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Zhang X, Schall MC, Chen H, Gallagher S, Davis GA, Sesek R. Manufacturing worker perceptions of using wearable inertial sensors for multiple work shifts. APPLIED ERGONOMICS 2022; 98:103579. [PMID: 34507084 DOI: 10.1016/j.apergo.2021.103579] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/18/2021] [Revised: 08/30/2021] [Accepted: 08/31/2021] [Indexed: 06/13/2023]
Abstract
Wearable inertial sensors may be used to objectively quantify exposure to some physical risk factors associated with musculoskeletal disorders. However, concerns regarding their potential negative effects on user safety and satisfaction remain. This study characterized the self-reported daily discomfort, distraction, and burden associated with wearing inertial sensors on the upper arms, trunk, and dominant wrist of 31 manufacturing workers collected over 15 full work shifts. Results indicated that the workers considered the devices as generally comfortable to wear, not distracting, and not burdensome to use. Exposure to non-neutral postures (discomfort, right arm, beta = 0.02; trunk, beta = -0.01), non-cyclic tasks (distraction, beta = -0.26), and higher body mass indices (discomfort, beta = 0.05; distraction, beta = 0.02) contributed to statistically significant (p < 0.05), albeit practically small increases in undesirable ratings. For instance, for each additional percentage of time working with the right arm elevated ≥60°, self-reported discomfort ratings increased 0.02 cm on a standard 10 cm visual analog scale. Female workers reported less discomfort and distraction while wearing the sensors at work than males (discomfort, beta = -0.93; distraction, beta = -0.3). In general, the low ratings of discomfort, distraction, and burden associated with wearing the devices during work suggests that inertial sensors may be suitable for extended use among manufacturing workers.
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Affiliation(s)
- Xuanxuan Zhang
- Department of Applied Science and Technology, College of Engineering and Computer Sciences, Marshall University, Huntington, WV, USA; Department of Industrial and Systems Engineering, Samuel Ginn College of Engineering, Auburn University, Auburn, AL, USA.
| | - Mark C Schall
- Department of Industrial and Systems Engineering, Samuel Ginn College of Engineering, Auburn University, Auburn, AL, USA.
| | - Howard Chen
- Department of Mechanical Engineering, Samuel Ginn College of Engineering, Auburn University, Auburn, AL, USA.
| | - Sean Gallagher
- Department of Industrial and Systems Engineering, Samuel Ginn College of Engineering, Auburn University, Auburn, AL, USA.
| | - Gerard A Davis
- Department of Industrial and Systems Engineering, Samuel Ginn College of Engineering, Auburn University, Auburn, AL, USA.
| | - Richard Sesek
- Department of Industrial and Systems Engineering, Samuel Ginn College of Engineering, Auburn University, Auburn, AL, USA.
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Benzo R, Farag A, Whitaker K, Xiao Q, Carr L. A comparison of occupational physical activity and sedentary behavior patterns of nurses working 12-h day and night shifts. INTERNATIONAL JOURNAL OF NURSING STUDIES ADVANCES 2021. [DOI: 10.1016/j.ijnsa.2021.100028] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022] Open
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SUNG KC, CHUNG JY, FENG IJ, YANG SH, HSU CC, LIN HJ, WANG JJ, HUANG CC. Plantar fasciitis in physicians and nurses: a nationwide population-based study. INDUSTRIAL HEALTH 2020; 58:153-160. [PMID: 31548445 PMCID: PMC7118066 DOI: 10.2486/indhealth.2019-0069] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/01/2019] [Accepted: 09/13/2019] [Indexed: 06/10/2023]
Abstract
Physicians and nurses in Taiwan have heavy workload and long working hours, which may contribute to plantar fasciitis. However, this issue is unclear, and therefore, we conducted this study to delineate it. We conducted a nationwide population-based study by identifying 26,024 physicians and 127,455 nurses and an identical number of subjects for comparison (general population) via the National Health Insurance Research Database. The risk of plantar fasciitis between 2006 and 2012 was compared between physicians and general population, between nurses and general population, and between physicians and nurses. We also compared the risk of plantar fasciitis among physician subgroups. Physicians and nurses had a period prevalence of plantar fasciitis of 8.14% and 13.11% during the 7-yr period, respectively. The risk of plantar fasciitis was lower among physicians (odds ratio [OR]: 0.660; 95% confidence interval [CI]: 0.622-0.699) but higher among nurses (OR: 1.035; 95% CI: 1.011-1.059) compared with that in the general population. Nurses also had a higher risk than the physicians after adjusting for age and sex (adjusted odds ratio [AOR]: 1.541; 95% CI: 1.399-1.701). Physician subspecialties of orthopedics and physical medicine and rehabilitation showed a higher risk. Female physicians had a higher risk of plantar fasciitis than male physicians. This study showed that nurses, physician specialties of orthopedics and physical medicine and rehabilitation, and female physicians had a higher risk of plantar fasciitis. Improvement of the occupational environment and health promotion are suggested for these populations.
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Affiliation(s)
- Kuo-Chang SUNG
- Department of Emergency Medicine, Chi-Mei Medical Center,
Taiwan
| | - Jui-Yuan CHUNG
- Department of Emergency Medicine, Cathay General Hospital,
Taiwan
| | - I-Jung FENG
- Department of Medical Research, Chi-Mei Medical Center,
Taiwan
| | - Shu-Han YANG
- Department of Physical Medicine and Rehabilitation, Chi-Mei
Medical Center, Taiwan
| | - Chien-Chin HSU
- Department of Emergency Medicine, Chi-Mei Medical Center,
Taiwan
- Department of Biotechnology, Southern Taiwan University of
Science and Technology, Taiwan
| | - Hung-Jung LIN
- Department of Emergency Medicine, Chi-Mei Medical Center,
Taiwan
- Department of Emergency Medicine, Taipei Medical University,
Taiwan
| | - Jhi-Joung WANG
- Department of Medical Research, Chi-Mei Medical Center,
Taiwan
- Allied AI Biomed Center, Southern Taiwan University of
Science and Technology, Taiwan
| | - Chien-Cheng HUANG
- Department of Emergency Medicine, Chi-Mei Medical Center,
Taiwan
- Department of Senior Services, Southern Taiwan University of
Science and Technology, Taiwan
- Department of Environmental and Occupational Health, College
of Medicine, National Cheng Kung University, Taiwan
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Allan J, Sadko K, Bell C, Johnston D. How many calories do nurses burn at work? A real-time study of nurses' energy expenditure. J Res Nurs 2019; 24:488-497. [PMID: 34394566 DOI: 10.1177/1744987119837586] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
Background Nurses have high rates of overweight and obesity, and physical inactivity is one key determinant of weight gain. Aims The present study aims to quantify nurses' energy expenditure over a standard 12-hour shift to establish whether activity levels at work are too low to maintain a healthy body weight. Methods Ward-based nurses (n = 96, 90 female, mean age = 36 years, mean experience = 10 years, mean body mass index = 26.6) wore heart rate and physical activity monitors for the duration of one full working shift. Heart rate and activity data were used in combination with demographic information to estimate each nurse's energy expenditure over 12 hours. Results On average, nurses burned 2.12 kcals per minute while at work, equating to 1521 kcals/6364 kJ (SD = 403 kcals/1686 kJ) per 12-hour shift. Energy expenditure over 12 hours varied markedly between nurses (from 812 kcals/3397 kJ to 3005 kcals/12,573 kJ) but was sufficient in 72% of participants (assuming minimal resting levels of energy expenditure for the 12 hours not at work) to burn off a daily calorie intake of 2000 kcals. Conclusions Three-quarters of nurses expend more energy on working days than is required to maintain a healthy body weight if dietary intake does not exceed recommended levels.
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Affiliation(s)
- Julia Allan
- Senior Lecturer, Institute of Applied Health Sciences, University of Aberdeen, UK
| | | | - Cheryl Bell
- Institute of Applied Health Sciences, University of Aberdeen, UK
| | - Derek Johnston
- Emeritus Professor, School of Psychology, University of Aberdeen, UK
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Farrahi V, Niemelä M, Kangas M, Korpelainen R, Jämsä T. Calibration and validation of accelerometer-based activity monitors: A systematic review of machine-learning approaches. Gait Posture 2019; 68:285-299. [PMID: 30579037 DOI: 10.1016/j.gaitpost.2018.12.003] [Citation(s) in RCA: 57] [Impact Index Per Article: 11.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/30/2018] [Revised: 11/08/2018] [Accepted: 12/03/2018] [Indexed: 02/02/2023]
Abstract
BACKGROUND Objective measures using accelerometer-based activity monitors have been extensively used in physical activity (PA) and sedentary behavior (SB) research. To measure PA and SB precisely, the field is shifting towards machine learning-based (ML) approaches for calibration and validation of accelerometer-based activity monitors. Nevertheless, various parameters regarding the use and development of ML-based models, including data type (raw acceleration data versus activity counts), sampling frequency, window size, input features, ML technique, accelerometer placement, and free-living settings, affect the predictive ability of ML-based models. The effects of these parameters on ML-based models have remained elusive, and will be systematically reviewed here. The open challenges were identified and recommendations are made for future studies and directions. METHOD We conducted a systematic search of PubMed and Scopus databases to identify studies published before July 2017 that used ML-based techniques for calibration and validation of accelerometer-based activity monitors. Additional articles were manually identified from references in the identified articles. RESULTS A total of 62 studies were eligible to be included in the review, comprising 48 studies that calibrated and validated ML-based models for predicting the type and intensity of activities, and 22 studies for predicting activity energy expenditure. CONCLUSIONS It appears that various ML-based techniques together with raw acceleration data sampled at 20-30 Hz provide the opportunity of predicting the type and intensity of activities, as well as activity energy expenditure with comparable overall predictive accuracies regardless of accelerometer placement. However, the high predictive accuracy of laboratory-calibrated models is not reproducible in free-living settings, due to transitive and unseen activities together with differences in acceleration signals.
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Affiliation(s)
- Vahid Farrahi
- Research Unit of Medical Imaging, Physics and Technology, University of Oulu, Oulu, Finland.
| | - Maisa Niemelä
- Research Unit of Medical Imaging, Physics and Technology, University of Oulu, Oulu, Finland; Infotech, University of Oulu, Oulu, Finland; Medical Research Center, Oulu University Hospital and University of Oulu, Oulu, Finland
| | - Maarit Kangas
- Research Unit of Medical Imaging, Physics and Technology, University of Oulu, Oulu, Finland; Medical Research Center, Oulu University Hospital and University of Oulu, Oulu, Finland
| | - Raija Korpelainen
- Medical Research Center, Oulu University Hospital and University of Oulu, Oulu, Finland; Center for Life Course Health Research, University of Oulu, Oulu, Finland; Oulu Deaconess Institute, Department of Sports and Exercise Medicine, Finland
| | - Timo Jämsä
- Research Unit of Medical Imaging, Physics and Technology, University of Oulu, Oulu, Finland; Infotech, University of Oulu, Oulu, Finland; Medical Research Center, Oulu University Hospital and University of Oulu, Oulu, Finland; Diagnostic Radiology, Oulu University Hospital, Oulu, Finland
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Preferred Placement and Usability of a Smart Textile System vs. Inertial Measurement Units for Activity Monitoring. SENSORS 2018; 18:s18082501. [PMID: 30071635 PMCID: PMC6111998 DOI: 10.3390/s18082501] [Citation(s) in RCA: 33] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/23/2018] [Revised: 07/22/2018] [Accepted: 07/22/2018] [Indexed: 01/02/2023]
Abstract
Wearable sensors and systems have become increasingly popular in recent years. Two prominent wearable technologies for human activity monitoring are smart textile systems (STSs) and inertial measurement units (IMUs). Despite ongoing advances in both, the usability aspects of these devices require further investigation, especially to facilitate future use. In this study, 18 participants evaluate the preferred placement and usability of two STSs, along with a comparison to a commercial IMU system. These evaluations are completed after participants engaged in a range of activities (e.g., sitting, standing, walking, and running), during which they wear two representatives of smart textile systems: (1) a custom smart undershirt (SUS) and commercial smart socks; and (2) a commercial whole-body IMU system. We first analyze responses regarding the usability of the STS, and subsequently compared these results to those for the IMU system. Participants identify a short-sleeved shirt as their preferred activity monitor. In additional, the SUS in combination with the smart socks is rated superior to the IMU system in several aspects of usability. As reported herein, STSs show promise for future applications in human activity monitoring in terms of usability.
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Lee W, Seto E, Lin KY, Migliaccio GC. An evaluation of wearable sensors and their placements for analyzing construction worker's trunk posture in laboratory conditions. APPLIED ERGONOMICS 2017; 65:424-436. [PMID: 28420483 DOI: 10.1016/j.apergo.2017.03.016] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/15/2016] [Revised: 03/28/2017] [Accepted: 03/29/2017] [Indexed: 06/07/2023]
Abstract
This study investigates the effect of sensor placement on the analysis of trunk posture for construction activities using two off-the-shelf systems. Experiments were performed using a single-parameter monitoring wearable sensor (SPMWS), the ActiGraph GT9X Link, which was worn at six locations on the body, and a multi-parameter monitoring wearable sensor (MPMWS), the Zephyr BioHarness™3, which was worn at two body positions. One healthy male was recruited and conducted 10 experiment sessions to repeat measurements of trunk posture within our study. Measurements of upper-body thoracic bending posture during the lifting and lowering of raised deck materials in a laboratory setting were compared against video-captured observations of posture. The measurements from the two sensors were found to be in agreement during slow-motion symmetric bending activities with a target bending of ≤45°. However, for asymmetric bending tasks, when the SPMWS was placed on the chest, its readings were substantially different from those of the MPMWS worn on the chest or under the armpit.
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Affiliation(s)
- Wonil Lee
- Department of Construction Management, College of Built Environments, University of Washington, Seattle, WA 98195, USA; Department of Environmental and Occupational Health Sciences, School of Public Health, University of Washington, Seattle, WA 98195, USA.
| | - Edmund Seto
- Department of Environmental and Occupational Health Sciences, School of Public Health, University of Washington, Seattle, WA 98195, USA
| | - Ken-Yu Lin
- Department of Construction Management, College of Built Environments, University of Washington, Seattle, WA 98195, USA
| | - Giovanni C Migliaccio
- Department of Construction Management, College of Built Environments, University of Washington, Seattle, WA 98195, USA
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Sedighi Maman Z, Alamdar Yazdi MA, Cavuoto LA, Megahed FM. A data-driven approach to modeling physical fatigue in the workplace using wearable sensors. APPLIED ERGONOMICS 2017; 65:515-529. [PMID: 28259238 DOI: 10.1016/j.apergo.2017.02.001] [Citation(s) in RCA: 59] [Impact Index Per Article: 8.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/04/2016] [Revised: 01/28/2017] [Accepted: 02/01/2017] [Indexed: 05/14/2023]
Abstract
Wearable sensors are currently being used to manage fatigue in professional athletics, transportation and mining industries. In manufacturing, physical fatigue is a challenging ergonomic/safety "issue" since it lowers productivity and increases the incidence of accidents. Therefore, physical fatigue must be managed. There are two main goals for this study. First, we examine the use of wearable sensors to detect physical fatigue occurrence in simulated manufacturing tasks. The second goal is to estimate the physical fatigue level over time. In order to achieve these goals, sensory data were recorded for eight healthy participants. Penalized logistic and multiple linear regression models were used for physical fatigue detection and level estimation, respectively. Important features from the five sensors locations were selected using Least Absolute Shrinkage and Selection Operator (LASSO), a popular variable selection methodology. The results show that the LASSO model performed well for both physical fatigue detection and modeling. The modeling approach is not participant and/or workload regime specific and thus can be adopted for other applications.
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Affiliation(s)
- Zahra Sedighi Maman
- Department of Industrial and Systems Engineering, Auburn University, AL 36849, USA.
| | | | - Lora A Cavuoto
- Department of Industrial and Systems Engineering, University at Buffalo, NY 14260, USA.
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Bort-Roig J, Puig-Ribera A, Contreras RS, Chirveches-Pérez E, Martori JC, Gilson ND, McKenna J. Monitoring sedentary patterns in office employees: validity of an m-health tool (Walk@Work-App) for occupational health. GACETA SANITARIA 2017; 32:563-566. [PMID: 28923337 DOI: 10.1016/j.gaceta.2017.05.004] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/16/2017] [Revised: 05/09/2017] [Accepted: 05/16/2017] [Indexed: 11/28/2022]
Abstract
OBJECTIVE This study validated the Walk@Work-Application (W@W-App) for measuring occupational sitting and stepping. METHODS The W@W-App was installed on the smartphones of office-based employees (n=17; 10 women; 26±3 years). A prescribed 1-hour laboratory protocol plus two continuous hours of occupational free-living activities were performed. Intra-class correlation coefficients (ICC) compared mean differences of sitting time and step count measurements between the W@W-App and criterion measures (ActivPAL3TM and SW200Yamax Digi-Walker). RESULTS During the protocol, agreement between self-paced walking (ICC=0.85) and active working tasks step counts (ICC=0.80) was good. The smallest median difference was for sitting time (1.5seconds). During free-living conditions, sitting time (ICC=0.99) and stepping (ICC=0.92) showed excellent agreement, with a difference of 0.5minutes and 18 steps respectively. CONCLUSIONS The W@W-App provided valid measures for monitoring occupational sedentary patterns in real life conditions; a key issue for increasing awareness and changing occupational sedentariness.
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Affiliation(s)
- Judit Bort-Roig
- Research Group on Physical Activity and Sports, Centre for Health and Social Care Research, University of Vic-Central University of Catalonia, Vic (Barcelona), Spain.
| | - Anna Puig-Ribera
- Research Group on Physical Activity and Sports, Centre for Health and Social Care Research, University of Vic-Central University of Catalonia, Vic (Barcelona), Spain
| | - Ruth S Contreras
- Research Group on Data and Signal Processing, University of Vic-Central University of Catalonia, Vic (Barcelona), Spain
| | - Emilia Chirveches-Pérez
- Research Group on Methodology, Methods, Models and Health and Social Outcomes (M3O), Universitat de Vic-Central University of Catalonia, Vic (Barcelona), Spain; Clinical Epidemiology Unit, Hospital Consortium Vic, Vic (Barcelona), Spain
| | - Joan C Martori
- Data Analysis and Modelling Research Group, University of Vic-Central University of Catalonia, Vic (Barcelona), Spain
| | - Nicholas D Gilson
- School of Human Movement and Nutrition Science, The University of Queensland, Brisbane, Australia
| | - Jim McKenna
- School of Sport, Leeds Beckett University, Leeds, United Kingdom
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Chappel SE, Verswijveren SJ, Aisbett B, Considine J, Ridgers ND. Nurses’ occupational physical activity levels: A systematic review. Int J Nurs Stud 2017; 73:52-62. [DOI: 10.1016/j.ijnurstu.2017.05.006] [Citation(s) in RCA: 33] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2017] [Revised: 05/08/2017] [Accepted: 05/08/2017] [Indexed: 10/19/2022]
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Gallagher S, Schall MC. Musculoskeletal disorders as a fatigue failure process: evidence, implications and research needs. ERGONOMICS 2017; 60:255-269. [PMID: 27376409 DOI: 10.1080/00140139.2016.1208848] [Citation(s) in RCA: 72] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/06/2023]
Abstract
Mounting evidence suggests that musculoskeletal disorders (MSDs) may be the result of a fatigue failure process in musculoskeletal tissues. Evaluations of MSD risk in epidemiological studies and current MSD risk assessment tools, however, have not yet incorporated important principles of fatigue failure analysis in their appraisals of MSD risk. This article examines the evidence suggesting that fatigue failure may play an important role in the aetiology of MSDs, assesses important implications with respect to MSD risk assessment and discusses research needs that may be required to advance the scientific community's ability to more effectively prevent the development of MSDs. Practitioner Summary: Evidence suggests that musculoskeletal disorders (MSDs) may result from a fatigue failure process. This article proposes a unifying framework that aims to explain why exposure to physical risk factors contributes to the development of work-related MSDs. Implications of that framework are discussed.
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Affiliation(s)
- Sean Gallagher
- a Industrial and Systems Engineering , Auburn University , Auburn , AL , USA
| | - Mark C Schall
- a Industrial and Systems Engineering , Auburn University , Auburn , AL , USA
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12
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Trunk Motion System (TMS) Using Printed Body Worn Sensor (BWS) via Data Fusion Approach. SENSORS 2017; 17:s17010112. [PMID: 28075342 PMCID: PMC5298685 DOI: 10.3390/s17010112] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/05/2016] [Revised: 12/19/2016] [Accepted: 12/20/2016] [Indexed: 11/17/2022]
Abstract
Human movement analysis is an important part of biomechanics and rehabilitation, for which many measurement systems are introduced. Among these, wearable devices have substantial biomedical applications, primarily since they can be implemented both in indoor and outdoor applications. In this study, a Trunk Motion System (TMS) using printed Body-Worn Sensors (BWS) is designed and developed. TMS can measure three-dimensional (3D) trunk motions, is lightweight, and is a portable and non-invasive system. After the recognition of sensor locations, twelve BWSs were printed on stretchable clothing with the purpose of measuring the 3D trunk movements. To integrate BWSs data, a neural network data fusion algorithm was used. The outcome of this algorithm along with the actual 3D anatomical movements (obtained by Qualisys system) were used to calibrate the TMS. Three healthy participants with different physical characteristics participated in the calibration tests. Seven different tasks (each repeated three times) were performed, involving five planar, and two multiplanar movements. Results showed that the accuracy of TMS system was less than 1.0°, 0.8°, 0.6°, 0.8°, 0.9°, and 1.3° for flexion/extension, left/right lateral bending, left/right axial rotation, and multi-planar motions, respectively. In addition, the accuracy of TMS for the identified movement was less than 2.7°. TMS, developed to monitor and measure the trunk orientations, can have diverse applications in clinical, biomechanical, and ergonomic studies to prevent musculoskeletal injuries, and to determine the impact of interventions.
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Bakola H, Zyga S, Stergioulas A, Kipreos G, Panoutsopoulos G. Musculoskeletal Problems Among Greek Perioperative Nurses in Regional Hospitals in Southern Peloponnese : Musculoskeletal Problems in Perioperative Nurses. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2017; 989:21-37. [PMID: 28971414 DOI: 10.1007/978-3-319-57348-9_3] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/28/2023]
Abstract
The surgery unit is a particularly labor-intensive environment in the hospital. Studies reflect the correlation of labor risk factors for musculoskeletal injuries among nurses but few have investigated the relationship to perioperative nurses. The purpose of this study is the identification and definition of ergonomic risk factors in the operating room and their connection with musculoskeletal disorders in perioperative nurses in regional hospitals in Greece. Forty four Greek perioperative nurses working in regional hospitals in southern Peloponnese participated. Anonymous self-administered questionnaire was used to collect the data, which consisted of three parts (investigating musculoskeletal symptoms, description of work, psychometric evaluation). The analysis was done with the statistical program SPSS.19. Symptoms of musculoskeletal problems emerged. Specifically, 54.4% in the lumbar, 47.7% in the neck, 45.5% in the shoulder, followed by smaller percentages of the hip, knee, elbow and ankle. 6.8% of participants indicated no musculoskeletal symptoms in the last year while 74.9% of those who had symptoms presented them in two or more areas. Activities rated as a major problem among others were the manual handling, tools with weight and vibration etc. 100% of respondents agreed that the work in the surgery unit is demanding and has anxiety. The lack of support from the government (81.8%), combined with the low perioperative nurses (6.8%) having the opportunity to participate in administrative decisions concerning them were related to problems in the organization and management of work. Apart from engineers target factors, a main aim should be the organization of work within the framework of a national policy based on European directives on the protection and promotion of the health and safety of workers.
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Affiliation(s)
- Helen Bakola
- Department of Nursing, Faculty of Human Movement and Quality of Life Sciences, University of Peloponnese, Sparta, Greece.
| | - Sofia Zyga
- Department of Nursing, Faculty of Human Movement and Quality of Life Sciences, University of Peloponnese, Sparta, Greece
| | - Apostolos Stergioulas
- Department of Sports, Organization and Management, University of Peloponnese, Tripoli, Greece
| | - George Kipreos
- Department of Sports, Organization and Management, University of Peloponnese, Tripoli, Greece
| | - George Panoutsopoulos
- Department of Nursing, Faculty of Human Movement and Quality of Life Sciences, University of Peloponnese, Sparta, Greece
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Schall MC, Fethke NB, Chen H. Working postures and physical activity among registered nurses. APPLIED ERGONOMICS 2016; 54:243-50. [PMID: 26851483 DOI: 10.1016/j.apergo.2016.01.008] [Citation(s) in RCA: 24] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/14/2015] [Revised: 12/15/2015] [Accepted: 01/11/2016] [Indexed: 05/27/2023]
Abstract
Nurses report a high prevalence of musculoskeletal discomfort, particularly of the low back and neck/shoulder. This study characterized the full-shift upper arm and trunk postures and movement velocities of registered nurses using inertial measurement units (IMUs). Intensity of occupational physical activity (PA) was also ascertained using a waist-worn PA monitor and using the raw acceleration data from each IMU. Results indicated that nurses spent a relatively small proportion of their work time with the arms or trunk in extreme postures, but had few opportunities for rest and recovery in comparison to several other occupational groups. Comparisons between nurses in different PA groups suggested that using a combination of accelerometers secured to several body locations may provide more representative estimates of physical demands than a single, waist-worn PA monitor. The findings indicate a need for continued field-based research with larger sample sizes to facilitate the development of maximally effective intervention strategies.
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Affiliation(s)
- Mark C Schall
- Department of Industrial and Systems Engineering, Auburn University, 3301 Shelby Center for Engineering Technology, Auburn, AL, USA.
| | - Nathan B Fethke
- Department of Occupational and Environmental Health, University of Iowa, Iowa City, IA, USA
| | - Howard Chen
- Department of Occupational and Environmental Health, University of Iowa, Iowa City, IA, USA
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