Walking faster and farther with a soft robotic exosuit: Implications for post-stroke gait assistance and rehabilitation

Louis N Awad, Pawel Kudzia, Dheepak Arumukhom Revi, Terry D Ellis, Conor J Walsh, Louis N Awad, Pawel Kudzia, Dheepak Arumukhom Revi, Terry D Ellis, Conor J Walsh

Abstract

Objective: Soft robotic exosuits can improve the mechanics and energetics of walking after stroke. Building on this prior work, we evaluated the effects of the first prototype of a portable soft robotic exosuit.

Methods: Exosuit-induced changes in the overground walking speed, distance, and energy expenditure of individuals post-stroke were evaluated statistically with alpha set to 0.05 and compared to minimal clinically important difference scores.

Results: Compared to baseline walking without the exosuit worn, the <5kg exosuit did not substantially modify walking speed, distance, or energy expenditure when worn unpowered. In contrast, when the exosuit was powered on to provide an average 22.87±0.58 %bodyweight of plantarflexor force assistance during the paretic limb's stance phase and assist the paretic dorsiflexors during swing phase to reduce drop-foot, study participants walked a median 0.14±0.06 m/s faster during the 10-meter walk test and traveled 32±8 m farther during the six minute walk test.

Conclusions: Individuals post-stroke can leverage the paretic plantarflexor and dorsiflexor assistance provided by soft robotic exosuits to achieve clinically-meaningful increases in speed and distance.

Keywords: Exosuit; propulsion; soft robotics; stroke; walking distance; walking speed.

Figures

Figure 1.
Figure 1.
(A) Total 6-minute walk test (6MWT) distances for each condition. Right – Difference in 6MWT distance between the no exosuit condition and each of the two unpowered exosuit conditions and the powered exosuit condition. Circles represent individual study participants. (B) Distance per minute of the 6MWT for each condition. The minimal clinically important difference (MCID) is depicted in each plot with the dashed horizontal lines. Significance () relative to no exosuit and unpowered exosuit conditions. Medians and sIQR are reported.
Figure 2.
Figure 2.
(A) Usual and (B) Maximum walking speeds, as measured using the 10-meter walk test, are shown for each condition tested. Right – The difference in each speed between the no exosuit condition and each of the two unpowered exosuit conditions and the powered exosuit condition. Circles represent individual study participants. The minimal clinically important difference (MCID) is depicted in each plot with the dashed horizontal lines. Significance () relative to no exosuit and unpowered exosuit conditions. Medians and sIQR are reported.
Figure 3.
Figure 3.
(A) Energy expenditure, measured with indirect calorimetry as oxygen utilization per kilogram of bodyweight and minute and (B) energy cost of walking, measured as oxygen utilization per kilogram of bodyweight and meter walked are presented for each condition. Medians and sIQR are reported.
Figure 4.
Figure 4.
(A) Overview of the soft robotic exosuit used to augment paretic ankle plantarflexion (PF) and dorsiflexion (DF) function during post-stroke hemiparetic walking. (B) Exemplar force profiles for PF and DF assistance are shown. The onset timing and peak magnitude of PF assistance and the onset and off timing of DF assistance were commanded as described in previous work . Assistance timing was delivered as a function of the paretic and nonparetic gait cycles defined by the detection of paretic (green) and nonparetic (red) foot strike and foot off. Photo in panel A courtesy of Rolex Foundation.

References

    1. Esquenazi A., Talaty M., and Jayaraman A., “Powered exoskeletons for walking assistance in persons with central nervous system injuries: A narrative review,” PM&R, vol. 9, no. 1, pp. 46–62, Jan. 2017.
    1. Hendricks H. T., van Limbeek J., Geurts A. C., and Zwarts M. J., “Motor recovery after stroke: A systematic review of the literature,” Arch. Physical Medicine Rehabil., vol. 83, no. 11, pp. 1629–37, Nov. 2002.
    1. Veale A. J. and Xie S. Q., “Towards compliant and wearable robotic orthoses: A review of current and emerging actuator technologies,” Med. Eng. Phys., vol. 38, no. 4, pp. 317–25, Apr. 2016.
    1. Bae J. et al., “Biomechanical mechanisms underlying exosuit-induced improvements in walking economy after stroke,” J. Exp. Biol., vol. 221, no. 5, Mar. 2018, Paper jeb168815.
    1. Awad L. N. et al., “A soft robotic exosuit improves walking in patients after stroke,” Sci. Translational Medicine, vol. 9, no. 400, Jul. 2017, Paper eaai9084.
    1. Schmidt K. et al., “The myosuit: Bi-articular anti-gravity exosuit that reduces hip extensor activity in sitting transfers,” Frontiers Neurorobotics, vol. 11, Oct. 2017, Art. no. 57.
    1. Sridar S., Qiao Z., Muthukrishnan N., Zhang W., and Polygerinos P., “A soft-inflatable exosuit for knee rehabilitation: Assisting swing phase during walking,” Frontiers Robot. AI, vol. 5, no. 44, May 2018.
    1. Panizzolo F. A., Bolgiani C., Liddo L. D., Annese E., and Marcolin G., “Reducing the energy cost of walking in older adults using a passive hip flexion device,” J. Neuroengineering Rehabil., vol. 16, no. 1, Dec. 2019.
    1. Bae J. et al., “A lightweight and efficient portable soft exosuit for paretic ankle assistance in walking after stroke,” in Proc. IEEE Int. Conf. Robot. Autom, May 2018, pp. 2820–2827.
    1. Awad L. N. et al., “Reducing circumduction and hip hiking during hemiparetic walking through targeted assistance of the paretic limb using a soft robotic exosuit,” Amer. J. Physical Medicine Rehabil., vol. 96, no. 10, pp. S157–S164, Oct. 2017.
    1. Fulk G. D., Reynolds C., Mondal S., and Deutsch J. E., “Predicting home and community walking activity in people with stroke,” Arch. Physical Medicine Rehabil., vol. 91, no. 10, pp. 1582–1586, Oct. 2010.
    1. Fulk G. D., He Y., Boyne P., and Dunning K., “Predicting home and community walking activity poststroke,” Stroke, vol. 48, no. 2, pp. 406–411, Feb. 2017.
    1. Awad L., Reisman D., and Binder-Macleod S., “Distance-induced changes in walking speed after stroke: Relationship to community walking activity,” J. Neurologic Physical Therapy: JNPT, vol. 43, no. 4, pp. 220–223, Oct. 2019.
    1. Brazg G. et al., “Effects of training intensity on locomotor performance in individuals with chronic spinal cord injury: A randomized crossover study,” Neurorehabilitation Neural Repair, vol. 31, no. 10-11, pp. 944–954, Oct. 2017.
    1. Kleim J. A. and Jones T. A., “Principles of experience-dependent neural plasticity: Implications for rehabilitation after brain damage,” J. Speech, Lang., Hearing Res.: JSLHR, vol. 51, no. 1, pp. S225–S239, Feb. 2008.
    1. Leech K. A. and Hornby T. G., “High-intensity locomotor exercise increases brain-derived neurotrophic factor in individuals with incomplete spinal cord injury,” J. Neurotrauma, vol. 34, no. 6, pp. 1240–1248, Mar. 2017.
    1. Hornby T. G. et al., “Clinical practice guideline to improve locomotor function following chronic stroke, incomplete spinal cord injury, and brain injury,” J. Neurologic Physical Therapy, vol. 44, no. 1, pp. 49–100, Jan. 2020.
    1. Combs S. A., Puymbroeck M. Van, Altenburger P. A., Miller K. K., Dierks T. A., and Schmid A. A., “Is walking faster or walking farther more important to persons with chronic stroke?” Disability Rehabil., vol. 35, no. 10, pp. 860–867, May 2013.
    1. Hornby T. G. et al., “Contributions of stepping intensity and variability to mobility in individuals poststroke,” Stroke, vol. 50, no. 9, pp. 2492–2499, Sep. 2019.
    1. Bethoux F. et al., “The effects of peroneal nerve functional electrical stimulation versus ankle-foot orthosis in patients with chronic stroke: A randomized controlled trial,” Neurorehabilitation Neural Repair, vol. 28, no. 7, pp. 688–97, Sep. 2014.
    1. Everaert D. G. et al., “Effect of a foot-drop stimulator and ankle-foot orthosis on walking performance after stroke: A multicenter randomized controlled trial,” Neurorehabilitation Neural Repair, vol. 27, no. 7, pp. 579–591, Sep. 2013.
    1. Leech K. A., Kinnaird C. R., Holleran C. L., Kahn J., and Hornby T. G., “Effects of locomotor exercise intensity on gait performance in individuals with incomplete spinal cord injury,” Physical Therapy, vol. 96, no. 12, pp. 1919–1929, Dec. 2016.
    1. Reinkensmeyer D., Akoner O., Ferris D., and Gordon K., “Slacking by the human motor system: Computational models and implications for robotic orthoses,” in Proc. Annu. Int. Conf. IEEE Eng. Medicine Biol. Soc., Sep. 2009, vol. 2009, pp. 2129–2132.
    1. Reinkensmeyer D. J., Wolbrecht E., and Bobrow J., “A computational model of human-robot load sharing during robot-assisted arm movement training after stroke,” in Proc. 29th Annu. Int. Conf. IEEE Eng. Medicine Biol. Soc., Aug. 2007, vol. 2007, pp. 4019–4023.
    1. Hidler J. et al., “Multicenter randomized clinical trial evaluating the effectiveness of the lokomat in subacute stroke,” Neurorehabilitation Neural Repair, vol. 23, no. 1, pp. 5–13, Jan. 2009.
    1. Hornby T. George et al., “Importance of specificity, amount, and intensity of locomotor training to improve ambulatory function in patients poststroke,” Topics Stroke Rehabil., vol. 18, no. 4, pp. 293–307, Jul. 2011.
    1. Bae J. et al., “A soft exosuit for patients with stroke: Feasibility study with a mobile off-board actuation unit,” in Proc. IEEE Int. Conf. Rehabil. Robot., Aug. 2015, pp. 131–138.
    1. Tang A., Eng J. J., and Rand D., “Relationship between perceived and measured changes in walking after stroke,” J. Neurologic Physical Therapy: JNPT, vol. 36, no. 3, pp. 115–121, Sep. 2012.
    1. Louie D. R. and Eng J. J., “Powered robotic exoskeletons in post-stroke rehabilitation of gait: A scoping review,” J. NeuroEngineering Rehabil., vol. 13, no. 1, Dec. 2016.
    1. Jayaraman A. et al., “Immediate adaptations to post-stroke walking performance using a wearable robotic exoskeleton,” Arch. Physical Medicine Rehabil., Sep. 2019.
    1. Graham S. A., Roth E. J., and Brown D. A., “Walking and balance outcomes for stroke survivors: A randomized clinical trial comparing body-weight-supported treadmill training with versus without challenging mobility skills,” J. NeuroEngineering Rehabil., vol. 15, no. 1, Dec. 2018.
    1. Shi B. et al., “Wearable ankle robots in post-stroke rehabilitation of gait: A systematic review,” Frontiers Neurorobotics, vol. 13, Aug. 2019, Art. no. 63.
    1. Perera S., Mody S. H., Woodman R. C., and Studenski S. A., “Meaningful change and responsiveness in common physical performance measures in older adults,” J. Amer. Geriatrics Soc., vol. 54, no. 5, pp. 743–749, May 2006.
    1. Barthuly A. M., Bohannon R. W., and Gorack W., “Gait speed is a responsive measure of physical performance for patients undergoing short-term rehabilitation,” Gait Posture, vol. 36, no. 1, pp. 61–64, May 2012.
    1. Tilson J. K. et al., “Meaningful gait speed improvement during the first 60 days poststroke: Minimal clinically important difference,” Physical Therapy, vol. 90, no. 2, pp. 196–208, Feb. 2010.
    1. McDonald J. H., Multiple Comparisons - Handbook of Biological Statistics. 3rd ed, Baltimore, Maryland, USA: Sparky House Publishing, 2014.

Source: PubMed

Sponsorer och medarbetare

Medicinska tillstånd

Läkemedelsinterventioner

3
Prenumerera