Assessing the Efficacy of Passive Exoskeletons for Construction Work: Lab-Based Study

NCT04567797 | Unknown FDA Device

• 1 other identifier: 2007820207
• Study Type: interventional
• Target: 25
• Locations: 1 country
• Sites: 1

Brief Summary

This project aims to assess the effectiveness and acceptability of four types of commercial Back support exoskeletons (BSEs) for concrete work tasks. BSEs are external wearable devices designed to reduce physical demands on the back by providing assistive moments to body joints to support muscles. There is considerable evidence to suggest such exoskeletons reduce the risks of back injuries for workers performing repetitive tasks. However, since the effects of using BSEs in concrete work tasks are still unknown, evidence-based information regarding effectiveness, productivity impact, and safety risks is required to help industries adopt BSEs as an ergonomic intervention.

Conditions

Healthy

Keywords

passive exoskeleton

Outcome Measures

Primary Outcomes (2)

• Muscle activities while performing simulated construction tasks

  Surface electromyography sensors will be placed on the following muscles of participants: Descending Trapezius (TRP), Anterior Deltoid (AD), Iliocostalis Lumborum (ILL), Rectus Abdominis (RA), External Oblique (EO), Cervical Erector Spinae (CES), Latissimus Dorsi (LD), and Vastus Lateralis (VL). Muscle activities while performing tasks represent the physical workload. Maximum Voluntary Contraction (MVC) technique will be used to normalize the muscle activities for comparison.

  From admission to discharge, up to 3 hours

• Body segment motions in a three-dimensional space measured by two methods

  Method 1: Wearable inertial sensors will be attached using hypoallergenic double-sided tape at the low-back near the waist (S1), upper back (T6), sternum, upper arm (R, L), lower arm (R, L), thigh (R, L), and shank (R, L). Body segment motions will be used to calculate relative angles, repetition count, duration of postures, which represent the physical workload of tasks. Method 2: Optical markers will be placed on anatomical landmarks of participants including the head, shoulders, arms, hands, back, pelvis, legs, and feet. The data collected my optical markers are mainly used for calibrating other sensors.

  From admission to discharge, up to 3 hours

Secondary Outcomes (1)

• Subjective review of workload level and experience using different exoskeleton

  From admission to discharge, up to 3 hours

Study Arms (1)

Exoskeleton

EXPERIMENTAL

To compare the efficacy of four different exoskeleton devices, all participants will be asked to finish simulated construction tasks with each exoskeleton. Additionally, all participants will be asked to finish the same tasks without wearing an exoskeleton for reference.

Device: Laevo 2; Device: backX; Device: FLx ErgoSkeleton; Device: V22 ErgoSkeleton

Interventions

Laevo 2 DEVICE

The Laevo V2 is a wearable chest and back support exoskeleton. The Laevo transfers the from its chest pad to the thighs while bending forward. The passive exoskeleton (works with gas springs, not motors) transfers part of the load away from the back muscles, reducing the pressure on the spinal column. It provides a dampening effect on the back, reducing the risk of sudden back muscle contractions that needlessly overcompress the spine.

Exoskeleton

backX DEVICE

backX is a novel industrial exoskeleton that substantially augments its wearer and reduces the forces and torques on a wearer's lower back region (L5/S1 disc) by an average of 60% while the wearer is stooping, lifting objects, bending or reaching. backX augments the wearer's strength and can reduce the risk of back injuries among workers. It does not require external motors or power source. The mechanism of backX is similar to the first device "Laevo 2".

Exoskeleton

FLx ErgoSkeleton DEVICE

The FLx ErgoSkeleton is a range limiting work vest for physical work use. The FLx naturally reminds the user of the correct posture and lifting techniques while on the job site.

Exoskeleton

V22 ErgoSkeleton DEVICE

Similar to the FLx ErgoSkeleton, the V22 ErgoSkeleton keeps the position of the human body as to always stay within a safe body posture while lifting or moving heavy objects. The V22 ErgoSkeleton applies pressure to remind the user both during improper lifts and over rotation. In addition, the V22 ErgoSkeleton comes with two clutch controlled cables to assist in lifting and moving. The cables transfer part of the weight of the object being held directly to the V22 ErgoSkeleton vest, similar to other arm and shoulder support exoskeletons.

Exoskeleton

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Healthy Volunteers: Yes
• Age Groups: Adult (18-64), Older Adult (65+)

You may qualify if:

• Be at least 18 years old.
• Be able to walk and/or lift heavy objects without pain/discomfort.

You may not qualify if:

• Have prior back/neck injuries or chronic pain in the last 6 months.
• Have a pacemakers.
• Have breast implants.
• Have removed the axillary lymph nodes.
• Pregnant women.
• Using blood thinning medications.
• Participants must consult a physician prior to participating this study if any of the following occurred before or during use: Inguinal hernia, hernia, knee injury hip/knee prosthesis, hyperextended knee, recent surgery, skin disease/injury, scars, inflammation, skin reddening.

Sponsors & Collaborators

• University of Arizona: lead

Study Sites (1)

Smart Life in Motion (SLIM) Lab

Tucson, Arizona, 85721, United States

Location

Related Publications (21)

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  PMID: 19394867 BACKGROUND

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  PMID: 9502361 BACKGROUND

• Kavcic N, Grenier S, McGill SM. Quantifying tissue loads and spine stability while performing commonly prescribed low back stabilization exercises. Spine (Phila Pa 1976). 2004 Oct 15;29(20):2319-29. doi: 10.1097/01.brs.0000142222.62203.67.

  PMID: 15480148 BACKGROUND

• Allison GT, Godfrey P, Robinson G. EMG signal amplitude assessment during abdominal bracing and hollowing. J Electromyogr Kinesiol. 1998 Feb;8(1):51-7. doi: 10.1016/s1050-6411(97)00004-7.

  PMID: 9667034 BACKGROUND

• O'Sullivan PB, Twomey L, Allison GT. Altered abdominal muscle recruitment in patients with chronic back pain following a specific exercise intervention. J Orthop Sports Phys Ther. 1998 Feb;27(2):114-24. doi: 10.2519/jospt.1998.27.2.114.

  PMID: 9475135 BACKGROUND

• Vera-Garcia FJ, Elvira JL, Brown SH, McGill SM. Effects of abdominal stabilization maneuvers on the control of spine motion and stability against sudden trunk perturbations. J Electromyogr Kinesiol. 2007 Oct;17(5):556-67. doi: 10.1016/j.jelekin.2006.07.004. Epub 2006 Sep 22.

  PMID: 16996278 BACKGROUND

• Vera-Garcia FJ, Brown SH, Gray JR, McGill SM. Effects of different levels of torso coactivation on trunk muscular and kinematic responses to posteriorly applied sudden loads. Clin Biomech (Bristol). 2006 Jun;21(5):443-55. doi: 10.1016/j.clinbiomech.2005.12.006. Epub 2006 Jan 27.

  PMID: 16442677 BACKGROUND

• Rogers, E. (2020). The Survey of Occupational Injuries and Illnesses Respondent Follow-Up Survey. Monthly Labor Review.

  BACKGROUND

• Dong, X., Chowdhury, R., McCann, M., Trahan, C., & Gittle-man, J. S. (2008). The construction chart book: The US construction industry and its workers. In The Center for Construction Research and Training. Silver Spring.

  BACKGROUND

• West GH, Dawson J, Teitelbaum C, Novello R, Hunting K, Welch LS. An analysis of permanent work disability among construction sheet metal workers. Am J Ind Med. 2016 Mar;59(3):186-95. doi: 10.1002/ajim.22545. Epub 2016 Jan 21.

  PMID: 26792244 BACKGROUND

• Marcum J, Adams D. Work-related musculoskeletal disorder surveillance using the Washington state workers' compensation system: Recent declines and patterns by industry, 1999-2013. Am J Ind Med. 2017 May;60(5):457-471. doi: 10.1002/ajim.22708. Epub 2017 Mar 15.

  PMID: 28295479 BACKGROUND

• Ngo, B. P., Yazdani, A., Carlan, N., & Wells, R. (2017). Lifting height as the dominant risk factor for low-back pain and loading during manual materials handling: A scoping review. IISE Transactions on Occupational Ergonomics and Human Factors, 5(3-4), 158-171.

  BACKGROUND

• Kincl LD, Anton D, Hess JA, Weeks DL. Safety voice for ergonomics (SAVE) project: protocol for a workplace cluster-randomized controlled trial to reduce musculoskeletal disorders in masonry apprentices. BMC Public Health. 2016 Apr 27;16:362. doi: 10.1186/s12889-016-2989-x.

  PMID: 27121123 BACKGROUND

• Dong, X., Betit, E., Dale, A., Barlet, G., and Wei, G. (2019). Trends of Musculoskeletal Disorders and Interventions in the Construction Industry. Quarterly Data Report by CPWR.

  BACKGROUND

• Madinei S, Alemi MM, Kim S, Srinivasan D, Nussbaum MA. 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. 2020 May;62(3):441-457. doi: 10.1177/0018720819890966. Epub 2020 Jan 14.

  PMID: 31934773 BACKGROUND

• Alemi MM, Madinei S, Kim S, Srinivasan D, Nussbaum MA. Effects of Two Passive Back-Support Exoskeletons on Muscle Activity, Energy Expenditure, and Subjective Assessments During Repetitive Lifting. Hum Factors. 2020 May;62(3):458-474. doi: 10.1177/0018720819897669. Epub 2020 Feb 4.

  PMID: 32017609 BACKGROUND

• Lim S, D'Souza C. Statistical prediction of load carriage mode and magnitude from inertial sensor derived gait kinematics. Appl Ergon. 2019 Apr;76:1-11. doi: 10.1016/j.apergo.2018.11.007. Epub 2018 Nov 29.

  PMID: 30642513 BACKGROUND

• Lim S, D'Souza C. Statistical Prediction of Hand Force Exertion Levels in a Simulated Push Task using Posture Kinematics. Proc Hum Factors Ergon Soc Annu Meet. 2017 Sep;61(1):1031-1035. doi: 10.1177/1541931213601741. Epub 2017 Sep 28.

  PMID: 29276370 BACKGROUND

• Lim S, D'Souza C. Inertial Sensor-based Measurement of Thoracic-Pelvic Coordination Predicts Hand-Load Levels in Two-handed Anterior Carry. Proc Hum Factors Ergon Soc Annu Meet. 2018 Sep;62(1):798-799. doi: 10.1177/1541931218621181. Epub 2018 Sep 27. No abstract available.

  PMID: 32322142 BACKGROUND

• Lim, S. (2019). Combining Inertial Sensing and Predictive Modeling for Biomechanical Exposure Assessment in Specific Material Handling Work (Doctoral dissertation), University of Michigan, Ann Arbor.

  BACKGROUND

Study Officials

• Xiang Yang, Master

  University of Arizona

  PRINCIPAL INVESTIGATOR

Central Study Contacts

Sol Lim, Ph.D.

CONTACT

520-626-0728; lims@arizona.edu

Xiang Yang, Master

CONTACT

520-788-3880; xiangyang@email.arizona.edu

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: NA
• Masking: NONE
• Purpose: PREVENTION
• Intervention Model: SINGLE GROUP
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Principal Investigator

Study Record Dates

• First Submitted: September 4, 2020
• First Posted: September 29, 2020
• Study Start: October 1, 2020
• Primary Completion: December 1, 2020
• Study Completion: January 1, 2021
• Last Updated: September 29, 2020

Record last verified: 2020-09

Data Sharing

• IPD Sharing: Will not share

Locations

US (1)