The exoskeleton expansion: improving walking and running economy

Gregory S Sawicki, Owen N Beck, Inseung Kang, Aaron J Young, Gregory S Sawicki, Owen N Beck, Inseung Kang, Aaron J Young

Abstract

Since the early 2000s, researchers have been trying to develop lower-limb exoskeletons that augment human mobility by reducing the metabolic cost of walking and running versus without a device. In 2013, researchers finally broke this 'metabolic cost barrier'. We analyzed the literature through December 2019, and identified 23 studies that demonstrate exoskeleton designs that improved human walking and running economy beyond capable without a device. Here, we reviewed these studies and highlighted key innovations and techniques that enabled these devices to surpass the metabolic cost barrier and steadily improve user walking and running economy from 2013 to nearly 2020. These studies include, physiologically-informed targeting of lower-limb joints; use of off-board actuators to rapidly prototype exoskeleton controllers; mechatronic designs of both active and passive systems; and a renewed focus on human-exoskeleton interface design. Lastly, we highlight emerging trends that we anticipate will further augment wearable-device performance and pose the next grand challenges facing exoskeleton technology for augmenting human mobility.

Keywords: Assistive devices; Augmentation; Economy; Energetic; Metabolic cost; Run; Walk; Wearable robotics.

Conflict of interest statement

The authors declare that they have no competing interests.

Figures

Fig. 1
Fig. 1
Milestones illustrating the advancement of exoskeleton technology. Tethered (blue) and autonomous (red) exoskeletons assisting at the ankle (circle), knee (triangle), and hip (square) joint to improve healthy, natural walking (left) and running (right) economy versus using no device are shown
Fig. 2
Fig. 2
The year that each exoskeleton study was published versus the change in net metabolic cost versus walking or running without using the respective device. Red indicates autonomous and blue indicates a tethered exoskeletons. Different symbols indicate the leg joint(s) that each device directly targets. Asterisk indicates special case and cross indicates a passive exoskeleton

References

    1. Ferris DP. The exoskeletons are here. J Neuroeng Rehabil. 2009;6:17.
    1. Herr H. Exoskeletons and orthoses: classification, design challenges and future directions. J Neuroeng Rehabil. 2009;6:21.
    1. Beneke R, Meyer K. Walking performance and economy in chronic heart failure patients pre and post exercise training. Eur J Appl Physiol Occup Physiol. 1997;75(3):246–251.
    1. Hoogkamer W, et al. Altered running economy directly translates to altered distance-running performance. Med Sci Sports Exerc. 2016;48(11):2175–2180.
    1. Newman AB, et al. Association of long-distance corridor walk performance with mortality, cardiovascular disease, mobility limitation, and disability. JAMA. 2006;295(17):2018–2026.
    1. Gerardi D, et al. Variables related to increased mortality following out-patient pulmonary rehabilitation. Eur Respir J. 1996;9(3):431–435.
    1. Norris JA, et al. Effect of augmented plantarflexion power on preferred walking speed and economy in young and older adults. Gait Posture. 2007;25(4):620–627.
    1. Walsh CJ, Endo K, Herr H. A quasi-passive leg exoskeleton for load-carrying augmentation. Int J Humanoid Robot. 2007;4(3):487–506.
    1. Sawicki GS, Ferris DP. Mechanics and energetics of level walking with powered ankle exoskeletons. J Exp Biol. 2008;211:1402–1413.
    1. Gregorczyk KN, et al. Effects of a lower-body exoskeleton device on metabolic cost and gait biomechanics during load carriage. Ergonomics. 2010;53:1263–1275.
    1. Malcolm P, et al. A simple exoskeleton that assists plantarflexion can reduce the metabolic cost of human walking. PLoS One. 2013;8:e56137.
    1. Mooney Luke M, Rouse Elliott J, Herr Hugh M. Autonomous exoskeleton reduces metabolic cost of human walking. Journal of NeuroEngineering and Rehabilitation. 2014;11(1):151.
    1. Collins SH, Wiggin MB, Sawicki GS. Reducing the energy cost of human walking using an unpowered exoskeleton. Nature. 2015;522:212–215.
    1. Lee G, et al. Reducing the metabolic cost of running with a tethered soft exosuit. Sci Robot. 2017;2(6):eaan6708.
    1. Kim J, et al. 2018 IEEE International Conference on Robotics and Automation (ICRA) 2018. Autonomous and portable soft exosuit for hip extension assistance with online walking and running detection algorithm.
    1. Kim J, et al. Reducing the metabolic rate of walking and running with a versatile, portable exosuit. Science. 2019;365(6454):668.
    1. Nasiri R, Ahmadi A, Ahmadabadi MN. Reducing the energy cost of human running using an unpowered exoskeleton. IEEE Trans Neural Syst Rehabil Eng. 2018;26(10):2026–2032.
    1. Simpson CS, et al. Connecting the legs with a spring improves human running economy. J Exp Biol. 2019;222(17):jeb202895.
    1. Mooney Luke M, Rouse Elliott J, Herr Hugh M. Autonomous exoskeleton reduces metabolic cost of human walking during load carriage. Journal of NeuroEngineering and Rehabilitation. 2014;11(1):80.
    1. Lee S, et al. Autonomous multi-joint soft exosuit with augmentation-power-based control parameter tuning reduces energy cost of loaded walking. J Neuroeng Rehabil. 2018;15(1):66.
    1. MacLean MK, Ferris DP. Energetics of walking with a robotic knee exoskeleton. J Appl Biomech. 2019;35(5):320.
    1. Seo K, Lee J, Park YJ. 2017 IEEE International Conference on Rehabilitation Robotics (ICORR) 2017. Autonomous hip exoskeleton saves metabolic cost of walking uphill.
    1. Kim D-S, et al. A wearable hip-assist robot reduces the cardiopulmonary metabolic energy expenditure during stair ascent in elderly adults: a pilot cross-sectional study. BMC Geriatr. 2018;18(1):230.
    1. Sawicki GS, Ferris DP. Powered ankle exoskeletons reveal the metabolic cost of plantar flexor mechanical work during walking with longer steps at constant step frequency. J Exp Biol. 2009;212:21–31.
    1. Mooney LM, Herr HM. Biomechanical walking mechanisms underlying the metabolic reduction caused by an autonomous exoskeleton. J Neuroeng Rehabil. 2016;13:4.
    1. Seo K, et al. 2016 IEEE International Conference on Robotics and Automation (ICRA) 2016. Fully autonomous hip exoskeleton saves metabolic cost of walking.
    1. Galle S, et al. Reducing the metabolic cost of walking with an ankle exoskeleton: interaction between actuation timing and power. J Neuroeng Rehabil. 2017;14(1):35.
    1. Lee Y, et al. 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) 2017. A flexible exoskeleton for hip assistance.
    1. Lee H, et al. A wearable hip assist robot can improve gait function and cardiopulmonary metabolic efficiency in elderly adults. IEEE Trans Neural Syst Rehabil Eng. 2017;25(9):1549–1557.
    1. Ding Y, et al. Human-in-the-loop optimization of hip assistance with a soft exosuit during walking. Science Robotics. 2018;3(15):eaar5438.
    1. Panizzolo FA, et al. Reducing the energy cost of walking in older adults using a passive hip flexion device. J Neuroeng Rehabil. 2019;16(1):117.
    1. Lim B, et al. Delayed outputf feedback control for gait assistance with a robotic hip exoskeleton. IEEE Trans Robot. 2019;35(4):1055–1062.
    1. Khazoom C, et al. Design and control of a multifunctional ankle exoskeleton powered by magnetorheological actuators to assist walking, jumping, and landing. IEEE Robot Automation Lett. 2019;4(3):3083–3090.
    1. Farley CT, McMahon TA. Energetics of walking and running: insights from simulated reduced-gravity experiments. J Appl Physiol. 1992;73(6):2709–2712.
    1. Kipp S, Kram R, Hoogkamer W. Extrapolating metabolic savings in running: implications for performance predictions. Front Physiol. 2019;10:79.
    1. Umberger BR, Rubenson J. Understanding muscle energetics in locomotion: new modeling and experimental approaches. Exerc Sport Sci Rev. 2011;39(2):59–67.
    1. Sawicki GS, Lewis CL, Ferris DP. It pays to have a spring in your step. Exerc Sport Sci Rev. 2009;37(3):130.
    1. Chen W, et al. On the biological mechanics and energetics of the hip joint muscle–tendon system assisted by passive hip exoskeleton. Bioinspir Biomim. 2018;14(1):016012.
    1. Browning RC, et al. The effects of adding mass to the legs on the energetics and biomechanics of walking. Med Sci Sports Exerc. 2007;39(3):515–525.
    1. Yan T, et al. Review of assistive strategies in powered lower-limb orthoses and exoskeletons. Robot Auton Syst. 2015;64:120–136.
    1. Koller JR, et al. Learning to walk with an adaptive gain proportional myoelectric controller for a robotic ankle exoskeleton. J Neuroeng Rehabil. 2015;12(1):1.
    1. Young AJ, Gannon H, Ferris DP. A biomechanical comparison of proportional electromyography control to biological torque control using a powered hip exoskeleton. Front Bioeng Biotechnol. 2017;5:37.
    1. Zhang J, Cheah CC, Collins SH. Torque Control in Legged Locomotion. In: Sharbafi MA, Seyfarth A, editors. Bioinspired Legged Locomotion. Amsterdam: Elsevier; 2017. p. 347–400.
    1. Zhang J, et al. Human-in-the-loop optimization of exoskeleton assistance during walking. Science. 2017;356(6344):1280.
    1. Quinlivan BT, et al. Assistance magnitude versus metabolic cost reductions for a tethered multiarticular soft exosuit. Sci Robot. 2017;2(2):1–10.
    1. Kang I, Hsu H, Young A. The effect of hip assistance levels on human energetic cost using robotic hip exoskeletons. IEEE Robot Automation Lett. 2019;4(2):430–437.
    1. Jackson RW, Collins SH. An experimental comparison of the relative benefits of work and torque assistance in ankle exoskeletons. J Appl Physiol. 2015;119(5):541–557.
    1. Ding Y, et al. Effect of timing of hip extension assistance during loaded walking with a soft exosuit. J Neuroeng Rehabil. 2016;13(1):87.
    1. Guizzo E, Goldstein H. The rise of the body bots [robotic exoskeletons] IEEE Spectr. 2005;42(10):50–56.
    1. Zoss AB, Kazerooni H, Chu A. Biomechanical design of the Berkeley lower extremity exoskeleton (BLEEX) IEEE/ASME Trans Mechatronics. 2006;11(2):128–138.
    1. Walsh CJ, Pasch K, Herr H. An autonomous, underactuated exoskeleton for load-carrying augmentation. In: 2006 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS); 2006.
    1. Raytheon XOS. 2 exoskeleton, second-generation robotics suit. 2010.
    1. Caputo JM, Collins SH. 2013 IEEE International Conference on Robotics and Automation. 2013. An experimental robotic testbed for accelerated development of ankle prostheses.
    1. Ding Y, et al. 2014 IEEE International Conference on Robotics and Automation (ICRA) 2014. Multi-joint actuation platform for lower extremity soft exosuits.
    1. Young A, et al. Influence of power delivery timing on the energetics and biomechanics of humans wearing a hip exoskeleton. Front Bioeng Biotechnol. 2017;5:4.
    1. Witte Kirby Ann, Collins Steven H. Wearable Robotics. 2020. Design of Lower-Limb Exoskeletons and Emulator Systems; pp. 251–274.
    1. Caputo JM, Collins SH, Adamczyk PG. 2014 IEEE International Workshop on Advanced Robotics and its Social Impacts. 2014. Emulating prosthetic feet during the prescription process to improve outcomes and justifications.
    1. Kim M, et al. Human-in-the-loop bayesian optimization of wearable device parameters. PLoS One. 2017;12(9):e0184054.
    1. Diller S, Majidi C, Collins SH. 2016 IEEE International Conference on Robotics and Automation (ICRA) 2016. A lightweight, low-power electroadhesive clutch and spring for exoskeleton actuation.
    1. Donelan JM, et al. Biomechanical energy harvesting: generating electricity during walking with minimal user effort. Science. 2008;319(5864):807–810.
    1. Beck ON, et al. Exoskeletons improve locomotion economy by reducing active muscle volume. Exerc Sport Sci Rev. 2019;47(4):237–245.
    1. Braun DJ, et al. Variable stiffness spring actuators for low-energy-cost human augmentation. IEEE Trans Robot. 2019;35(6):1435–1449.
    1. Yandell MB, et al. Physical interface dynamics alter how robotic exosuits augment human movement: implications for optimizing wearable assistive devices. J Neuroeng Rehabil. 2017;14(1):40.
    1. Giovacchini F, et al. A light-weight active orthosis for hip movement assistance. Robot Auton Syst. 2015;73:123–134.
    1. Lv G, Zhu H, Gregg RD. On the design and control of highly backdrivable lower-limb exoskeletons: a discussion of past and ongoing work. IEEE Control Syst Mag. 2018;38(6):88–113.
    1. Asbeck AT, et al. IEEE International Conference on Rehabilitation Robotics. 2013. Biologically-inspired soft exosuit.
    1. Panizzolo FA, et al. A biologically-inspired multi-joint soft exosuit that can reduce the energy cost of loaded walking. J Neuroeng Rehabil. 2016;13(1):43.
    1. Lee S, et al. 2018 IEEE International Conference on Robotics and Automation (ICRA) 2018. Autonomous Multi-Joint Soft Exosuit for Assistance with Walking Overground.
    1. Felt W, et al. “Body-in-the-loop”: optimizing device parameters using measures of instantaneous energetic cost. PLoS One. 2015;10:e0135342.
    1. Ingraham KA, Ferris DP, Remy CD. Evaluating physiological signal salience for estimating metabolic energy cost from wearable sensors. J Appl Physiol. 2019;126(3):717–729.
    1. Slade P, et al. Rapid energy expenditure estimation for ankle assisted and inclined loaded walking. J Neuroeng Rehabil. 2019;16(1):67.
    1. Huang H, et al. A cyber expert system for auto-tuning powered prosthesis impedance control parameters. Ann Biomed Eng. 2016;44(5):1613–1624.
    1. Kumar S, et al. IEEE Transactions on Control Systems Technology. 2019. Extremum seeking control for model-free auto-tuning of powered prosthetic legs; pp. 1–16.
    1. Huang H, et al. Continuous locomotion-mode identification for prosthetic legs based on neuromuscular-mechanical fusion. IEEE Trans Biomed Eng. 2011;58(10):2867–2875.
    1. Young AJ, Hargrove LJ. A classification method for user-independent intent recognition for transfemoral amputees using powered lower limb prostheses. IEEE Trans Neural Syst Rehabil Eng. 2016;24(2):217–225.
    1. Ferris DP, et al. An improved powered ankle-foot orthosis using proportional myoelectric control. Gait Posture. 2006;23(4):425–428.
    1. Sawicki GS, Ferris DP. A pneumatically powered knee-ankle-foot orthosis (KAFO) with myoelectric activation and inhibition. J Neuroeng Rehabil. 2009;6:23.
    1. Ferris DP, Lewis CL. 2009 Annual international conference of the Ieee engineering in medicine and biology society. 2009. Robotic lower limb exoskeletons using proportional myoelectric control; pp. 2119–2124.
    1. Koller JR, Remy CD, Ferris DP. Biomechanics and energetics of walking in powered ankle exoskeletons using myoelectric control versus mechanically intrinsic control. J Neuroeng Rehabil. 2018;15(1):42.
    1. Grazi L, et al. Gastrocnemius myoelectric control of a robotic hip exoskeleton can reduce the user's lower-limb muscle activities at push off. Front Neurosci. 2018;12:71.
    1. Young A, Kuiken T, Hargrove L. Analysis of using EMG and mechanical sensors to enhance intent recognition in powered lower limb prostheses. J Neural Eng. 2014;11(5):056021.
    1. Kang I, et al. 2019 IEEE 16th International Conference on Rehabilitation Robotics (ICORR) 2019. Electromyography (EMG) signal contributions in speed and slope estimation using robotic exoskeletons.
    1. Steele KM, et al. Muscle recruitment and coordination with an ankle exoskeleton. J Biomech. 2017;59:50–58.
    1. Kao P-C, Lewis CL, Ferris DP. Short-term locomotor adaptation to a robotic ankle exoskeleton does not alter soleus Hoffmann reflex amplitude. J Neuroeng Rehabil. 2010;7:33.
    1. Kao P-C, Lewis CL, Ferris DP. Joint kinetic response during unexpectedly reduced plantar flexor torque provided by a robotic ankle exoskeleton during walking. J Biomech. 2010;43(7):1401–1407.
    1. Weyand PG, et al. Faster top running speeds are achieved with greater ground forces not more rapid leg movements. J Appl Physiol. 2000;89(5):1991–1999.
    1. Sutrisno A, Braun DJ. Enhancing mobility with quasi-passive variable stiffness exoskeletons. IEEE Trans Neural Syst Rehabil Eng. 2019;27(3):487–496.
    1. Lane AR, et al. Body mass index and type 2 collagen turnover in individuals after anterior cruciate ligament reconstruction. J Athl Train. 2019;54(3):270–275.

Source: PubMed

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