Skip to main content
SpringerLink
Log in

A Systematic Review on Evaluation Strategies for Field Assessment of Upper-Body Industrial Exoskeletons: Current Practices and Future Trends

  • 50th Anniversary Reviews
  • Published:
Annals of Biomedical Engineering Aims and scope Submit manuscript

Abstract

With rising manual work demands, physical assistance at the workplace is crucial, wherein the use of industrial exoskeletons (i-EXOs) could be advantageous. However, outcomes of numerous laboratory studies may not be directly translated to field environments. To explore this discrepancy, we conducted a systematic review including 31 studies to identify and compare the approaches, techniques, and outcomes within field assessments of shoulder and back support i-EXOs. Findings revealed that the subjective approaches [i.e., discomfort (23), usability (22), acceptance/perspectives (21), risk of injury (8), posture (3), perceived workload (2)] were reported more common (27) compared to objective (15) approaches [muscular demand (14), kinematics (8), metabolic costs (5)]. High variability was also observed in the experimental methodologies, including control over activity, task physics/duration, sample size, and reported metrics/measures. In the current study, the detailed approaches, their subject-related factors, and observed trends have been discussed. In sum, a new guideline, including tools/technologies has been proposed that could be utilized for field evaluation of i-EXOs. Lastly, we discussed some of the common technical challenges experimenters face in evaluating i-EXOs in field environments. Efforts presented in this study seek to improve the generalizability in testing and implementing i-EXOs.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Figure 1
Figure 2
Figure 3
Figure 4
Figure 5
Figure 6

Similar content being viewed by others

References

  1. Abdoli-Eramaki M, Agababova M, Janabi J, Pasko E, Damecour C (2019) Evaluation and comparison of lift styles for an ideal lift among individuals with different levels of training. Appl. Ergon. 78:120–126

    Article  PubMed  Google Scholar 

  2. Alberto R, Draicchio F, Varrecchia T, Silvetti A, Iavicoli S (2018) Wearable monitoring devices for biomechanical risk assessment at work: current status and future challenges—a systematic review. Int. J. Environ. Res. Public Health 15:1–26

    Google Scholar 

  3. Alemi MM, Geissinger J, Simon AA, Chang SE, Asbeck AT (2019) A passive exoskeleton reduces peak and mean EMG during symmetric and asymmetric lifting. J. Electromyogr. Kinesiol. 47:25–34

    Article  PubMed  Google Scholar 

  4. Alemi MM, Madinei S, Kim S, Srinivasan D, Nussbaum MA (2020) Effects of two passive back-support exoskeletons on muscle activity, energy expenditure, and subjective assessments during repetitive lifting. Hum. Factors 62:458–474

    Article  PubMed  Google Scholar 

  5. Amandels, S., H. O. Het Eyndt, L. Daenen, and V. Hermans. Introduction and testing of a passive exoskeleton in an industrial working environment. In: Proceedings of the 20th Congress of the International Ergonomics Association. Springer, 2019, pp. 387–392.

  6. Baltrusch SJ, van Dieën JH, Bruijn SM, Koopman AS, van Bennekom CAM, Houdijk H (2019) The effect of a passive trunk exoskeleton on metabolic costs during lifting and walking. Ergonomics 62:903–916

    Article  CAS  PubMed  Google Scholar 

  7. Baltrusch SJ, Houdijk H, van Dieën JH, de Kruif JTCM (2021) Passive trunk exoskeleton acceptability and effects on self-efficacy in employees with low-back pain: a mixed method approach. J. Occup. Rehabil. 31:129–141

    Article  CAS  PubMed  Google Scholar 

  8. Bani Hani D, Huangfu R, Sesek R, Schall MC, Davis GA, Gallagher S (2021) Development and validation of a cumulative exposure shoulder risk assessment tool based on fatigue failure theory. Ergonomics 64:39–54

    Article  PubMed  Google Scholar 

  9. Bochen, J. Influence of Prolonged Sitting and Psychosocial Stress on Lumbar Spine Kinematics, Kinetics, Discomfort, and Muscle Fatigue, Virginia Tech, 2013.

  10. Bosch T, van Eck J, Knitel K, de Looze M (2016) The effects of a passive exoskeleton on muscle activity, discomfort and endurance time in forward bending work. Appl. Ergon. 54:212–217

    Article  PubMed  Google Scholar 

  11. Budihardjo, I. Studies of compressive forces on L5/S1 during dynamic manual lifting. Thesis, Iowa State University, 2002.

  12. Bureau of Labor Statistics. Projections Overview and Highlights, 2020–30. Bureau of Labor Statistics, 2021.

  13. Bureau of Labor Statistics. Survey of Occupational Injuries and Illnesses Data. Bureau of Labor Statistics, 2021.

  14. Butler T (2016) Exoskeleton technology. Ergonomics 61:32–36

    Google Scholar 

  15. Butler T, Gillette J (2019) Exoskeletons: used as PPE for injury prevention. Prof. Saf. 64(3):33

    Google Scholar 

  16. Chang SE, Pesek T, Pote TR, Hull J, Geissinger J, Simon AA, Alemi MM, Asbeck AT (2020) Design and preliminary evaluation of a flexible exoskeleton to assist with lifting. Wearable Technol. 1

    Article  Google Scholar 

  17. Claramunt Molet, M., B. Domingo Mateu, J. Danús Jaume, A. Ugartemendia Etxarri, I. de la Maza, V. Enriquez Carrera, O. Muñoz Fernández, S. Domingo, F. Miralles, J. M. Font Llagunes, and S. Idelsohn Zielonka. Biomechanical Evaluation of Upper Limb Exoskeletons in Automotive Assembly Using EMG. IX Reunión del Capítulo Español de la Sociedad Europea de Biomecánica, 2019, pp. 25–26.

  18. Crea S, Beckerle P, De Looze M, De Pauw K, Grazi L, Kermavnar T, Masood J, O’Sullivan LW, Pacifico I, Rodriguez-Guerrero C, Vitiello N, Ristić-Durrant D, Veneman J (2021) Occupational exoskeletons: a roadmap toward large-scale adoption. Methodology and challenges of bringing exoskeletons to workplaces. Wearable Technol. 2:e11–e22

    Article  Google Scholar 

  19. Dahmen, C., and M. Hefferle. Application of ergonomic assessment methods on an exoskeleton centered workplace. In: Proceedings of the XXXth Annual Occupational Ergonomics and Safety Conference, 2018, pp. 17–25.

  20. De Bock S, Ghillebert J, Govaerts R, Elprama SA, Marusic U, Serrien B, Jacobs A, Geeroms J, Meeusen R, De Pauw K (2021) Passive shoulder exoskeletons: more effective in the lab than in the field? IEEE Trans. Neural Syst. Rehabil. Eng. 29:173–183

    Article  PubMed  Google Scholar 

  21. De Bock S, Ghillebert J, Govaerts R, Tassignon B, Rodriguez-Guerrero C, Crea S, Veneman J, Geeroms J, Meeusen R, De Pauw K (2022) Benchmarking occupational exoskeletons: an evidence mapping systematic review. Appl. Ergon. 98

    Article  PubMed  Google Scholar 

  22. De Luca CJ (1984) Myoelectrical manifestations of localized muscular fatigue in humans. Crit. Rev. Biomed. Eng. 11:251–279

    PubMed  Google Scholar 

  23. De Vries A, Krause F, de Looze MP (2021) The effectivity of a passive arm support exoskeleton in reducing muscle activation and perceived exertion during plastering activities. Ergonomics 64:712–721

    Article  PubMed  Google Scholar 

  24. De Vries A, De Looze M (2019) The effect of arm support exoskeletons in realistic work activities: a review study. J. Ergon. 9:1–9

    Google Scholar 

  25. Dewi NS, Komatsuzaki M (2018) On-body personal assist suit for commercial farming: effect on heart rate, EMG, trunk movements, and user acceptance during digging. Int. J. Ind. Ergon. 68:290–296

    Article  Google Scholar 

  26. Faber GS, Chang CC, Kingma I, Dennerlein JT, van Dieën JH (2016) Estimating 3D L5/S1 moments and ground reaction forces during trunk bending using a full-body ambulatory inertial motion capture system. J. Biomech. 49:904–912

    Article  CAS  PubMed  Google Scholar 

  27. Ferreira, G., J. Gaspar, C. Fujão, and I. L. Nunes. Piloting the use of an upper limb passive exoskeleton in automotive industry: assessing user acceptance and intention of use. In: Advances in Intelligent Systems and Computing, AISC, vol 1207, pp. 342–349, 2020.

  28. Flor, R., J. Gaspar, C. Fujão, and I. L. Nunes. How workers perceive LAEVO exoskeleton use in non-cyclic tasks. In: AHFE 2021: Advances in Human Factors and System Interaction. Springer, 2021, pp. 147–154.

  29. Gillette JC, Stephenson ML (2019) Electromyographic assessment of a shoulder support exoskeleton during on-site job tasks. IISE Trans. Occup. Ergon. Hum. Factors 7:302–310

    Article  Google Scholar 

  30. González-Izal M, Malanda A, Gorostiaga E, Izquierdo M (2012) Electromyographic models to assess muscle fatigue. J. Electromyogr. Kinesiol. 22:501–512

    Article  PubMed  Google Scholar 

  31. Graham RB, Agnew MJ, Stevenson JM (2009) Effectiveness of an on-body lifting aid at reducing low back physical demands during an automotive assembly task: assessment of EMG response and user acceptability. Appl. Ergon. 40:936–942

    Article  PubMed  Google Scholar 

  32. Gull MA, Bai S (2020) A review on design of upper limb exoskeletons. Robotics 9(1):1–35

    Article  Google Scholar 

  33. Hefferle, M., M. Snell, and K. Kluth. Influence of two industrial overhead exoskeletons on perceived strain—a field study in the automotive industry. In: International Conference on Applied Human Factors and Ergonomics, AHFE 2020: Advances in Human Factors in Robots, Drones and Unmanned Systems. Springer, 2021, pp. 94–100.

  34. Hellig T, Johnen L, Mertens A, Nitsch V, Brandl C (2020) Prediction model of the effect of postural interactions on muscular activity and perceived exertion. Ergonomics 63:593–606

    Article  PubMed  Google Scholar 

  35. Hensel R, Keil M (2019) Subjective evaluation of a passive industrial exoskeleton for lower-back support: a field study in the automotive sector. IISE Trans. Occup. Ergon. Hum. Factors 7:213–221

    Article  Google Scholar 

  36. Herzog W (1988) The relation between the resultant moments at a joint and the moments measured by an isokinetic dynamometer. J Biomech. https://doi.org/10.1016/0021-9290(88)90185-6

    Article  PubMed  Google Scholar 

  37. Higgins, J. P. T., J. Savović, M. J. Page, R. G. Elbers, and J. A. C. Sterne. Assessing risk of bias in a randomized trial. In: Cochrane Handbook for Systematic Reviews of Interventions. Chichester: Wiley, 2019, pp. 205–228.

  38. Hignett S, McAtamney L (2000) Rapid entire body assessment (REBA). Appl. Ergon. 31:201–205

    Article  CAS  PubMed  Google Scholar 

  39. Hoffmann N, Prokop G, Weidner R (2021) Methodologies for evaluating exoskeletons with industrial applications. Ergonomics 65(2):1–38

    Google Scholar 

  40. Iranzo S, Piedrabuena A, Iordanov D, Martinez-Iranzo U, Belda-Lois JM (2020) Ergonomics assessment of passive upper-limb exoskeletons in an automotive assembly plant. Appl. Ergon. 87

    Article  PubMed  Google Scholar 

  41. Ivaldi, S., P. Maurice, W. Gomes, J. Theurel, L. Wioland, J. J. Atain-Kouadio, L. Claudon, H. Hani, A. Kimmoun, J. M. Sellal, B. Levy, J. Paysant, S. Malikov, B. Chenuel, and N. Settembre. Using exoskeletons to assist medical staff during prone positioning of mechanically ventilated COVID-19 patients: a pilot study. In: International Conference on Applied Human Factors and Ergonomics, AHFE 2021: Advances in Human Factors and Ergonomics in Healthcare and Medical Devices. Lecture Notes in Network Systems, vol. 263, pp. 88–100, 2021.

  42. Ivaldi, S., P. Maurice, W. Gomes, J. Theurel, L. Wioland, B. Chenuel, and N. Settembre. Using exoskeletons to assist medical staff during prone positioning of mechanically ventilated COVID-19 patients: a pilot study. In: Applied Human Factors and Ergonomics International Conference, 2021.

  43. Jallon R, Imbeau D, De Marcellis-Warin N (2011) Development of an indirect-cost calculation model suitable for workplace use. J. Saf. Res. 42:149–164

    Article  Google Scholar 

  44. Jia B, Kim S, Nussbaum MA (2011) An EMG-based model to estimate lumbar muscle forces and spinal loads during complex, high-effort tasks: development and application to residential construction using prefabricated walls. Int. J. Ind. Ergon. 41:437–446

    Article  Google Scholar 

  45. Kim S, Nussbaum MA, Mokhlespour Esfahani MI, Alemi MM, Alabdulkarim S, Rashedi E (2018) Assessing the influence of a passive, upper extremity exoskeletal vest for tasks requiring arm elevation: Part I—“Expected” effects on discomfort, shoulder muscle activity, and work task performance. Appl. Ergon. 70:315–322

    Article  PubMed  Google Scholar 

  46. Kim S, Nussbaum MA, Mokhlespour Esfahani MI, Alemi MM, Jia B, Rashedi E (2018) Assessing the influence of a passive, upper extremity exoskeletal vest for tasks requiring arm elevation: Part II—“Unexpected” effects on shoulder motion, balance, and spine loading. Appl. Ergon. 70:323–330

    Article  PubMed  Google Scholar 

  47. Kim S, Nussbaum MA, Smets M (2021) Usability, user acceptance, and health outcomes of arm-support exoskeleton use in automotive assembly. J. Occup. Environ. Med. 64(3):1–10

    Google Scholar 

  48. Kim S, Nussbaum MA, Smets M, Ranganathan S (2021) Effects of an arm-support exoskeleton on perceived work intensity and musculoskeletal discomfort: an 18-month field study in automotive assembly. Am. J. Ind. Med. 64(11):905–914

    Article  PubMed  Google Scholar 

  49. Kingma I, Baten CTM, Dolan P, Toussaint HM, Van Dieën JH, De Looze MP, Adams MA (2001) Lumbar loading during lifting: a comparative study of three measurement techniques. J. Electromyogr. Kinesiol. 11:337–345

    Article  CAS  PubMed  Google Scholar 

  50. Koenig, J. A quantitative assessment of the effects of passive upper extremity exoskeletons on sonographer’s muscle activity and posture while performing transthoracic echocardiograms. Thesis, Iowa State University, 2020.

  51. Kuber PM, Rashedi E (2020) Product ergonomics in industrial exoskeletons: potential enhancements for workforce safety and efficiency. Theor. Issues Ergon. Sci. 22:729–752

    Article  Google Scholar 

  52. Kuber, P. M., and E. Rashedi. Towards reducing risk of injury in nursing: design and analysis of a new passive exoskeleton for torso twist assist. In: Proceedings of the International Symposium on Human Factors and Ergonomics in Health Care, 2021.

  53. Lanotte, F., L. Grazi, B. Chen, N. Vitiello, and S. Crea. A low-back exoskeleton can reduce the erector spinae muscles activity during freestyle symmetrical load lifting tasks. In: Proceedings of the IEEE RAS EMBS International Conference on Biomedical Robotics and Biomechatronics 2018, August, pp. 701–706, 2018.

  54. Larsen FG, Svenningsen FP, Andersen MS, de Zee M, Skals S (2019) Estimation of spinal loading during manual materials handling using inertial motion capture. Ann. Biomed. Eng. 48:805–821

    Article  PubMed  Google Scholar 

  55. Le P, Marras WS (2016) Evaluating the low back biomechanics of three different office workstations: seated, standing, and perching. Appl. Ergon. 56:170–178

    Article  PubMed  Google Scholar 

  56. Liberty Mutual. Liberty Mutual Workplace Safety Index—Risk Control from Liberty Mutual Insurance. Liberty Mutual, 2021, pp. 1–2.

  57. Liu Y, Li X, Lai J, Zhu A, Zhang X, Zheng Z, Zhu H, Shi Y, Wang L, Chen Z (2021) The effects of a passive exoskeleton on human thermal responses in temperate and cold environments. Int. J. Environ. Res. Public Health 18(8):3889

    Article  PubMed  PubMed Central  Google Scholar 

  58. Lorenzini, M., W. Kim, E. De Momi, and A. Ajoudani. A new overloading fatigue model for ergonomic risk assessment with application to human–robot collaboration. In: Proceedings—IEEE International Conference on Robotics and Automation 2019, May, pp. 1962–1968, 2019.

  59. Luger T, Bär M, Seibt R, Rimmele P, Rieger MA, Steinhilber B (2021) A passive back exoskeleton supporting symmetric and asymmetric lifting in stoop and squat posture reduces trunk and hip extensor muscle activity and adjusts body posture—a laboratory study. Appl. Ergon. 97

    Article  PubMed  Google Scholar 

  60. Luger T, Cobb TJ, Seibt R, Rieger MA, Steinhilber B (2019) Subjective evaluation of a passive lower-limb industrial exoskeleton used during simulated assembly. IISE Trans. Occup. Ergon. Hum. Factors 7:175–184

    Article  Google Scholar 

  61. Madinei S, Alemi MM, Kim S, Srinivasan D, Nussbaum MA (2020) Biomechanical evaluation of passive back-support exoskeletons in a precision manual assembly task: “Expected” effects on trunk muscle activity, perceived exertion, and task performance. Hum. Factors 62:441–457

    Article  PubMed  Google Scholar 

  62. Marginson V, Eston R (2001) The relationship between torque and joint angle during knee extension in boys and men. J. Sport Sci. 19:875–880

    Article  CAS  Google Scholar 

  63. Matijevich ES, Volgyesi P, Zelik KE (2021) A promising wearable solution for the practical and accurate monitoring of low back loading in manual material handling. Sensors (Switz.) 21:1–25

    Google Scholar 

  64. Maurice P, Čamernik J, Gorjan D, Schirrmeister B, Bornmann J, Tagliapietra L, Latella C, Pucci D, Fritzsche L, Ivaldi S, Babič J (2019) Evaluation of PAEXO, a novel passive exoskeleton for overhead work. Comput. Methods Biomech. Biomed. Eng. 22:S448–S450

    Article  Google Scholar 

  65. McFarland T, Fischer S (2019) Considerations for industrial use: a systematic review of the impact of active and passive upper limb exoskeletons on physical exposures. IISE Trans Occup Ergon Hum Factors. https://doi.org/10.1080/24725838.2019.1684399

    Article  Google Scholar 

  66. Motmans, R., T. Debaets, and S. Chrispeels. Effect of a passive exoskeleton on muscle activity and posture during order picking. In: Congress of the International Ergonomics Association, IEA 2018: Proceedings of the 20th Congress of the International Ergonomics Association (IEA 2018). Springer, 2019, pp. 338–346.

  67. Moyon A, Poirson E, Petiot JF (2018) Experimental study of the physical impact of a passive exoskeleton on manual sanding operations. Procedia CIRP 70:284–289

    Article  Google Scholar 

  68. Nussbaum MA, Lowe BD, de Looze M, Harris-Adamson C, Smets M (2019) An introduction to the special issue on occupational exoskeletons. IISE Trans. Occup. Ergon. Hum. Factors 7:153–162

    Article  Google Scholar 

  69. Omoniyi A, Trask C, Milosavljevic S, Thamsuwan O (2020) Farmers’ perceptions of exoskeleton use on farms: finding the right tool for the work(er). Int. J. Ind. Ergon. 80

    Article  Google Scholar 

  70. Page MJ, McKenzie JE, Bossuyt PM, Boutron I, Hoffmann TC, Mulrow CD, Shamseer L, Tetzlaff JM, Akl EA, Brennan SE, Chou R, Glanville J, Grimshaw JM, Hróbjartsson A, Lalu MM, Li T, Loder EW, Mayo-Wilson E, McDonald S, McGuinness LA, Stewart LA, Thomas J, Tricco AC, Welch VA, Whiting P, Moher D, The PRISMA (2020) statement: an updated guideline for reporting systematic reviews. BMJ. https://doi.org/10.1136/bmj.n71

    Article  PubMed  Google Scholar 

  71. Perotto AO (2011) Anatomical Guide for the Electromyographer. Charles C Thomas Publisher, Springfield

    Google Scholar 

  72. Pesenti M, Antonietti A, Gandolla M, Pedrocchi A (2021) Towards a functional performance validation standard for industrial low-back exoskeletons: state of the art review. Sensors (Switz.) 21:1–23

    Google Scholar 

  73. Picchiotti MT, Weston EB, Knapik GG, Dufour JS, Marras WS (2019) Impact of two postural assist exoskeletons on biomechanical loading of the lumbar spine. Appl. Ergon. 75:1–7

    Article  PubMed  Google Scholar 

  74. Pillai MV, Van Engelhoven L, Kazerooni H (2020) Evaluation of a lower leg support exoskeleton on floor and below hip height panel work. Hum. Factors 62:489–500

    Article  PubMed  Google Scholar 

  75. Poliero T, Sposito M, Toxiri S, Di Natali C, Iurato M, Sanguineti V, Caldwell DG, Ortiz J (2021) Versatile and non-versatile occupational back-support exoskeletons: a comparison in laboratory and field studies. Wearable Technol. 2:1–21

    Article  Google Scholar 

  76. Price C, Parker D, Nester C (2016) Validity and repeatability of three in-shoe pressure measurement systems. Gait Posture 46:69–74

    Article  PubMed  Google Scholar 

  77. Rampichini S, Vieira TM, Castiglioni P, Merati G (2020) Complexity analysis of surface electromyography for assessing the myoelectric manifestation of muscle fatigue: a review. Entropy 22(5):529

    Article  PubMed Central  Google Scholar 

  78. Rashedi E, Kim S, Nussbaum MA, Agnew MJ (2014) Ergonomic evaluation of a wearable assistive device for overhead work. Ergonomics 57:1864–1874

    Article  PubMed  Google Scholar 

  79. Renner KE, Blaise Williams DS, Queen RM (2019) The reliability and validity of the Loadsol® under various walking and running conditions. Sensors (Switz.) 19:1–14

    Google Scholar 

  80. Riddle M, MacDermid-Watts K, Holland S, MacDermid JC, Lalone E, Ferreira L (2018) Wearable strain gauge-based technology measures manual tactile forces during the activities of daily living. J Rehabil Assist Technol Eng. https://doi.org/10.1177/2055668318793587

    Article  PubMed  PubMed Central  Google Scholar 

  81. Scherpereel KL, Bolus NB, Jeong HK, Inan OT, Young AJ (2021) Estimating knee joint load using acoustic emissions during ambulation. Ann. Biomed. Eng. 49:1000–1011

    Article  PubMed  Google Scholar 

  82. Schmalz, T., J. Bornmann, B. Schirrmeister, J. Schändlinger, and M. Schuler, T. Principle Study About the Effect of an Industrial Exoskeleton on Overhead Work Exoskeleton. Dortmund: Verlag Orthopädie-technik, 2019.

  83. Schwerha DJ, McNamara N, Kim S, Nussbaum MA (2022) Exploratory field testing of passive exoskeletons in several manufacturing environments: perceived usability and user acceptance. IISE Trans Occup Ergon Hum Factors. https://doi.org/10.1080/24725838.2022.2059594

    Article  PubMed  Google Scholar 

  84. Schwerha DJ, McNamara N, Nussbaum MA, Kim S (2021) Adoption potential of occupational exoskeletons in diverse enterprises engaged in manufacturing tasks. Int J Ind Ergon. https://doi.org/10.1016/j.ergon.2021.103103

    Article  Google Scholar 

  85. Sedighi Maman Z, Chen YJ, Baghdadi A, Lombardo S, Cavuoto LA, Megahed FM (2020) A data analytic framework for physical fatigue management using wearable sensors. Expert Syst Appl. https://doi.org/10.1016/j.eswa.2020.113405

    Article  Google Scholar 

  86. Shinde GV, Jadhav VS (2012) Ergonomic analysis of an assembly workstation to identify time consuming and fatigue causing factors using application of motion study. Int. J. Eng. Technol. 4:220–227

    Google Scholar 

  87. Siedl SM, Mara M (2021) Exoskeleton acceptance and its relationship to self-efficacy enhancement, perceived usefulness, and physical relief: a field study among logistics workers. Wearable Technol. 2:e10–e15

    Article  Google Scholar 

  88. Smets M (2019) A field evaluation of arm-support exoskeletons for overhead work applications in automotive assembly. IISE Trans. Occup. Ergon. Hum. Factors 5838:1–7

    Google Scholar 

  89. Thakur K, Kuber PM, Abdollahi M, Rashedi E (2022) Why multi-tier surgical instrument table matters? An ergonomic analysis from mento-physical demand perspectives. Appl Ergon. https://doi.org/10.1016/j.apergo.2022.103828

    Article  PubMed  Google Scholar 

  90. Thamsuwan O, Milosavljevic S, Srinivasan D, Trask C (2020) Potential exoskeleton uses for reducing low back muscular activity during farm tasks. Am. J. Ind. Med. 63(11):1017–1028

    Article  PubMed  Google Scholar 

  91. Toxiri S, Näf MB, Lazzaroni M, Fernández J, Sposito M, Poliero T, Monica L, Anastasi S, Caldwell DG, Ortiz J (2019) Back-support exoskeletons for occupational use: an overview of technological advances and trends. IISE Trans. Occup. Ergon. Hum. Factors 7:237–249

    Article  Google Scholar 

  92. U.S. Bureau of Labor Statistics. Injuries, Illnesses, and Fatalities. U.S. Bureau of Labor Statistics, 2020.

  93. Vøllestad NK (1997) Measurement of human muscle fatigue. J. Neurosci. Methods 74:219–227

    Article  PubMed  Google Scholar 

  94. Wang Z, Wu X, Zhang Y, Chen C, Liu S, Liu Y, Peng A, Ma Y (2021) A semi-active exoskeleton based on EMGs reduces muscle fatigue when squatting. Front. Neurorobot. 15:1–12

    Google Scholar 

  95. Weston EB, Alizadeh M, Hani H, Knapik GG, Souchereau RA, Marras WS (2021) A physiological and biomechanical investigation of three passive upper-extremity exoskeletons during simulated overhead work. Ergonomics 65(1):1–33

    Google Scholar 

  96. Wiggin, M. B., S. H. Collins, and G. S. Sawicki. A passive elastic ankle exoskeleton using controlled energy storage and release to reduce the metabolic cost of walking. In: Proceedings 7th Annual Dynamic Walking Conference, pp. 24–25, 2012.

  97. Zelik KE, Nurse CA, Schall MC, Sesek RF, Marino MC, Gallagher S (2022) An ergonomic assessment tool for evaluating the effect of back exoskeletons on injury risk. Appl Ergon. https://doi.org/10.1016/j.apergo.2021.103619

    Article  PubMed  Google Scholar 

  98. Zhang JT, Novak AC, Brouwer B, Li Q (2013) Concurrent validation of Xsens MVN measurement of lower limb joint angular kinematics. Physiol Meas. https://doi.org/10.1088/0967-3334/34/8/n63

    Article  PubMed  PubMed Central  Google Scholar 

Download references

Funding

Internal resources supported this research at the Rochester Institute of Technology.

Conflict of interest

The authors do not declare any conflict of interest in the work presented in this article.

Author information

Authors and Affiliations

  1. Biomechanics and Ergonomics Lab, Industrial and Systems Engineering Department, Rochester Institute of Technology, Rochester, NY, USA

    Pranav Madhav Kuber, Masoud Abdollahi & Ehsan Rashedi

  2. Center for Advanced Orthopaedic Studies, Beth Israel Deaconess Medical Center, Boston, MA, USA

    Mohammad Mehdi Alemi

  3. Department of Orthopaedic Surgery, Harvard Medical School, Boston, MA, USA

    Mohammad Mehdi Alemi

  4. Industrial and Systems Engineering Department, Rochester Institute of Technology, 1 Lomb Memorial Dr, Rochester, NY, 14623, USA

    Ehsan Rashedi

Authors
  1. Pranav Madhav Kuber
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Masoud Abdollahi
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Mohammad Mehdi Alemi
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Ehsan Rashedi
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Ehsan Rashedi.

Additional information

Associate Editor Stefan M. Duma oversaw the review of this article.

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Appendix

Appendix

See Table 6 .

Table 6 Risk of bias summary with B1: Bias arising from randomization process, B2: Bias due to deviations from intended interventions, B3: Bias due to missing outcome data, B4: Bias in measurement of the outcome, B5: Bias in selection of the reported result, B6: Bias due to missing information about prior musculoskeletal injury in participants.
Full size table

Rights and permissions

Springer Nature or its licensor holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Kuber, P.M., Abdollahi, M., Alemi, M.M. et al. A Systematic Review on Evaluation Strategies for Field Assessment of Upper-Body Industrial Exoskeletons: Current Practices and Future Trends. Ann Biomed Eng 50, 1203–1231 (2022). https://doi.org/10.1007/s10439-022-03003-1

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10439-022-03003-1

Keywords

Search

Navigation