A data-driven approach to modeling physical fatigue in the workplace using wearable sensors

Applied Ergonomics

Volumn 65, Issue , 2017, Pages 515-529

  Sedighi Maman, Zahra ^a   Alamdar Yazdi, Mohammad Ali ^a   Cavuoto, Lora A ^b   Megahed, Fadel M ^c  

^a AUBURN UNIVERSITY   (United States)

^b the State University of New York   (United States)

^c MIAMI UNIVERSITY   (United States)

Author keywords

Analytics; Feature selection; Penalized regression; Physical fatigue

Indexed keywords

FEATURE EXTRACTION; LINEAR REGRESSION; MANUFACTURE; REGRESSION ANALYSIS; WEARABLE TECHNOLOGY;

ANALYTICS; DATA-DRIVEN APPROACH; IMPORTANT FEATURES; LEAST ABSOLUTE SHRINKAGE AND SELECTION OPERATORS; MANUFACTURING TASKS; MULTIPLE LINEAR REGRESSION MODELS; PENALIZED REGRESSION; PHYSICAL FATIGUES;

WEARABLE SENSORS;

ADULT; ARTICLE; BIOLOGICAL MONITORING; BIOSENSOR; CONTROLLED STUDY; EQUIPMENT DESIGN; ERGONOMICS; FATIGUE; FEMALE; HUMAN; HUMAN EXPERIMENT; JOB PERFORMANCE; MALE; MIDDLE AGED; NORMAL HUMAN; OCCUPATIONAL HEALTH; PHYSICAL FATIGUE; PORTABLE EQUIPMENT; SHIFT WORKER; TASK PERFORMANCE; WORK ENVIRONMENT; WORKLOAD; WORKPLACE; YOUNG ADULT; ADOLESCENT; DEVICES; ELECTRONIC DEVICE; EVALUATION STUDY; GENETIC PROCEDURES; MANUFACTURING INDUSTRY; MULTIVARIATE ANALYSIS; OCCUPATIONAL DISEASE; PHYSIOLOGY; STATISTICAL MODEL; WORK;

ADOLESCENT; ADULT; BIOSENSING TECHNIQUES; FATIGUE; FEMALE; HUMANS; LINEAR MODELS; MALE; MANUFACTURING INDUSTRY; MIDDLE AGED; MULTIVARIATE ANALYSIS; OCCUPATIONAL DISEASES; WEARABLE ELECTRONIC DEVICES; WORK; WORKPLACE; YOUNG ADULT;

EID: 85014121867     PISSN: 00036870     EISSN: 18729126     Source Type: Journal    
DOI: 10.1016/j.apergo.2017.02.001     Document Type: Article

References (99)

1. Achermann, P., The two-process model of sleep regulation revisited. Aviat. Space, Environ. Med. 75:Suppl. 1 (2004), A37–A43.
2. Åkerstedt, T., Folkard, S., Portin, C., Predictions from the three-process model of alertness, aviation. Space, Environ. Med. 75:3 (2004), A75–A83.
3. Amick, B.C. III, Robertson, M.M., DeRango, K., Bazzani, L., Moore, A., Rooney, T., Harrist, R., Effect of office ergonomics intervention on reducing musculoskeletal symptoms. Spine 28:24 (2003), 2706–2711.
4. Atallah, L., Lo, B.P., King, R.C., Yang, G.-Z., Sensor Placement for Activity Detection Using Wearable accelerometers., in: BSN. 2010, 24–29.
5. Aughey, R.J., Australian football player work rate: evidence of fatigue and pacing. Int. J. Sports Physiol. Perform. 5:3 (2010), 394–405.
6. Balasubramanian, V., Adalarasu, K., Regulapati, R., Comparing dynamic and stationary standing postures in an assembly task. Int. J. Industrial Ergonomics 39:5 (2009), 649–654.
7. Balkin, T.J., Horrey, W.J., Graeber, R.C., Czeisler, C.A., Dinges, D.F., The challenges and opportunities of technological approaches to fatigue management. Accid. Analysis Prev. 43:2 (2011), 565–572.
8. Bao, L., Intille, S.S., Activity Recognition from User-annotated Acceleration Data, in: International Conference on Pervasive Computing. 2004, Springer, 1–17.
9. Barker, L.M., Nussbaum, M.A., The effects of fatigue on performance in simulated nursing work. Ergonomics 54:9 (2011), 815–829.
10. Battini, D., Persona, A., Sgarbossa, F., Innovative real-time system to integrate ergonomic evaluations into warehouse design and management. Comput. Industrial Eng. 77 (2014), 1–10.
11. Belyavin, A.J., Spencer, M.B., Modeling performance and alertness: the qinetiq approach. Aviat. Space, Environ. Med. 75:3 (2004), A93–A103.
12. Björklund, M., Crenshaw, A.G., Djupsjöbacka, M., Johansson, H., Position sense acuity is diminished following repetitive low-intensity work to fatigue in a simulated occupational setting. Eur. J. Appl. Physiol. 81:5 (2000), 361–367.
13. Bonato, P., Wearable sensors and systems. IEEE Eng. Med. Biol. Mag. 29:3 (2010), 25–36.
14. Bonato, P., Ebenbichler, G.R., Roy, S.H., Lehr, S., Posch, M., Kollmitzer, J., Della Croce, U., Muscle fatigue and fatigue-related biomechanical changes during a cyclic lifting task. Spine 28:16 (2003), 1810–1820.
15. A. A. Borbély, A two process model of sleep regulation., Human Neurobiology.
16. Borbély, A.A., Achermann, P., Concepts and models of sleep regulation: an overview. J. Sleep Res. 1:2 (1992), 63–79.
17. Borg, G.A., Borg's Perceived Exertion and Pain Scales. 1998, Human Kinetics, Champaign, IL.
18. Bosch, T., De Looze, M., Van Dieen, J., Development of fatigue and discomfort in the upper trapezius muscle during light manual work. Ergonomics 50:2 (2007), 161–177.
19. Burgess-Limerick, R., Abernethy, B., Neal, R.J., Relative phase quantifies interjoint coordination. J. Biomechanics 26:1 (1993), 91–94.
20. Cat — fatigue risk management system — caterpillar, http://www.cat.com/en_US/support/operations/frms.html, [Online; accessed 1-June-2016].
21. Catapult usa — wearable technology for elite sports, http://www.catapultsports.com/, [Online; accessed 1-June-2016].
22. L. A. Cavuoto, F. M. Megahed, Understanding fatigue and the implications for worker safety, Proceedings of the ASSE Professional Development Conference & Exposition, Atlanta, GA, June 26–29 (2016).
23. Cavuoto, L.A., Nussbaum, M.A., Influences of obesity on job demands and worker capacity. Curr. Obes. Rep. 3:3 (2014), 341–347.
24. Chang, F.-L., Sun, Y.-M., Chuang, K.-H., Hsu, D.-J., Work fatigue and physiological symptoms in different occupations of high-elevation construction workers. Appl. Ergon. 40:4 (2009), 591–596.
25. Cheng, T., Migliaccio, G.C., Teizer, J., Gatti, U.C., Data fusion of real-time location sensing and physiological status monitoring for ergonomics analysis of construction workers. J. Comput. Civ. Eng. 27:3 (2012), 320–335.
26. Cook, C., Burgess-Limerick, R., The effect of forearm support on musculoskeletal discomfort during call centre work. Appl. Ergon. 35:4 (2004), 337–342.
27. Côté, J.N., Raymond, D., Mathieu, P.A., Feldman, A.G., Levin, M.F., Differences in multi-joint kinematic patterns of repetitive hammering in healthy, fatigued and shoulder-injured individuals. Clin. Biomech. 20:6 (2005), 581–590.
28. Dag, A., Topuz, K., Oztekin, A., Bulur, S., Megahed, F.M., A probabilistic data-driven framework for scoring the preoperative recipient-donor heart transplant survival. Decis. Support Syst. 86 (2016), 1–12.
29. Dawson, D., Noy, Y.I., Härmä, M., Åkerstedt, T., Belenky, G., Modelling fatigue and the use of fatigue models in work settings. Accid. Analysis Prev. 43:2 (2011), 549–564.
30. de Oliveira Sato, T., Coury, H.J.C.G., Evaluation of musculoskeletal health outcomes in the context of job rotation and multifunctional jobs. Appl. Ergon. 40:4 (2009), 707–712.
31. Dempsey, P.G., A critical review of biomechanical, epidemiological, physiological and psychophysical criteria for designing manual materials handling tasks. Ergonomics 41:1 (1998), 73–88.
32. Di Milia, L., Smolensky, M.H., Costa, G., Howarth, H.D., Ohayon, M.M., Philip, P., Demographic factors, fatigue, and driving accidents: an examination of the published literature. Accident Analysis & Prevention 43:2 (2011), 516–532.
33. Diego-Mas, J.A., Alcaide-Marzal, J., Using kinect sensor in observational methods for assessing postures at work. Appl. Ergon. 45:4 (2014), 976–985.
34. Dong, H., Ugaldey, I., El Saddik, A., Development of a fatigue-tracking system for monitoring human body movement. Instrumentation and Measurement Technology Conference (I2MTC) Proceedings, 2014 IEEE International, 2014, IEEE, 786–791.
35. Forestier, N., Nougier, V., The effects of muscular fatigue on the coordination of a multijoint movement in human. Neurosci. Lett. 252:3 (1998), 187–190.
36. Gallagher, S., Heberger, J.R., Examining the interaction of force and repetition on musculoskeletal disorder risk a systematic literature review. Hum. Factors J. Hum. Factors Ergonomics Soc. 55:1 (2013), 108–124.
37. Gander, P., Hartley, L., Powell, D., Cabon, P., Hitchcock, E., Mills, A., Popkin, S., Fatigue risk management: organizational factors at the regulatory and industry/company level. Accid. Analysis Prev. 43:2 (2011), 573–590.
38. Garg, A., Kapellusch, J.M., Applications of biomechanics for prevention of work-related musculoskeletal disorders. Ergonomics 52:1 (2009), 36–59.
39. Gatti, U.C., Schneider, S., Migliaccio, G.C., Physiological condition monitoring of construction workers. Automation Constr. 44 (2014), 227–233.
40. V. J. Gawron, J. French, D. Funke, An overview of fatigue.
41. GPS unit — performance monitoring & analysis — STATSports, http://statsports.com/technology/viper-pod/, [Online; accessed 1-June-2016].
42. Heinz, E.A., Kunze, K.S., Sulistyo, S., Junker, H., Lukowicz, P., Tröster, G., Experimental evaluation of variations in primary features used for accelerometric context recognition. European Symposium on Ambient Intelligence, 2003, Springer, 252–263.
43. Hesterberg, T., Choi, N.H., Meier, L., Fraley, C., et al. Least angle and 1 penalized regression: a review. Stat. Surv. 2 (2008), 61–93.
44. Hoerl, A.E., Kennard, R.W., Ridge regression: biased estimation for nonorthogonal problems. Technometrics 12:1 (1970), 55–67.
45. Hu, B., Ning, X., The influence of lumbar extensor muscle fatigue on lumbar–pelvic coordination during weightlifting. Ergonomics 58:8 (2015), 1424–1432.
46. Hursh, S.R., Redmond, D.P., Johnson, M.L., Thorne, D.R., Belenky, G., Balkin, T.J., Storm, W.F., Miller, J.C., Eddy, D.R., Fatigue models for applied research in warfighting. Aviat. space, Environ. Med. 75:Suppl. 1 (2004), A44–A53.
47. Huynh, T., Schiele, B., Analyzing features for activity recognition, in: proceedings of the 2005 joint conference on Smart objects and ambient intelligence: innovative context-aware services: usages and technologies. ACM, 2005, 159–163.
48. Huysmans, M.A., Hoozemans, M.J., van der Beek, A.J., de Looze, M.P., van Dieën, J.H., Position sense acuity of the upper extremity and tracking performance in subjects with non-specific neck and upper extremity pain and healthy controls. J. Rehabilitation Med. 42:9 (2010), 876–883.
49. Jewett, M.E., Kronauer, R.E., Interactive mathematical models of subjective alertness and cognitive throughput in humans. J. Biol. Rhythms 14:6 (1999), 588–597.
50. Kajimoto, O., Fatigue science for human health, springer Japan, tokyo. Ch. Dev. a Method Eval. Fatigue Its Econ. Impacts, 2008, 33–46, 10.1007/978-4-431-73464-2_3 URL http://dx.doi.org/10.1007/978-4-431-73464-2_3.
51. Kang, H.G., Mahoney, D.F., Hoenig, H., Hirth, V.A., Bonato, P., Hajjar, I., Lipsitz, L.A., In situ monitoring of health in older adults: technologies and issues. J. Am. Geriatrics Soc. 58:8 (2010), 1579–1586.
52. Kelsey, J.L., Githens, P.B., White, A.A., Holford, T.R., Walter, S.D., O'Connor, T., Ostfeld, A.M., Weil, U., Southwick, W.O., Calogero, J.A., An epidemiologic study of lifting and twisting on the job and risk for acute prolapsed lumbar intervertebral disc. J. Orthop. Res. 2:1 (1984), 61–66.
53. Kern, N., Schiele, B., Schmidt, A., Multi-sensor activity context detection for wearable computing. European Symposium on Ambient Intelligence, 2003, Springer, 220–232.
54. Kim, S., Nussbaum, M.A., Performance evaluation of a wearable inertial motion capture system for capturing physical exposures during manual material handling tasks. Ergonomics 56:2 (2013), 314–326.
55. Kimura, M., Sato, H., Ochi, M., Hosoya, S., Sadoyama, T., Electromyogram and perceived fatigue changes in the trapezius muscle during typewriting and recovery. Eur. J. Appl. Physiology 100:1 (2007), 89–96.
56. Kotsiantis, S., Kanellopoulos, D., Pintelas, P., et al. Handling imbalanced datasets: a review. GESTS Int. Trans. Comput. Sci. Eng. 30:1 (2006), 25–36.
57. Krause, A., Siewiorek, D.P., Smailagic, A., Farringdon, J., Unsupervised, Dynamic Identification of Physiological and Activity Context in Wearable computing., in: ISWC, vol. 3, 2003, 88.
58. Krueger, G.P., Sustained work, fatigue, sleep loss and performance: a review of the issues. Work & Stress 3:2 (1989), 129–141.
59. Kumar, S., Theories of musculoskeletal injury causation. Ergonomics 44:1 (2001), 17–47.
60. Lee, S.-W., Mase, K., Activity and location recognition using wearable sensors. IEEE pervasive Comput. 1:3 (2002), 24–32.
61. Lehman, K., Psihogios, J., Meulenbroek, R., Effects of sitting versus standing and scanner type on cashiers. Ergonomics 44:7 (2001), 719–738.
62. Liu, T., Inoue, Y., Shibata, K., Development of a wearable sensor system for quantitative gait analysis. Measurement 42:7 (2009), 978–988.
63. Looze, M. d., Bosch, T., Dieën, J. v., Manifestations of shoulder fatigue in prolonged activities involving low-force contractions. Ergonomics 52:4 (2009), 428–437.
64. L. Lu, R. F. Sesek, F. M. Megahed, L. N. Cavuoto, A survey of the prevalence of fatigue among workers at u.s. manufacturers, Applied ErgonomicsUnder Review.
65. Magora, A., Investigation of the relation between low back pain and occupation. iv. physical requirements: bending, rotation, reaching and sudden maximal effort. Scand. J. Rehabilitation Med., 5(4), 1973, 186.
66. Mallis, M.M., Mejdal, S., Nguyen, T.T., Dinges, D.F., Summary of the key features of seven biomathematical models of human fatigue and performance, aviation. Space, Environ. Med. 75:3 (2004), A4–A14.
67. Marras, W.S., Schoenmarxlin, R.W., Wrist motions in industry. Ergonomics 36:4 (1993), 341–351.
68. Marras, W.S., Lavender, S.A., Leurgans, S.E., Rajulu, S.L., Allread, W.G., Fathallah, F.A., Ferguson, S.A., The role of dynamic three-dimensional trunk motion in occupationally-related low back disorders: the effects of workplace factors, trunk position, and trunk motion characteristics on risk of injury. Spine 18:5 (1993), 617–628.
69. Marras, W.S., Cutlip, R.G., Burt, S.E., Waters, T.R., National occupational research agenda (nora) future directions in occupational musculoskeletal disorder health research. Appl. Ergon. 40:1 (2009), 15–22.
70. Mital, A., Foononi-Fard, H., Brown, M.L., Physical fatigue in high and very high frequency manual materials handling: perceived exertion and physiological indicators. Hum. Factors J. Hum. Factors Ergonomics Soc. 36:2 (1994), 219–231.
71. Montgomery, D.C., Introduction to Statistical Quality Control. 2014, John Wiley & Sons.
72. Murata, A., Proposal of a method to predict subjective rating on drowsiness using physiological and behavioral measures. IIE Trans. Occup. Ergonomics Hum. Factors, 2016, 1–13.
73. Neuberger, G.B., Measures of fatigue: the fatigue questionnaire, fatigue severity scale, multidimensional assessment of fatigue scale, and short form-36 vitality (energy/fatigue) subscale of the short form health survey. Arthritis Care & Res. 49:S5 (2003), S175–S183.
74. Nyan, M., Tay, F.E., Murugasu, E., A wearable system for pre-impact fall detection. J. Biomechanics 41:16 (2008), 3475–3481.
75. Ohgi, Y., Proceedings of IEEE Microcomputer-based Acceleration Sensor Device for Sports Biomechanics-stroke Evaluation by Using Swimmer's Wrist Acceleration, in: Sensors, vol. 1, 2002, IEEE, 699–704 2002.
76. Ohgi, Y., Yasumura, M., Ichikawa, H., Miyaji, C., Analysis of Stroke Technique Using Acceleration Sensor Ic in Freestyle Swimming. 2000, The Engineering of Sport, 503–512.
77. Pantelopoulos, A., Bourbakis, N.G., A survey on wearable sensor-based systems for health monitoring and prognosis, systems, man, and cybernetics, Part C: applications and reviews. IEEE Trans. 40:1 (2010), 1–12.
78. Pirttikangas, S., Fujinami, K., Nakajima, T., Feature selection and activity recognition from wearable sensors. International Symposium on Ubiquitious Computing Systems, 2006, Springer, 516–527.
79. Poh, M.-Z., Swenson, N.C., Picard, R.W., A wearable sensor for unobtrusive, long-term assessment of electrodermal activity. Biomedical Eng. IEEE Trans. 57:5 (2010), 1243–1252.
80. L. Quiros, Bnl ergonomics bulletin, Brookhaven National Laboratory, New York 4.
81. Ravi, N., Dandekar, N., Mysore, P., Littman, M.L., Activity Recognition from Accelerometer Data, in: AAAI, vol. 5, 2005, 1541–1546.
82. Ray, S.J., Teizer, J., Real-time construction worker posture analysis for ergonomics training. Advanced Eng. Informatics 26:2 (2012), 439–455.
83. Roach, G.D., Fletcher, A., DAWsON, D., A model to predict work-related fatigue based on hours of work. Aviat. Space, Environ. Med. 75:Suppl. 1 (2004), A61–A69.
84. Rodacki, A.L., Fowler, N.E., Bennett, S.J., Multi-segment coordination: fatigue effects. Med. Sci. Sports Exerc. 33:7 (2001), 1157–1167.
85. Roja, Z., Kalkis, V., Vain, A., Kalkis, H., Eglite, M., Assessment of skeletal muscle fatigue of road maintenance workers based on heart rate monitoring and myotonometry. J. Occup. Med. Toxicol. 1:1 (2006), 1–9.
86. Schall, M.C., Fethke, N.B., Chen, H., Gerr, F., A comparison of instrumentation methods to estimate thoracolumbar motion in field-based occupational studies. Appl. Ergon. 48 (2015), 224–231.
87. Schall, M.C., Fethke, N.B., Chen, H., Working postures and physical activity among registered nurses. Appl. Ergon. 54 (2016), 243–250.
88. Schall, M.C., Fethke, N.B., Chen, H., Evaluation of four sensor locations for physical activity assessment. Appl. Ergon. 53 (2016), 103–109.
89. Seay, J.F., Van Emmerik, R.E., Hamill, J., Low back pain status affects pelvis-trunk coordination and variability during walking and running. Clin. Biomech. 26:6 (2011), 572–578.
90. Sharpe, M., Archard, L., Banatvala, J., Borysiewicz, L., Clare, A., David, A., Edwards, R., Hawton, K.E., Lambert, H., Lane, R., et al. A report–chronic fatigue syndrome: guidelines for research. J. R. Soc. Med., 84(2), 1991, 118.
91. Straker, L., Stevenson, M., Twomey, L., A comparison of risk assessment of single and combination manual handling tasks: 1. maximum acceptable weight measures. Ergonomics 39:1 (1996), 128–140.
92. Tibshirani, R., Regression shrinkage and selection via the lasso. J. R. Stat. Soc. Ser. B Methodol., 1996, 267–288.
93. Vignais, N., Miezal, M., Bleser, G., Mura, K., Gorecky, D., Marin, F., Innovative system for real-time ergonomic feedback in industrial manufacturing. Appl. Ergon. 44:4 (2013), 566–574.
94. Visser, B., van Dieën, J.H., Pathophysiology of upper extremity muscle disorders. J. Electromyogr. Kinesiol. 16:1 (2006), 1–16.
95. Waters, T.R., Putz-Anderson, V., Garg, A., Fine, L.J., Revised niosh equation for the design and evaluation of manual lifting tasks. Ergonomics 36:7 (1993), 749–776.
96. Williamson, A., Lombardi, D.A., Folkard, S., Stutts, J., Courtney, T.K., Connor, J.L., The link between fatigue and safety. Accid. Analysis Prev. 43:2 (2011), 498–515.
97. Yung, M., Fatigue at the Workplace: Measurement and Temporal Development. PhD Dissertation, 2016, University of Waterloo Located at https://uwspace.uwaterloo.ca/handle/10012/10119.
98. Yung, M., Bigelow, P.L., Hastings, D.M., Wells, R.P., Detecting within-and between-day manifestations of neuromuscular fatigue at work: an exploratory study. Ergonomics 57:10 (2014), 1562–1573.
99. Zou, H., Hastie, T., Regularization and variable selection via the elastic net. J. R. Stat. Soc. Ser. B Stat. Methodol. 67:2 (2005), 301–320.