference. The participants' HR was registered at the end of the route by a chest-strap pulse monitor and a polar watch according to the manufacturer's recommendation. A multivariate Generalized Additive Mixed Model (MGAMM) was used for modeling heart rate based on explanatory variables of workload, carry method, HR, body weight, height, knee height, shoulder height, elbow height, and hand height. The significance level of the tests was considered as <0.05.

Results: Based on the MGAMM, the average HR (bpm) of participants increased as the workload increased (P<0.001). Handling the load with a taller person increased the HR compared to shorter partner (P<0.001). Moreover, the nonlinear associations of the resting HR (P<0.001), body weight (P<0.001), height (P<0.001), and the height of elbow, hand and knee (P<0.001) were statistically significant. The adjusted R of the model was 0.89 indicating that about 90 percent of the variations observed in HR could be explained by the variables in the model. This was greater than the model considering only linear effects (R =0.60).

Conclusion: The model obtained in this study can predict the heart rate of individual and team one-handed handling with high validity. The MGAMM can be used in modeling heart rate in manual handling.

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