Wonil Lee, Ken-Yu Lin, Peter W. Johnson and Edmund Y.W. Seto
The identification of fatigue status and early intervention to mitigate fatigue can reduce the risk of workplace injuries. Off-the-shelf wearable sensors capable of assessing…
Abstract
Purpose
The identification of fatigue status and early intervention to mitigate fatigue can reduce the risk of workplace injuries. Off-the-shelf wearable sensors capable of assessing multiple parameters are available. However, using numerous variables in the fatigue prediction model can elicit data issues. This study aimed at identifying the most relevant variables for measuring occupational fatigue among entry-level construction workers by using common wearable sensor technologies, such as electrocardiogram and actigraphy sensors.
Design/methodology/approach
Twenty-two individuals were assigned different task workloads in repeated sessions. Stepwise logistic regression was used to identify the most parsimonious fatigue prediction model. Heart rate variability measurements, standard deviation of NN intervals and power in the low-frequency range (LF) were considered for fatigue prediction. Fast Fourier transform and autoregressive (AR) analysis were employed as frequency domain analysis methods.
Findings
The log-transformed LF obtained using AR analysis is preferred for daily fatigue management, whereas the standard deviation of normal-to-normal NN is useful in weekly fatigue management.
Research limitations/implications
This study was conducted with entry-level construction workers who are involved in manual material handling activities. The findings of this study are applicable to this group.
Originality/value
This is the first study to investigate all major measures obtainable through electrocardiogram and actigraphy among current mainstream wearables for monitoring occupational fatigue in the construction industry. It contributes knowledge on the use of wearable technology for managing occupational fatigue among entry-level construction workers engaged in material handling activities.
Details
Keywords
Honglei Liu, Jiule Song and Guangbin Wang
With the increasing attention acquired from researchers and practitioners in Architecture, Engineering and Construction (AEC) industry, building information modeling (BIM) has…
Abstract
Purpose
With the increasing attention acquired from researchers and practitioners in Architecture, Engineering and Construction (AEC) industry, building information modeling (BIM) has fundamentally changed the approach we design, construct and delivery, as well as operate and maintenance of buildings and civil infrastructures. This study tries to provide an innovative perspective on BIM research. This study aims to analyze the necessity and feasibility of BIM user satisfaction research and define what BIM user satisfaction is, and then to develop a quantitative method for the measurement of BIM user satisfaction.
Design/methodology/approach
As it is indicated in the content, BIM user satisfaction is measured by the sum of the user's weighted reactions to a set of factors. To be specific, the entropy method was adopted to calculate the “weighting” of the factors, and the triangular fuzzy number (TFN) method was selected to compute the “scoring” of the factors. Through the literature review, methodology and tool development, as well as case study and discussions, this paper was generated sequentially.
Findings
This study found that the proposed tool for the measurement of BIM success is valid and reliable; it formerly translated the conceptual definition of BIM user satisfaction into an accurate measurement instrument. It also indicated that many factors are affecting the BIM users' satisfaction, and each of the factors inherited various importance and score, and the findings are expected to improve the performance and effectiveness of BIM management.
Originality/value
Through the translation of the conceptual BIM user satisfaction into a valid quantitative measurement instrument, this research provides an excellent framework for the management of BIM from the user's perspective, and it could help to stimulate user's acceptance of BIM in the AEC industry in future.