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Wearable Sensors and Robotic Devices to Prevent and Monitor Work-Related Diseases

A special issue of International Journal of Environmental Research and Public Health (ISSN 1660-4601). This special issue belongs to the section "Occupational Safety and Health".

Deadline for manuscript submissions: closed (31 July 2022) | Viewed by 16591

Special Issue Editors

Dr. Juri Taborri

E-Mail Website
Chief Guest Editor
Department of Economics, Engineering, Society and Business Organization, Tuscia University, Largo dell’Università Snc, 01100 Viterbo, VT, Italy
Interests: measurements; sensors; artificial intelligence; virtual reality; robotics; biomedical engineering
Special Issues, Collections and Topics in MDPI journals
Dr. Simone Pasinetti

E-Mail Website
Guest Editor
Vis4Mechs Lab, Department of Mechanical and Industrial Engineering, University of Brescia, 25123 Brescia, Italy
Interests: mechanical and thermal measurements; industrial robotics; collaborative robotics; wearable robotics; biomechanics of human body; 2D and 3D vision systems

Special Issue Information

Occupational and work-related diseases are disorders caused by exposure to risk factors arising from work activities. Of these, motor disorders related to the musculoskeletal system represent one of the main categories that can lead to both fatal and nonfatal injuries. Epicondylitis, carpal tunnel syndrome, and neck and back disease are just some examples of the main common disorders. The accurate measurement and monitoring of parameters related to worker movements in the workplace can lead to early prediction of the disorders, guaranteeing the possibility to implement a specific program for worker safety and/or to improve workplace conditions. In addition, the use of assistive and supporting devices for helping workers during the execution of specific challenging activities can lead to a reduction of motor disorder occurrence.

In the last year, technological advancements have allowed expansion in the applicability of human motion analysis that has also been applied in work environments. This is due to the advent of wearable sensors which are able to measure useful parameters for motor assessment through synthetic quantitative indices. Among the various types of sensors, inertial sensors are the most widespread for both kinematic and balance analysis, while force transducers are the most popular for kinetic analysis. In addition, wearable sensors for physiological parameters, such as heart rate, blood pressure, and energy consumption, can provide additional useful information on worker health condition. With regard to assistive and supportive devices, wearable exoskeletons as well as robots have shown their potential to reduce the efforts of workers and to improve the working conditions.

This Special Issue aims to promote innovative technologies and methodologies for the assessment of worker motion and health condition, as well as the development of supporting robotic devices. Original research contributions as well as review articles are welcome. 

Potential topics include but are not limited to the following:

  • Innovative methodologies for worker motion analysis and health condition monitoring;
  • Application of wearable sensors for worker motion analysis and health condition monitoring;
  • Design of innovative sensors for worker motion analysis and health condition monitoring;
  • Application of robotic devices for supporting workers;
  • Design of innovative robotic devices for supporting workers;
  • Artificial intelligence for evaluating work safety;
  • Algorithms for evaluation of ergonomic worker condition;
  • Synthetic indices for work-related disorder prevention;
  • Guidelines for the implementation of specific programs to address worker safety.

Dr. Juri Taborri
Dr. Simone Pasinetti
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. International Journal of Environmental Research and Public Health is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2500 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • biomechanics
  • wearable sensors
  • motion analysis
  • measurements
  • robotics
  • ergonomics
  • occupational safety
  • artificial intelligence
  • exoskeletons
  • occupational disorders
  • physiological parameters

Published Papers (5 papers)

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Research

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21 pages, 4354 KiB  
Article
Is There a Difference in Brain Functional Connectivity between Chinese Coal Mine Workers Who Have Engaged in Unsafe Behavior and Those Who Have Not?
by Fangyuan Tian, Hongxia Li, Shuicheng Tian, Chenning Tian and Jiang Shao
Int. J. Environ. Res. Public Health 2022, 19(1), 509; https://doi.org/10.3390/ijerph19010509 (registering DOI) - 3 Jan 2022
Cited by 5 | Viewed by 2412
Abstract
(1) Background: As a world-recognized high-risk occupation, coal mine workers need various cognitive functions to process the surrounding information to cope with a large number of perceived hazards or risks. Therefore, it is necessary to explore the connection between coal mine workers’ neural [...] Read more.
(1) Background: As a world-recognized high-risk occupation, coal mine workers need various cognitive functions to process the surrounding information to cope with a large number of perceived hazards or risks. Therefore, it is necessary to explore the connection between coal mine workers’ neural activity and unsafe behavior from the perspective of cognitive neuroscience. This study explored the functional brain connectivity of coal mine workers who have engaged in unsafe behaviors (EUB) and those who have not (NUB). (2) Methods: Based on functional near-infrared spectroscopy (fNIRS), a total of 106 workers from the Hongliulin coal mine of Shaanxi North Mining Group, one of the largest modern coal mines in China, completed the test. Pearson’s Correlation Coefficient (COR) analysis, brain network analysis, and two-sample t-test were used to investigate the difference in brain functional connectivity between the two groups. (3) Results: The results showed that there were significant differences in functional brain connectivity between EUB and NUB among the frontopolar area (p = 0.002325), orbitofrontal area (p = 0.02102), and pars triangularis Broca’s area (p = 0.02888). Small-world properties existed in the brain networks of both groups, and the dorsolateral prefrontal cortex had significant differences in clustering coefficient (p = 0.0004), nodal efficiency (p = 0.0384), and nodal local efficiency (p = 0.0004). (4) Conclusions: This study is the first application of fNIRS to the field of coal mine safety. The fNIRS brain functional connectivity analysis is a feasible method to investigate the neuropsychological mechanism of unsafe behavior in coal mine workers in the view of brain science. Full article
(This article belongs to the Special Issue Wearable Sensors and Robotic Devices to Prevent and Monitor Work-Related Diseases)
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35 pages, 7893 KiB  
Article
Development of a Personal Ultrasound Exposimeter for Occupational Health Monitoring
by Michal Cieslak, Christoph Kling and Andrea Wolff
Int. J. Environ. Res. Public Health 2021, 18(24), 13289; https://doi.org/10.3390/ijerph182413289 - 16 Dec 2021
Cited by 1 | Viewed by 2661
Abstract
Prolonged exposure to airborne ultrasound in a workplace can have a detrimental influence on a worker’s well-being. Given the ever-increasing use of ultrasonic industrial equipment, it is of vital importance—and may also be regulated by law—to monitor ultrasound exposure during a normal workday [...] Read more.
Prolonged exposure to airborne ultrasound in a workplace can have a detrimental influence on a worker’s well-being. Given the ever-increasing use of ultrasonic industrial equipment, it is of vital importance—and may also be regulated by law—to monitor ultrasound exposure during a normal workday as part of workplace risk assessment. However, the devices currently utilized exhibit limitations with regard to both their operational frequency and their portability (wearability). In this paper, the first prototype of a high-frequency and ultrasound personal exposimeter is presented in the light of the latest national and international standards governing high-frequency and ultrasonic noise measurement in the field of occupational health monitoring. The prototype was tested in the laboratory environment in order to assess its sound level detection capabilities in both the audible and ultrasonic frequency ranges. Several common industrial scenarios—including an ultrasonic welding machine, an ultrasonic cleaning bath, and a compressed air gun—were simulated in a laboratory environment. For each simulated set-up, a corresponding high-frequency or ultrasonic signal was fed through a specially prepared generation chain. Each experimental scenario was initially surveyed with an ultrasound level meter previously tested up to 100 kHz. This was followed by a measurement with the prototype. For this study, the simulated sound signals varied between 10 kHz and 40 kHz on the frequency scale and between 60 dB and 90 dB in amplitude. The portability of the prototype, which may be required to be worn throughout an entire workday (e.g., 8 h), was also considered. All the experiments were performed on a customized ultrasound measurement set-up within a free-field environment located at the Physikalisch-Technische Bundesanstalt (PTB) in Braunschweig, Germany. Results obtained suggest a good agreement between the measurements performed with both devices in the louder areas of the sound fields produced. Because the overall measurement uncertainty is highly dependent on the specificity of the individual measurement set-up and measurement procedure, an uncertainty budget estimated for the prototype considers electro-acoustical contributions only. Full article
(This article belongs to the Special Issue Wearable Sensors and Robotic Devices to Prevent and Monitor Work-Related Diseases)
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10 pages, 696 KiB  
Article
Sitting Posture during Prolonged Computer Typing with and without a Wearable Biofeedback Sensor
by Yi-Liang Kuo, Kuo-Yuan Huang, Chieh-Yu Kao and Yi-Ju Tsai
Int. J. Environ. Res. Public Health 2021, 18(10), 5430; https://doi.org/10.3390/ijerph18105430 - 19 May 2021
Cited by 14 | Viewed by 4364
Abstract
Prolonged sitting combined with an awkward posture might contribute to the increased risks of developing spinal pain. Maintaining an upright sitting posture is thus often suggested, especially nowadays when people spend longer periods in the sitting posture for occupational or leisure activities. Many [...] Read more.
Prolonged sitting combined with an awkward posture might contribute to the increased risks of developing spinal pain. Maintaining an upright sitting posture is thus often suggested, especially nowadays when people spend longer periods in the sitting posture for occupational or leisure activities. Many types of assistive devices are commercially available to help computer users maintain an upright sitting posture. As the technology advances, wearable sensors that use microelectromechanical technology are designed to provide real-time biofeedback and promote adjusting posture actively. However, whether such wearable biofeedback sensors could assist adjusting sitting posture in computer users during prolonged typing remains unknown. This study aimed to investigate the effects of a wearable biofeedback sensor on maintaining an upright sitting posture. Twenty-one healthy young adults were recruited and performed a 1-h computer typing task twice, with and without using the active biofeedback device. The sagittal spinal posture during computer typing was measured using a three-dimensional motion analysis system. Using the wearable biofeedback sensor significantly decreased the neck flexion (p < 0.001), thoracic kyphotic (p = 0.033), and pelvic plane (p = 0.021) angles compared with not using the sensor. Computer users and sedentary workers may benefit from using wearable biofeedback sensors to actively maintain an upright sitting posture during prolonged deskwork. Full article
(This article belongs to the Special Issue Wearable Sensors and Robotic Devices to Prevent and Monitor Work-Related Diseases)
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13 pages, 2992 KiB  
Article
Trunk Flexion Monitoring among Warehouse Workers Using a Single Inertial Sensor and the Influence of Different Sampling Durations
by Micaela Porta, Massimiliano Pau, Pier Francesco Orrù and Maury A. Nussbaum
Int. J. Environ. Res. Public Health 2020, 17(19), 7117; https://doi.org/10.3390/ijerph17197117 - 28 Sep 2020
Cited by 8 | Viewed by 2682
Abstract
Trunk flexion represents a risk factor for the onset of low-back disorders, yet limited quantitative data exist regarding flexion exposures in actual working conditions. In this study, we evaluated the potential of using a single inertial measurement unit (IMU) to classify trunk flexion, [...] Read more.
Trunk flexion represents a risk factor for the onset of low-back disorders, yet limited quantitative data exist regarding flexion exposures in actual working conditions. In this study, we evaluated the potential of using a single inertial measurement unit (IMU) to classify trunk flexion, in terms of amplitude, frequency, and duration, and assessed the influence of alternative time durations on exposure results. Twelve warehouse workers were monitored during two hours of an actual shift while wearing a single IMU on their low back. Trunk flexion data were reduced using exposure variation analysis integrated with recommended exposure thresholds. Workers spent 5.1% of their working time with trunk flexion of 30–60° and 2.3% with flexion of 60–90°. Depending on the level of acceptable error, relatively shorter monitoring periods (up to 50 min) might be sufficient to characterize trunk flexion exposures. Future work is needed, however, to determine if these results generalize to other postural exposures and tasks. Full article
(This article belongs to the Special Issue Wearable Sensors and Robotic Devices to Prevent and Monitor Work-Related Diseases)
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Review

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22 pages, 1297 KiB  
Review
Preventing and Monitoring Work-Related Diseases in Firefighters: A Literature Review on Sensor-Based Systems and Future Perspectives in Robotic Devices
by Juri Taborri, Simone Pasinetti, Ludovica Cardinali, Fabrizio Perroni and Stefano Rossi
Int. J. Environ. Res. Public Health 2021, 18(18), 9723; https://doi.org/10.3390/ijerph18189723 - 15 Sep 2021
Cited by 4 | Viewed by 3233
Abstract
In recent years, the necessity to prevent work-related diseases has led to the use of sensor-based systems to measure important features during working activities. This topic achieved great popularity especially in hazardous and demanding activities such as those required of firefighters. Among feasible [...] Read more.
In recent years, the necessity to prevent work-related diseases has led to the use of sensor-based systems to measure important features during working activities. This topic achieved great popularity especially in hazardous and demanding activities such as those required of firefighters. Among feasible sensor systems, wearable sensors revealed their advantages in terms of possibility to conduct measures in real conditions and without influencing the movements of workers. In addition, the advent of robotics can be also exploited in order to reduce work-related disorders. The present literature review aims at providing an overview of sensor-based systems used to monitor physiological and physical parameters in firefighters during real activities, as well as to offer ideas for understanding the potentialities of exoskeletons and assistive devices. Full article
(This article belongs to the Special Issue Wearable Sensors and Robotic Devices to Prevent and Monitor Work-Related Diseases)
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