Evaluation of Mental and Physical Load During Lab-simulated Industrial Work
Phase: NA
Conditions: Work-Related Condition, Physical Stress, Mental Fatigue
Sponsor: Vrije Universiteit Brussel

Protocol Trial 
 
 
Title of the project 
Wearable Robotic Upper Body Exoskeleton for Workers (Exo4Work) 
 
Objective of the study 
The overall objective of the Exo4Work project is to design, develop and validate a smart 
modular exoskeleton for spinal, torso and upper limb support to assist workers, to reduce the 
physical load on workers, keep older workers active for a longer period of time, increase 
quality of work, reduce fatigue, and prevent injuries. 
 
The objective of this study is to assess physical and mental load of industrial work in 
laboratory conditions. 
 
Investigator(s) 
Prof. Dr. Romain Meeusen (PI, MFYS-VUB) – Romain.Meeusen@vub.be – responsible head 
of the research group 
Dr. Kevin De Pauw (MFYS-VUB) – Kevin.De.Pauw@vub.be 
Drs. Sander De Bock (MFYS-VUB) – Sander.De.Bock@vub.be 
Bert Pluym (MFYS-VUB) – Bert.Pluym@vub.be 
 
Departments/laboratories involved in the study 
Research group Human Physiology (MFYS-VUB) – 02/629 22 22 
Pleinlaan 2, 1050 Brussel 
 
Introduction 
 
It is acknowledged that industrial workers face high risks of musculoskeletal injuries, such as 
lower back pain, since they work in small places and non-ergonomical postures. Besides 
providing preventive evidence-based practical guidelines to support occupational safety and 
health, a potential solution can be found in the research field of Human-Centered Robotics, 
i.e. the implementation of exoskeletons. An exoskeleton is a wearable, external mechanical 
structure that assists the operator during human movement.  
 
Companies gain increasing interest in the implementation of exoskeletons in the working 
environment with the aim to improve work efficiency and reduce work-related injuries. The 
research field about the implementation of exoskeletons in field conditions is novel. After an 
observational, ergonomic evaluation of work postures during different industrial tasks in an 
earlier stage of the project, the current study will simulate industrial work in laboratory 
settings. The outcome will be an ergonomic evaluation of postures of industrial work using 
physiological and biomechanical data. 
 
Study design 
 
The design of the study is interventional, cross-over (in laboratory conditions).  
 
The subjects 
 
Number of subjects 
 

During this experiment twelve healthy subjects will be recruited. Experiments wherein 
industrial work will be simulated in laboratory settings will be conducted. These experimental 
trials will take place at VUB (climate chamber, research group MFYS). 
 
Inclusion criteria 
 
Healthy males between 18-65 yrs 
 
Exclusion criteria 
 
Injuries 
 
Replacement of subjects 
 
New subjects will be recruited in case of drop out. 
 
Restrictions and prohibitions for the subjects 
 
/ 
 
Procedures 
 
The physical and mental load of simulated industrial work will be investigated in laboratory 
conditions. Each subject will perform a pre-test and three lab trials. The pre-test (1h) will 
include basic biometric measurements, simple motor tasks (e.g. squatting), a dual-task 
walking task using the cognitive Stroop task to determine reaction time and accuracy during 
walking (Arcelin et al., 1998) and a familiarization trial of the simulated industrial task 
(described further down this protocol). 
A first lab trial will include a cognitive task (90 min, 2-back task (Massar et al., 2010) 
(cognitive component). During a second trial a 90 minute walking task will be performed 
(physical component). The third trial will exist out of a simulated industrial task (physical and 
cognitive component). The simulated industrial task will be a 90 minute task during which 
boxes (max 15 kg) will be moved from one place to another (0.05 Hz) while also performing 
a cognitive task (2-back task). Before and after the cognitive, physical or simulated industrial 
task a 10 minute Stroop task will be performed. 
In the laboratory the ergospirometric device K5 (Cosmed) will be attached to the subject to 
measure oxygen consumption (via a mask) and indirectly energy expenditure. A heart 
frequency monitor (Polar) will be attached using a chest belt. The non-invasive electro-
encaphalography (EEG) and electro-myography (EMG) electrodes will be placed on the 
subjects head using non-invasive EEGcap and EMG surface electrodes, respectively. 
Furthermore, different questionnaires will be used, i.e. the Rating of Perceived Exertion 
(RPE), the Profile of Mood States (POMS), the Local Discomfort Scale, the Visual Analogue 
Scale (VAS) for fatigue, Nasa TLX, heat scores and Need for Recovery scale. In simulated 
industrial settings oxygen consumption and heart rates will be determined, as well as 
following questionnaires: RPE, POMS, Local Discomfort Scale, VAS for fatigue, Nasa TLX, 
heat scores and Need for Recovery scale. 
 
Flowchart 
 

Twelve subjects will be included to conduct experiments in laboratory conditions. Three 
experimental trials per subject will be planned. One trial will include a simulated industrial 
task during which boxes are moved while walking on a treadmill. The intensity of the task 
will be determined based on the results of an ongoing observational study which 
ergonomically evaluates industrial work (approximated max 15 kg, lifting frequency of 0.05 
Hz). During the second trial, a 90 minute normal walking task on a treadmill will be executed. 
The third trial will include a 90 minute cognitive task (2-back task). Before and after each trial 
a 10 minute Stroop task will be performed in order to analyse the cognitive performance of 
the subject. The total duration of one experimental trial is 3 hours. 
 
 
 
Randomisation/blinding 
 
The order of the executed trials will be randomly assigned to avoid possible sequence effects. 
No blinding occurs. 
 
Prior and concomitant therapy 
 
Before the subjects start their first experimental trial, the health status of the subjects will be 
checked (Par-Q). 
 
Study analysis 
 
Sample size calculation 
Twelve subjects will be recruited to perform laboratory tests in a cross-over design. This 
amount of subjects is similar to the cohort size used in an earlier cross-over mental fatigue 
studie concering exercise (Martin et al., 2015).  
 
Analysis of the samples 
Physiological data gathering and analysis will be conducted by a PhD student of MFYS, 
Sander De Bock (Sander.De.Bock@vub.be). Ergospirometrical data will be gathered with the 
ergospirometrical device K5 from Cosmed and extracted to an Excel file using the program 
Omnia (Cosmed). Heart rate monitoring using Polar is a wireless and continuous process. 
Electro-physiological data (EXG, such as EMG, EEG) will be collected using Brain Vision 
Recorder (BrainProducts) and analysed using Brain Vision Analyzer (BrainProducts). 
 
Statistical analysis 
The physiological data will be statistically analysed with IBM SPSS statistics 25. Normality 
tests (Shapiro-Wilk normality testing) will precede parametric or non-parametric testing. Data 

analysis of electro-physiological data will be conducted using Brain Vision Analyzer, wherein 
data will be pre-processed (signal filtering, re-referencing, artefact removal) and processed 
(power spectral analysis, coherence and non-invasive brain imaging). From Brain Vision 
Analyzer files will be extracted and inserted in standardized Low Resolution Brain 
Electromagnetic Tomography or sLORETA. The statistical analysis performed in sLORETA 
is Statistical non-parametric mapping or SnPM using the Fisher’s permutation test that relies 
on 
a 
Bootstrap 
method 
with 
5000 
randomizations. 
Sander 
De 
Bock 
(Sander.De.Bock@vub.be) is responsible for the physiological data analyses. 
 
Quality control and quality assurance 
 
To ensure data quality (heart rate and oxygen consumption) outliers will be detected and 
removed. Preceding the determination of oxygen uptake using the mobile ergospirometric 
device K5 the device will be calibrated to obtain accurate data. Additionally, a well fit mask 
will be used per individual (mask sizes range from extra-small, small, medium, large to extra-
large). The latter will avoid leakage of air from the mask to the ambient air. 
 
EEG electrodes are embedded in an EEGcap (different sizes from 54 to 60 (cm) according to 
head size). The electrical signal will be optimized using a gel between the electrodes and the 
skin of the subjects’ head. Raw data will be recorded, but during recording the electrode 
impedance (indicator of signal quality) needs to be always kept below 10kΩ. Furthermore, 
during recording basic noise-reducing filters can be applied to allow the focus on the EEG 
frequency range of interest. The post-hoc pre-processing (basic filters and artefact removal) 
steps are performed by one researcher (Sander De Bock) and state-of-the-art pre-processing 
steps (such as Independent Component Analysis) are conducted to assure data quality. 
 
Data management 
 
Questionnaires filled out during the experiment will be scanned in and digitalized. 
Physiological data will be measured by specific devices and stored locally on laboratory 
computers. After each experiment, the data will be restored on the investigators personal 
computer or external hard drive. The laboratory computer, as well as the investigators 
personal computer are embedded in a back-up loop which backs up twice a day to the 
laboratory’s Synology NAS system. 
 
Publication policy 
 
The publication policy of the research group is to publish papers in international peer-
reviewed journals (preferably Q1 journals). All authors should have made substantial 
contributions to (1) the design of the study or acquisition of data or analysis and interpretation 
of data, (2) drafting the article or revising it critically, (3) final approval of the version to be 
submitted. 
 
References 
 
Arcelin, R., Delignieres, D., & Brisswalter, J. (1998). Selective Effects of Physical Exercise 
on Choice Reaction Processes. Perceptual 
and Motor Skills, 87(1), 175–185. 
https://doi.org/10.2466/pms.1998.87.1.175 

Massar, S. A. A., Wester, A. E., Volkerts, E. R., & Kenemans, J. L. (2010). Manipulation 
specific effects of mental fatigue: Evidence from novelty processing and simulated driving. 
Psychophysiology, 47(6), 1119–1126. https://doi.org/10.1111/j.1469-8986.2010.01028.x 
Martin, K., Thompson, K. G., Keegan, R., Ball, N., & Rattray, B. (2015). Mental fatigue does 
not affect maximal anaerobic exercise performance, 715–725. https://doi.org/10.1007/s00421-
014-3052-1