Cited by 131Prosthetics and Rehabilitation RoboticsMuscle activation and electromyography studiesRobotic Locomotion and Control

A review of current state-of-the-art control methods for lower-limb powered prostheses

Open access
Gehlhar, Rachel, Tucker, Maegan, Young, Aaron J., Ames, Aaron D.·2023·Annual Reviews in Control

Abstract

Lower-limb prostheses aim to restore ambulatory function for individuals with lower-limb amputations. While the design of lower-limb prostheses is important, this paper focuses on the complementary challenge - the control of lower-limb prostheses. Specifically, we focus on powered prostheses, a subset of lower-limb prostheses, which utilize actuators to inject mechanical power into the walking gait of a human user. In this paper, we present a review of existing control strategies for lower-limb powered prostheses, including the control objectives, sensing capabilities, and control methodologies. We separate the various control methods into three main tiers of prosthesis control: high-level control for task and gait phase estimation, mid-level control for desired torque computation (both with and without the use of reference trajectories), and low-level control for enforcing the computed torque commands on the prosthesis. In particular, we focus on the high- and mid-level control approaches in this review. Additionally, we outline existing methods for customizing the prosthetic behavior for individual human users. Finally, we conclude with a discussion on future research directions for powered lower-limb prostheses based on the potential of current control methods and open problems in the field.

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1016/j.arcontrol.2023.03.003

Cites

6 of 6 references verified0 citation errors · 0 not checkable

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • Cybersecurity issues become a major problem when distribution networks grow more automated and linked due to smart technologies and EVs.

    “Cybersecurity issues become a major problem when distribution networks grow more automated and linked as a result of the combination of smart technologies and EVs.”

    From A Review: The Impact of High Penetration of EVs on Distribution Network and Its Management Strategy (2025) · cites this paper as [40]

    The Introduction’s “Current Limitations of Powered Prostheses” and Discussion’s “Open Problems” address prosthesis control faults, not cybersecurity in electricity distribution networks. Searches for cybersecurity, distribution networks, smart technologies, and EVs found no passage addressing the claim. Page numbers are unavailable in our copy. (LLM, conf=0.78)

    Experimental — accuracy not yet measured
  • These systems provide avenues for malicious actors to meddle in service and alter charging practices, posing a threat to public safety and increasing utility costs.

    “These systems provide avenues for malicious actors to meddle in service, alter charging practices, posing a threat to public safety and eating up utility money.”

    From A Review: The Impact of High Penetration of EVs on Distribution Network and Its Management Strategy (2025) · cites this paper as [40]

    The Introduction (Current Limitations of Powered Prostheses; page not provided) discusses device cost and mechanical or electronic failures, while the Discussion (Open Problems; page not provided) discusses user safety from prosthesis faults. Searches for malicious interference, charging practices, and utility costs found no passage addressing the claim. (LLM, conf=0.76)

    Experimental — accuracy not yet measured
  • EV charging and distribution activities are carried out through digital communication channels, making networks vulnerable to intrusions.

    “EV charging and distribution activities are carried out through digital communication channels, so networks are vulnerable to intrusions.”

    From A Review: The Impact of High Penetration of EVs on Distribution Network and Its Management Strategy (2025) · cites this paper as [40]

    The Sensing for Prosthesis Control > EMG Sensors and Discussion > Open Problems passages concern prosthesis sensors and control faults, not EV infrastructure. Searches for EV charging, digital communication, cybersecurity, and network intrusions found no passage addressing the claim. (LLM, conf=0.78)

    Experimental — accuracy not yet measured

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Cites

Flagged first, then by citations

Research works printed but not linked: 221

  1. Aghasadeghi N, Zhao H, Hargrove LJ, Ames AD, Perreault EJ, Bretl T, 2013. Learning impedance controller parameters for lower-limb prostheses, in: Intelligent robots and systems (IROS), 2013 IEEE/RSJ international conference on, IEEE. pp. 4268– 4274.
  2. Ames AD, 2014. Human-inspired control of bipedal walking robots. IEEE Transactions on Automatic Control 59, 1115– 1130.
  3. Ames AD, Galloway K, Sreenath K, Grizzle JW, 2014. Rapidly exponentially stabilizing control lyapunov functions and hybrid zero dynamics. IEEE Transactions on Automatic Control 59, 876– 891.
  4. Aminian K, Najafi B, Büla C, Leyvraz PF, Robert P, 2002. Spatio-temporal parameters of gait measured by an ambulatory system using miniature gyroscopes. Journal of biomechanics 35, 689– 699. 11955509
  5. Armannsdottir A, Tranberg R, Halldorsdottir G, Briem K, 2018. Frontal plane pelvis and hip kinematics of transfemoral amputee gait. effect of a prosthetic foot with active ankle dorsiflexion and individualized training – a case study. Disability and Rehabilitation: Assistive Technology 13, 388– 393. 28974119
  6. Au S, Berniker M, Herr H, 2008. Powered ankle-foot prosthesis to assist level-ground and stair-descent gaits. Neural Networks 21, 654– 666. Robotics and Neuroscience. 18499394
  7. Au SK, Herr HM, 2008. Powered ankle-foot prosthesis. IEEE Robotics & Automation Magazine 15, 52– 59. PMC8009500 33790527
  8. Au SK, Weber J, Herr H, 2009. Powered ankle–foot prosthesis improves walking metabolic economy. IEEE Transactions on robotics 25, 51– 66.
  9. Azocar AF, Mooney LM, Duval JF, Simon AM, Hargrove LJ, Rouse EJ, 2020. Design and clinical implementation of an open-source bionic leg. Nature Biomedical Engineering 4, 941 – 953. PMC7581510 33020601
  10. Barnett CT, Polman RC, Vanicek N, 2014. Longitudinal kinematic and kinetic adaptations to obstacle crossing in recent lower limb amputees. Prosthetics and Orthotics International 38, 437– 446. 24150931
  11. Bartlett HL, King ST, Goldfarb M, Lawson BE, 2021. A semi-powered ankle prosthesis and unified controller for level and sloped walking. IEEE Transactions on Neural Systems and Rehabilitation Engineering 29, 320– 329. 33400653
  12. Bartlett HL, King ST, Goldfarb M, Lawson BE, 2022. Design and assist-as-needed control of a lightly powered prosthetic knee. IEEE Transactions on Medical Robotics and Bionics 4, 490– 501.
  13. Baud R, Manzoori AR, Ijspeert A, Bouri M, 2021. Review of control strategies for lower-limb exoskeletons to assist gait. Journal of NeuroEngineering and Rehabilitation 18, 1– 34. 34315499 PMC8314580
  14. Best T. Kevin, Welker Cara Gonzalez, Rouse Elliott J., Gregg Robert D., 2022. Data-Driven Variable Impedance Control of a Powered Knee–Ankle Prosthesis for Adaptive Speed and Incline Walking. IEEE Transactions on Robotics 1– 19 techrxiv preprint techrxiv:19165895.v3. PMC10249435 37304232
  15. Best TK, Embry KR, Rouse EJ, Gregg RD, 2021. Phase-variable control of a powered knee-ankle prosthesis over continuously varying speeds and inclines, in: 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), IEEE. pp. 6182– 6189. PMC8890507 35251752
  16. Bhakta K, Camargo J, Compton W, Herrin K, Young A, 2021. Evaluation of continuous walking speed determination algorithms and embedded sensors for a powered knee & ankle prosthesis. IEEE Robotics and Automation Letters 6, 4820– 4826.
  17. Bhakta K, Camargo J, Donovan L, Herrin K, Young A, 2020a. Machine learning model comparisons of user independent & dependent intent recognition systems for powered prostheses. IEEE Robotics and Automation Letters 5, 5393– 5400.
  18. Bhakta K, Camargo J, Kunapuli P, Childers L, Young A, 2020b. Impedance control strategies for enhancing sloped and level walking capabilities for individuals with transfemoral amputation using a powered multi-joint prosthesis. Military medicine 185, 490– 499. 32074296
  19. Blumentritt S, Scherer HW, Wellershaws U, Michael JW, 1997. Design principles, biomeclianical data and clinical experience with a polycentric knee offering controlled stance phase knee flexion: A preliminary report. JPO Journal of Prosthetics and Orthotics 9, 18– 24.
  20. Bohannon R, 1997. Comfortable and maximum walking speed of adults aged 20–79 years: Reference values and determinants. Age and ageing 26, 15– 9. 9143432
  21. Boonstra A, Schrama J, Fidler V, Eisma W, 1995. The gait of unilateral transfemoral amputees. Scandinavian journal of rehabilitation medicine 26, 217– 23. 7878397
  22. Brandt A, Huang HH, 2019. Effects of extended stance time on a powered knee prosthesis and gait symmetry on the lateral control of balance during walking in individuals with unilateral amputation. Journal of neuroengineering and rehabilitation 16, 1– 11. 31783759 PMC6883569
  23. Brockway J, 1987. Derivation of formulae used to calculate energy expenditure in man. Human nutrition. Clinical nutrition 41, 463– 471. 3429265
  24. Browning R, Modica J, Kram R, Goswami A, 2007. The effects of adding mass to the legs on the energetics and biomechanics of walking. Medicine and science in sports and exercise 39, 515– 25. 17473778
  25. Camargo J, Bhakta K, Herrin K, Young A, 2023. Biomechanical evaluation of stair ambulation using impedance control on an active prosthesis. Journal of Biomechanical Engineering 145, 1– 9. 36149020
  26. Camargo J, Bhakta K, Maldonado-Contreras J, Zhou S, Herrin K, Young A, 2022. Opensim model for biomechanical analysis with the open-source bionic leg, in: 2022 International Symposium on Medical Robotics (ISMR), IEEE. pp. 1– 6.
  27. Camargo J, Flanagan W, Csomay-Shanklin N, Kanwar B, Young A, 2021a. A machine learning strategy for locomotion classification and parameter estimation using fusion of wearable sensors. IEEE Transactions on Biomedical Engineering 68, 1569– 1578. 33710951
  28. Camargo J, Ramanathan A, Flanagan W, Young A, 2021b. A comprehensive, open-source dataset of lower limb biomechanics in multiple conditions of stairs, ramps, and level-ground ambulation and transitions. Journal of Biomechanics 119, 110320. 33677231
  29. Caputo JM, Collins SH, 2014a. Prosthetic ankle push-off work reduces metabolic rate but not collision work in non-amputee walking. Scientific reports 4, 1– 9. PMC4252906 25467389
  30. Caputo JM, Collins SH, 2014b. A universal ankle–foot prosthesis emulator for human locomotion experiments. Journal of biomechanical engineering 136. 24337103
  31. Cempini M, Hargrove LJ, Lenzi T, 2017. Design, development, and bench-top testing of a powered polycentric ankle prosthesis, in: 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pp. 1064– 1069.
  32. Ceseracciu E, Reggiani M, Sawacha Z, Sartori M, Spolaor F, Cobelli C, Pagello E, 2010. Svm classification of locomotion modes using surface electromyography for applications in rehabilitation robotics, in: 19th International Symposium in Robot and Human Interactive Communication, IEEE. pp. 165– 170.
  33. Clites TR, Carty MJ, Ullauri JB, Carney ME, Mooney LM, Duval JF, Srinivasan SS, Herr HM, 2018. Proprioception from a neurally controlled lower-extremity prosthesis. Science Translational Medicine 10, eaap8373. 29848665
  34. Culver S, Bartlett H, Shultz A, Goldfarb M, 2018. A stair ascent and descent controller for a powered ankle prosthesis. IEEE Transactions on Neural Systems and Rehabilitation Engineering 26, 993– 1002. 29752234
  35. Culver SC, Vailati LG, Goldfarb M, 2022. A primarily-passive knee prosthesis with powered stance and swing assistance, in: 2022 International Conference on Rehabilitation Robotics (ICORR), pp. 1– 6. 36176112
  36. Delp SL, Anderson FC, Arnold AS, Loan P, Habib A, John CT, Guendelman E, Thelen DG, 2007. Opensim: open-source software to create and analyze dynamic simulations of movement. IEEE transactions on biomedical engineering 54, 1940– 1950. 18018689
  37. DeVita P, Helseth J, Hortobagyi T, 2007. Muscles do more positive than negative work in human locomotion. The Journal of experimental biology 210, 3361– 73. 17872990 PMC2577758
  38. Dewald HA, Lukyanenko P, Lambrecht JM, Anderson JR, Tyler DJ, Kirsch RF, Williams MR, 2019. Stable, three degree-of-freedom myoelectric prosthetic control via chronic bipolar intramuscular electrodes: a case study. Journal of NeuroEngineering and Rehabilitation 16, 1– 13. 31752886 PMC6868792
  39. Diaz JP, da Silva RL, Zhong B, Huang HH, Lobaton E, 2018. Visual terrain identification and surface inclination estimation for improving human locomotion with a lower-limb prosthetic, in: 2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), IEEE. pp. 1817– 1820. 30440748
  40. Eilenberg MF, Geyer H, Herr H, 2010. Control of a powered ankle–foot prosthesis based on a neuromuscular model. IEEE Transactions on Neural Systems and Rehabilitation Engineering 18, 164– 173. 20071268
  41. Elery T, Rezazadeh S, Nesler C, Gregg RD, 2020. Design and validation of a powered knee–ankle prosthesis with high-torque, low-impedance actuators. IEEE Transactions on Robotics 36, 1649– 1668. 33299386 PMC7720653
  42. Embry KR, Villarreal DJ, Macaluso RL, Gregg RD, 2018. Modeling the kinematics of human locomotion over continuously varying speeds and inclines. IEEE Transactions on Neural Systems and Rehabilitation Engineering 26, 2342– 2350. 30403633 PMC6358210
  43. Engsberg J, Lee A, Tedford K, Harder J, 1993. Normative ground reaction force data for able-bodied and below-knee-amputee children during walking. Journal of pediatric orthopedics 13, 169– 73. 8459005
  44. Esposito ER, Rodriguez KM, Ràbago CA, Wilken JM, 2014. Does unilateral transtibial amputation lead to greater metabolic demand during walking. J Rehabil Res Dev 51, 1287– 96. 25671680
  45. Evans RL, Arvind D, 2014. Detection of gait phases using orient specks for mobile clinical gait analysis, in: 2014 11th International Conference on Wearable and Implantable Body Sensor Networks, IEEE. pp. 149– 154.
  46. Eveld M, King S, Zelik K, Goldfarb M, 2022. Factors leading to falls in transfemoral prosthesis users: a case series of sound-side stumble recovery responses. Journal of NeuroEngineering and Rehabilitation 19. PMC9502957 36151561
  47. Farris D, Sawicki G, 2011. The mechanics and energetics of human walking and running: A joint level perspective. Journal of the Royal Society, Interface / the Royal Society 9, 110– 8. PMC3223624 21613286
  48. Fey NP, Simon AM, Young AJ, Hargrove LJ, 2014. Controlling knee swing initiation and ankle plantarflexion with an active prosthesis on level and inclined surfaces at variable walking speeds. IEEE Journal of Translational Engineering in Health and Medicine 2, 1– 12. PMC4861549 27170878
  49. Flash T, Hogan N, 1985. The coordination of arm movements: an experimentally confirmed mathematical model. Journal of Neuroscience 5, 1688– 1703. 4020415 PMC6565116
  50. Fleming A, Stafford N, Huang S, Hu X, Ferris DP, Huang HH, 2021. Myoelectric control of robotic lower limb prostheses: a review of electromyography interfaces, control paradigms, challenges and future directions. Journal of neural engineering 18, 041004. PMC8694273 34229307
  51. Flowers W, Mann R, 1977. An electrohydraulic knee-torque controller for a prosthesis simulator. Journal of biomechanical engineering 99, 3– 8. 23720163
  52. Fluit R, Prinsen E, Wang S, Kooij H, 2019. A comparison of control strategies in commercial and research knee prostheses. IEEE transactions on bio-medical engineering PP. 31021749
  53. Fritz S, Lusardi M, 2009. Walking speed: The sixth vital sign. J Geriatr Phys Ther 32, 46– 49. 20039582
  54. Fylstra BL, Lee IC, Li M, Lewek M, Huang H, 2022. Human-prosthesis cooperation: Combining adaptive prosthesis control with visual feedback guided gait. PMC9753428 36517814
  55. Gadaleta M, Cisotto G, Rossi M, Rehman RZU, Rochester L, Del Din S, 2019. Deep learning techniques for improving digital gait segmentation, in: 2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), IEEE. pp. 1834– 1837. 31946254
  56. Gailey R, 2008. Review of secondary physical conditions associated with lower-limb amputation and long-term prosthesis use. The Journal of Rehabilitation Research and Development 45, 15– 30. 18566923
  57. Gao X, Si J, Wen Y, Li M, Huang H, 2021. Reinforcement learning control of robotic knee with human-in-the-loop by flexible policy iteration. IEEE Transactions on Neural Networks and Learning Systems. 33956634
  58. Gehlhar R, 2023. Model-Based Lower-Limb Powered Prosthesis Control: Developing and Realizing Nonlinear Subsystem Control Methods for Generalizable Prosthesis Control. Ph.D. thesis. California Institute of Technology, USA.
  59. Gehlhar R, Ames AD, 2021. Separable control lyapunov functions with application to prostheses. IEEE Control Systems Letters 5, 559– 564.
  60. Gehlhar R, Ames AD, 2023. Emulating human kinematic behavior on lower-limb prostheses via multi-contact models and force-based nonlinear control, in: 2023 IEEE International Conference on Robotics and Automation (ICRA), IEEE.
  61. Gehlhar R, Reher J, Ames AD, 2019. Control of separable subsystems with application to prostheses. arXiv preprint arXiv:1909.03102. · arXiv
  62. Gehlhar R, Yang J.h., Ames AD, 2022. Powered prosthesis locomotion on varying terrains: Model-dependent control with real-time force sensing. IEEE Robotics and Automation Letters 7, 5151– 5158.
  63. Geyer H, Herr H, 2010. A muscle-reflex model that encodes principles of legged mechanics produces human walking dynamics and muscle activities. IEEE Transactions on Neural Systems and Rehabilitation Engineering 18, 263– 273. 20378480
  64. Gordon M, Thatte N, Geyer H, 2019. Online learning for proactive obstacle avoidance with powered transfemoral prostheses, in: 2019 International Conference on Robotics and Automation (ICRA), pp. 7920– 7925.
  65. Gregg RD, Lenzi T, Hargrove LJ, Sensinger JW, 2014a. Virtual constraint control of a powered prosthetic leg: From simulation to experiments with transfemoral amputees. IEEE Transactions on Robotics 30, 1455– 1471. 25558185 PMC4279455
  66. Gregg RD, Rouse EJ, Hargrove LJ, Sensinger JW, 2014b. Evidence for a time-invariant phase variable in human ankle control. PLOS ONE 9, 1– 13. PMC3928429 24558485
  67. Hafner BJ, Sanders JE, Czerniecki J, Fergason J, 2002. Energy storage and return prostheses: does patient perception correlate with biomechanical analysis? Clinical Biomechanics 17, 325– 344. 12084537
  68. Hansen A, Childress D, 2010. Investigations of roll-over shape: Implications for design, alignment, and evaluation of ankle-foot prostheses and orthoses. Disability and rehabilitation 32, 2201– 9. 20626257
  69. Hansen A, Childress D, Knox E, 2004a. Roll-over shapes of human locomotor systems: Effects of walking speed. Clinical biomechanics (Bristol, Avon) 19, 407– 14. 15109762
  70. Hansen AH, Childress DS, Miff SC, Gard SA, Mesplay KP, 2004b. The human ankle during walking: implications for design of biomimetic ankle prostheses. Journal of Biomechanics 37, 1467– 1474. 15336920
  71. Hansen N, 2006. The cma evolution strategy: a comparing review. Towards a new evolutionary computation, 75– 102.
  72. Hargrove LJ, Englehart K, Hudgins B, 2007. A comparison of surface and intramuscular myoelectric signal classification. IEEE transactions on biomedical engineering 54, 847– 853. 17518281
  73. Hargrove LJ, Simon AM, Young AJ, Lipschutz RD, Finucane SB, Smith DG, Kuiken TA, 2013. Robotic leg control with emg decoding in an amputee with nerve transfers. New England Journal of Medicine 369, 1237– 1242. 24066744
  74. Hargrove LJ, Young AJ, Simon AM, Fey NP, Lipschutz RD, Finucane SB, Halsne EG, Ingraham KA, Kuiken TA, 2015. Intuitive Control of a Powered Prosthetic Leg During Ambulation: A Randomized Clinical Trial. JAMA 313, 2244– 2252. 26057285
  75. He Z, Zhang W, 2011. Estimation of walking speed using accelerometer and artificial neural networks, in: International Workshop on Computer Science for Environmental Engineering and EcoInformatics, Springer. pp. 42– 47.
  76. Herr H, Grabowski A, 2011. Bionic ankle-foot prosthesis normalizes walking gait for persons with leg amputation. Proceedings. Biological sciences / The Royal Society 279, 457– 64. PMC3234569 21752817
  77. Hijjawi JB, Kuiken TA, Lipschutz RD, Miller LA, Stubblefield KA, Dumanian GA, 2006. Improved myoelectric prosthesis control accomplished using multiple nerve transfers. Plastic and reconstructive surgery 118, 1573– 1578. 17102730
  78. Hobara H, Kobayashi Y, Nakamura T, Yamasaki N, Nakazawa K, Akai M, Ogata T, 2011. Lower extremity joint kinematics of stair ascent in transfemoral amputees. Prosthetics and orthotics international 35, 467– 72. 22013154
  79. Hogan N, 1984a. Adaptive control of mechanical impedance by coactivation of antagonist muscles. IEEE Transactions on Automatic Control 29, 681– 690.
  80. Hogan N, 1984b. Impedance control: An approach to manipulation, in: 1984 American Control Conference, pp. 304– 313.
  81. Holgate MA, Sugar TG, Bohler AW, 2009. A novel control algorithm for wearable robotics using phase plane invariants, in: 2009 IEEE International Conference on Robotics and Automation, pp. 3845– 3850.
  82. Hong JH, Mun MS, 2005. Relationship between socket pressure and emg of two muscles in trans-femoral stumps during gait. Prosthetics and orthotics international 29, 59– 72. 16180378
  83. Hong W, Paredes V, Chao K, Patrick S, Hur P, 2019. Consolidated control framework to control a powered transfemoral prosthesis over inclined terrain conditions, in: 2019 International Conference on Robotics and Automation (ICRA), pp. 2838– 2844.
  84. Hood S, Gabert L, Lenzi T, 2022. Powered knee and ankle prosthesis with adaptive control enables climbing stairs with different stair heights, cadences, and gait patterns. IEEE Transactions on Robotics 38, 1430– 1441. 35686286 PMC9175645
  85. Hu JS, Sun KC, Cheng CY, 2013. A kinematic human-walking model for the normal-gait-speed estimation using tri-axial acceleration signals at waist location. IEEE Transactions on Biomedical Engineering 60, 2271– 2279. 23529073
  86. Huang H, Kuiken TA, Lipschutz RD,, 2008. A strategy for identifying locomotion modes using surface electromyography. IEEE Transactions on Biomedical Engineering 56, 65– 73. PMC3025288 19224720
  87. Huang HH, Si J, Brandt A, Li M, 2021. Taking both sides: seeking symbiosis between intelligent prostheses and human motor control during locomotion. Current Opinion in Biomedical Engineering 20, 100314. 34458654 PMC8388605
  88. Huang S, Ferris DP, 2012. Muscle activation patterns during walking from transtibial amputees recorded within the residual limb-prosthetic interface. Journal of neuroengineering and rehabilitation 9, 1– 16. 22882763 PMC3582563
  89. Huang S, Wensman JP, Ferris DP, 2014. An experimental powered lower limb prosthesis using proportional myoelectric control. Journal of Medical Devices 8.
  90. Hunt GR, Hood S, Lenzi T, 2021. Stand-up, squat, lunge, and walk with a robotic knee and ankle prosthesis under shared neural control. IEEE Open Journal of Engineering in Medicine and Biology 2, 267– 277. 35402979 PMC8901006
  91. Hurley GRB, McKenney R, Robinson M, Zadravec M, Pierrynowski MR, 1990. The role of the contralateral limb in below-knee amputee gait. Prosthetics and Orthotics International 14, 33– 42. 2192355
  92. Inman VT, 1966. Human locomotion. Canadian Medical Association journal 94 20, 1047– 54. 5942660 PMC1935424
  93. Isakov E, Burger H, Krajnik J, Gregorič M, Marinček Črt, 1997. Double-limb support and step-length asymmetry in below-knee amputees. Scandinavian journal of rehabilitation medicine 29 2, 75– 9. 9198256
  94. Jaegers SM, Arendzen JH, de Jongh HJ, 1995. Prosthetic gait of unilateral transfemoral amputees: a kinematic study. Archives of physical medicine and rehabilitation 76 8, 736– 43. 7632129
  95. Jayaraman C, Hoppe-Ludwig S, Deems-Dluhy S, McGuire M, Mummidisetty C, Siegal R, Naef A, Lawson BE, Goldfarb M, Gordon KE, Jayaraman A, 2018. Impact of powered knee-ankle prosthesis on low back muscle mechanics in transfemoral amputees: A case series. Frontiers in Neuroscience 12. PMC5874899 29623025
  96. Jiang S, Partrick S, Zhao H, Ames AD, 2012. Outputs of human walking for bipedal robotic controller design, in: 2012 American Control Conference (ACC), pp. 4843– 4848.
  97. King S, Eveld M, Martínez A, Zelik K, Goldfarb M, 2019. A novel system for introducing precisely-controlled, unanticipated gait perturbations for the study of stumble recovery. Journal of NeuroEngineering and Rehabilitation 16, 69. 31182126 PMC6558741
  98. Krausz NE, Lenzi T, Hargrove LJ, 2015. Depth sensing for improved control of lower limb prostheses. IEEE Transactions on Biomedical Engineering 62, 2576– 2587. 26111386
  99. Kuiken TA, Dumanian G, Lipschutz RD, Miller L, Stubblefield K, 2004. The use of targeted muscle reinnervation for improved myoelectric prosthesis control in a bilateral shoulder disarticulation amputee. Prosthetics and orthotics international 28, 245– 253. 15658637
  100. Kuiken TA, Li G, Lock BA, Lipschutz RD, Miller LA, Stubblefield KA, Englehart KB, 2009. Targeted muscle reinnervation for real-time myoelectric control of multifunction artificial arms. Jama 301, 619– 628. 19211469 PMC3036162
  101. Kurbis AG, Laschowski B, Mihailidis A, 2022. Stair recognition for robotic exoskeleton control using computer vision and deep learning. bioRxiv. 36176138
  102. Lawson BE, Ledoux ED, Goldfarb M, 2017. A robotic lower limb prosthesis for efficient bicycling. IEEE Transactions on Robotics 33, 432– 445.
  103. Lawson BE, Mitchell J, Truex D, Shultz A, Ledoux E, Goldfarb M, 2014. A robotic leg prosthesis: Design, control, and implementation. IEEE Robotics & Automation Magazine 21, 70– 81.
  104. Lawson BE, Ruhe B, Shultz A, Goldfarb M, 2015. A powered prosthetic intervention for bilateral transfemoral amputees. IEEE Transactions on Biomedical Engineering 62, 1042– 1050. 25014950 PMC4469379
  105. Lawson BE, Varol HA, Huff A, Erdemir E, Goldfarb M, 2013. Control of stair ascent and descent with a powered transfemoral prosthesis. IEEE Transactions on Neural Systems and Rehabilitation Engineering 21, 466– 473. 23096120
  106. Ledoux ED, Goldfarb M, 2017a. Control and evaluation of a powered transfemoral prosthesis for stair ascent. IEEE Transactions on Neural Systems and Rehabilitation Engineering 25, 917– 924. 28113346
  107. Ledoux ED, Goldfarb M, 2017b. Control and evaluation of a powered transfemoral prosthesis for stair ascent. IEEE Transactions on Neural Systems and Rehabilitation Engineering 25, 917– 924. 28113346
  108. Lee H, Hogan N, 2014. Time-varying ankle mechanical impedance during human locomotion. IEEE Transactions on Neural Systems and Rehabilitation Engineering 23. 25137730
  109. Lee IC, Liu M, Lewek MD, Hu X, Filer WG, Huang H, 2022. Towards safe wearer-prosthesis interaction: Evaluation of gait stability and human compensation strategy under faults in robotic transfemoral prostheses. IEEE Transactions on Neural Systems and Rehabilitation Engineering. 36136925
  110. Lee J, Goldfarb M, 2020. Swing-assist for enhancing stair ambulation in a primarily-passive knee prosthesis, in: 2020 IEEE International Conference on Robotics and Automation (ICRA), pp. 740– 746.
  111. Lee JT, Goldfarb M, 2021. Effect of a swing-assist knee prosthesis on stair ambulation. IEEE Transactions on Neural Systems and Rehabilitation Engineering 29, 2046– 2054. 34587090
  112. van Leeuwen JL, 1992. Muscle Function in Locomotion. chapter 7. pp. 191– 250.
  113. Lehmann JF, Price R, Okumura R, Questad K, de Lateur BJ, Négretot A, 1998. Mass and mass distribution of below-knee prostheses: Effect on gait efficacy and self-selected walking speed. Archives of Physical Medicine and Rehabilitation 79, 162– 168. 9473997
  114. Lempereur M, Rousseau F, Rémy-Néris O, Pons C, Houx L, Quellec G, Brochard S, 2020. A new deep learning-based method for the detection of gait events in children with gait disorders: Proof-of-concept and concurrent validity. Journal of biomechanics 98, 109490. 31740015
  115. Lenzi T, Hargrove L, Sensinger J, 2014. Speed-adaptation mechanism: Robotic prostheses can actively regulate joint torque. IEEE Robotics & Automation Magazine 21, 94– 107.
  116. Li K, Tucker M, Gehlhar R, Yue Y, Ames AD, 2022. Natural multicontact walking for robotic assistive devices via musculoskeletal models and hybrid zero dynamics. IEEE Robotics and Automation Letters 7, 4283– 4290.
  117. Li M, Wen Y, Gao X, Si J, Huang H, 2021. Toward expedited impedance tuning of a robotic prosthesis for personalized gait assistance by reinforcement learning control. IEEE Transactions on Robotics 38, 407– 420.
  118. Li Q, Young M, Naing V, Donelan J, 2010. Walking speed estimation using a shank-mounted inertial measurement unit. Journal of biomechanics 43, 1640– 1643. 20185136
  119. Liu M, Wang D, Huang H, 2015. Development of an environment-aware locomotion mode recognition system for powered lower limb prostheses. IEEE Transactions on Neural Systems and Rehabilitation Engineering 24, 434– 443. 25879962
  120. Liu W, Wu R, Si J, Huang H, 2022. A new robotic knee impedance control parameter optimization method facilitated by inverse reinforcement learning. IEEE Robotics and Automation Letters 7, 10882– 10889.
  121. Ma WL, Kolathaya S, Ambrose ER, Hubicki CM, Ames AD, 2017. Bipedal robotic running with durus-2d: Bridging the gap between theory and experiment, in: Proceedings of the 20th International Conference on Hybrid Systems: Computation and Control, Association for Computing Machinery, New York, NY, USA. p. 265– 274.
  122. Major MJ, Serba CK, Gordon KE, 2020. Perturbation recovery during walking is impacted by knowledge of perturbation timing in below-knee prosthesis users and non-impaired participants. Plos one 15, e0235686. 32658907 PMC7357748
  123. Mannini A, Genovese V, Sabatini AM, 2013. Online decoding of hidden markov models for gait event detection using foot-mounted gyroscopes. IEEE journal of biomedical and health informatics 18, 1122– 1130. 25014927
  124. Mariani B, Hoskovec C, Rochat S, Büla C, Penders J, Aminian K, 2010. 3d gait assessment in young and elderly subjects using foot-worn inertial sensors. Journal of biomechanics 43, 2999– 3006. 20656291
  125. Martin AE, Gregg RD, 2017. Stable, robust hybrid zero dynamics control of powered lower-limb prostheses. IEEE Transactions on Automatic Control 62, 3930– 3942. 29276305 PMC5736162
  126. Martinez-Villalpando EC, Mooney L, Elliott G, Herr H, 2011. Antagonistic active knee prosthesis. a metabolic cost of walking comparison with a variable-damping prosthetic knee, in: 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, pp. 8519– 8522. 22256326
  127. Mendez J, Hood S, Gunnel A, Lenzi T, 2020. Powered knee and ankle prosthesis with indirect volitional swing control enables level-ground walking and crossing over obstacles. Science Robotics 5, eaba6635. PMC8020725 33022611
  128. Miller WC, Deathe AB, Speechley M, Koval J, 2001a. The influence of falling, fear of falling, and balance confidence on prosthetic mobility and social activity among individuals with a lower extremity amputation. Archives of physical medicine and rehabilitation 82, 1238– 1244. 11552197
  129. Miller WC, Speechley M, Deathe B, 2001b. The prevalence and risk factors of falling and fear of falling among lower extremity amputees. Archives of Physical Medicine and Rehabilitation 82, 1031– 1037. 11494181
  130. Molen NH, 2004. Energy/speed relation of below-knee amputees walking on a motor-driven treadmill. Internationale Zeitschrift für angewandte Physiologie einschließlich Arbeitsphysiologie 31, 173– 185. 4696826
  131. Morgenroth DC, Segal AD, Zelik KE, Czerniecki JM, Klute GK, Adamczyk PG, Orendurff MS, Hahn ME, Collins SH, Kuo AD, 2011. The effect of prosthetic foot push-off on mechanical loading associated with knee osteoarthritis in lower extremity amputees. Gait & posture 34, 502– 507. 21803584 PMC3189331
  132. Murray RM, Sastry SS, Zexiang L, 1994. A Mathematical Introduction to Robotic Manipulation. 1st ed., CRC Press, Inc.
  133. Myung IJ, 2003. Tutorial on maximum likelihood estimation. Journal of mathematical Psychology 47, 90– 100.
  134. Naseri A, Liu M, Lee IC, Liu W, Huang H, 2022. Characterizing prosthesis control fault during human-prosthesis interactive walking using intrinsic sensors. IEEE Robotics and Automation Letters 7, 8307– 8314. 36713301 PMC9881473
  135. Nefian AV, Liang L, Pi X, Liu X, Murphy K, 2002. Dynamic bayesian networks for audio-visual speech recognition. EURASIP Journal on Advances in Signal Processing 2002, 1– 15.
  136. Nolan L, Lees A, 2000. The functional demands on the intact limb during walking for active trans-femoral and trans-tibial amputees. Prosthetics and orthotics international 24, 117– 25. 11061198
  137. Nolan L, Wit A, Dudziñski K, Lees A, Lake M, Wychowanski M, 2003. Adjustments in gait symmetry in trans-femoral and trans-tibial amputees. Gait & posture 17, 142– 51. 12633775
  138. Nowroozi F, Salvanelli ML, Gerber LH, 1983. Energy expenditure in hip disarticulation and hemipelvectomy amputees. Archives of physical medicine and rehabilitation 64 7, 300– 3. 6860105
  139. Olenšek A, Zadravec M, Burger H, Matjačić Z, 2021. Dynamic balancing responses in unilateral transtibial amputees following outward-directed perturbations during slow treadmill walking differ considerably for amputated and non-amputated side. Journal of NeuroEngineering and Rehabilitation 18, 1– 11. 34332595 PMC8325816
  140. Pasquina PF, Evangelista M, Carvalho AJ, Lockhart J, Griffin S, Nanos G, McKay P, Hansen M, Ipsen D, Vandersea J,, 2015. First-in-man demonstration of a fully implanted myoelectric sensors system to control an advanced electromechanical prosthetic hand. Journal of neuroscience methods 244, 85– 93. 25102286 PMC4317373
  141. Peeraer L, Aeyels B, Van der Perre G, 1990. Development of emg-based mode and intent recognition algorithms for a computercontrolled above-knee prosthesis. Journal of biomedical engineering 12, 178– 182. 2348704
  142. Pfeifer S, Vallery H, Hardegger M, Riener R, Perreault EJ, 2012. Model-based estimation of knee stiffness. IEEE transactions on biomedical engineering 59, 2604– 2612. 22801482 PMC3643895
  143. Price MA, Beckerle P, Sup FC, 2019. Design optimization in lower limb prostheses: A review. IEEE Transactions on Neural Systems and Rehabilitation Engineering 27, 1574– 1588. 31283485
  144. Quesada RE, Caputo JM, Collins SH, 2016. Increasing ankle push-off work with a powered prosthesis does not necessarily reduce metabolic rate for transtibial amputees. Journal of Biomechanics 49, 3452– 3459. 27702444
  145. Quintero D, Reznick E, Lambert DJ, Rezazadeh S, Gray L, Gregg RD, 2018a. Intuitive clinician control interface for a powered knee-ankle prosthesis: A case study. IEEE journal of translational engineering in health and medicine 6, 1– 9. PMC6286184 30546971
  146. Quintero D, Villarreal DJ, Lambert DJ, Kapp S, Gregg RD, 2018b. Continuous-phase control of a powered knee–ankle prosthesis: Amputee experiments across speeds and inclines. IEEE Transactions on Robotics 34, 686– 701. 30008623 PMC6042879
  147. Quintero Maldonado D, Reznick E, Lambert D, Rezazadeh S, Gray L, Gregg R, 2018. Intuitive clinician control interface for a powered knee-ankle prosthesis: A case study. IEEE Journal of Translational Engineering in Health and Medicine PP, 1– 1. PMC6286184 30546971
  148. Ralston HJ, 2004. Energy-speed relation and optimal speed during level walking. Internationale Zeitschrift für angewandte Physiologie einschließlich Arbeitsphysiologie 17, 277– 283. 13610523
  149. Reher JP, Hereid A, Kolathaya S, Hubicki CM, Ames AD, 2020. Algorithmic foundations of realizing multi-contact locomotion on the humanoid robot durus, in: Algorithmic Foundations of Robotics XII. Springer, pp. 400– 415.
  150. Rezazadeh S, Quintero D, Divekar N, Reznick E, Gray L, Gregg RD, 2019. A phase variable approach for improved rhythmic and non-rhythmic control of a powered knee-ankle prosthesis. IEEE Access 7, 109840– 109855. 31656719 PMC6813797
  151. Riener R, Rabuffetti M, Frigo C, 2002. Stair ascent and descent at different inclinations. Gait & Posture 15, 32– 44. 11809579
  152. Rouse EJ, Gregg RD, Hargrove LJ, Sensinger JW, 2013. The difference between stiffness and quasi-stiffness in the context of biomechanical modeling. IEEE Transactions on Biomedical Engineering 60, 562– 568. 23212310 PMC4266141
  153. Rouse EJ, Hargrove LJ, Perreault EJ, Kuiken TA, 2012. Estimation of human ankle impedance during walking using the perturberator robot, in: 2012 4th IEEE RAS & EMBS International Conference on Biomedical Robotics and Biomechatronics (BioRob), pp. 373– 378.
  154. Rouse EJ, Hargrove LJ, Perreault EJ, Kuiken TA, 2014a. Estimation of human ankle impedance during the stance phase of walking. IEEE Transactions on Neural Systems and Rehabilitation Engineering 22, 870– 878. 24760937 PMC5823694
  155. Rouse EJ, Mooney LM, Herr HM, 2014b. Clutchable series-elastic actuator: Implications for prosthetic knee design. The International Journal of Robotics Research 33, 1611– 1625.
  156. Sabatini AM, Martelloni C, Scapellato S, Cavallo F, 2005. Assessment of walking features from foot inertial sensing. IEEE Transactions on biomedical engineering 52, 486– 494. 15759579
  157. Sánchez Manchola MD, Bernal MJP, Munera M, Cifuentes CA, 2019. Gait phase detection for lower-limb exoskeletons using foot motion data from a single inertial measurement unit in hemiparetic individuals. Sensors 19, 2988. 31284619 PMC6650967
  158. Schmalz T, Blumentritt S, Marx B, 2007. Biomechanical analysis of stair ambulation in lower limb amputees. Gait & Posture 25, 267– 278. 16725325
  159. Schmid M, Beltrami G, Zambarbieri D, Verni G, 2005. Centre of pressure displacements in trans-femoral amputees during gait. Gait & posture 21, 255– 62. 15760740
  160. Sensinger JW, Lock BA, Kuiken TA, 2009. Adaptive pattern recognition of myoelectric signals: exploration of conceptual framework and practical algorithms. IEEE Transactions on Neural Systems and Rehabilitation Engineering 17, 270– 278. 19497834 PMC3025709
  161. Shorter AL, Rouse EJ, 2018. Mechanical impedance of the ankle during the terminal stance phase of walking. IEEE Transactions on Neural Systems and Rehabilitation Engineering 26, 135– 143. 28976318
  162. Shultz AH, Lawson BE, Goldfarb M, 2015. Running with a powered knee and ankle prosthesis. IEEE Transactions on Neural Systems and Rehabilitation Engineering 23, 403– 412. 25020138
  163. Sigurðardóttir J, 2015. EMG as a control parameter in lower limb prosthetics: surface vs. implanted electrodes. Ph.D. thesis. Reykjavik University.
  164. Simon AM, Fey NP, Ingraham KA, Finucane SB, Halsne EG, Hargrove LJ, 2016. Improved weight-bearing symmetry for transfemoral amputees during standing up and sitting down with a powered knee-ankle prosthesis. Archives of Physical Medicine and Rehabilitation 97, 1100– 1106. 26686876
  165. Simon AM, Ingraham KA, Fey NP, Finucane SB, Lipschutz RD, Young AJ, Hargrove LJ, 2014. Configuring a powered knee and ankle prosthesis for transfemoral amputees within five specific ambulation modes. PloS one 9, e99387. 24914674 PMC4051756
  166. Sinitski EH, Lemaire ED, Baddour N, Besemann M, Dudek N, Hebert JS, 2021. Maintaining stable transtibial amputee gait on level and simulated uneven conditions in a virtual environment. Disability and Rehabilitation: Assistive Technology 16, 40– 48. 31349766
  167. Sinnet RW, Zhao H, Ames AD, 2011. Simulating prosthetic devices with human-inspired hybrid control, in: 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems, IEEE. pp. 1723– 1730.
  168. Sreenath K, Park HW, Poulakakis I, Grizzle J, 2013. Embedding active force control within the compliant hybrid zero dynamics to achieve stable, fast running on mabel. The International Journal of Robotics Research 32, 324– 345.
  169. Sturk JA, Lemaire ED, Sinitski EH, Dudek NL, Besemann M, Hebert JS, Baddour N, 2019. Maintaining stable trans-femoral amputee gait on level, sloped and simulated uneven conditions in a virtual environment. Disability and Rehabilitation: Assistive Technology 14, 226– 235. 29276850
  170. Sup F, Bohara A, Goldfarb M, 2008. Design and control of a powered transfemoral prosthesis. The International Journal of Robotics Research 27, 263– 273. 19898683 PMC2773553
  171. Sup F, Varol HA, Goldfarb M, 2011. Upslope walking with a powered knee and ankle prosthesis: Initial results with an amputee subject. IEEE Transactions on Neural Systems and Rehabilitation Engineering 19, 71– 78. 20952344
  172. Sup IV F, Varol A, Mitchell J, Withrow T, Goldfarb M, 2009. Preliminary evaluations of a self-contained anthropomorphic trans-femoral prosthesis. IEEE/ASME transactions on mechatronics: a joint publication of the IEEE Industrial Electronics Society and the ASME Dynamic Systems and Control Division 14, 667– 676. 20054424 PMC2801882
  173. Svensson W, Holmberg U, 2005. Foot and ground measurement using portable sensors, in: 9th International Conference on Rehabilitation Robotics, 2005. ICORR 2005., pp. 448– 451.
  174. Taborri J, Palermo E, Rossi S, Cappa P, 2016. Gait partitioning methods: A systematic review. Sensors 16, 66. 26751449 PMC4732099
  175. Taborri J, Scalona E, Palermo E, Rossi S, Cappa P, 2015. Validation of inter-subject training for hidden markov models applied to gait phase detection in children with cerebral palsy. Sensors 15, 24514– 24529. 26404309 PMC4610555
  176. Teixeira-Salmela LF, Nadeau S, Milot MH, Gravel D, Requião LF, 2008. Effects of cadence on energy generation and absorption at lower extremity joints during gait. Clinical Biomechanics 23, 769– 778. 18384921
  177. Thatte N, 2019. Design and Evaluation of Robust Control Methods for Robotic Transfemoral Prostheses. Ph.D. thesis. Carnegie Mellon University, USA.
  178. Thatte N, Duan H, Geyer H, 2018. A method for online optimization of lower limb assistive devices with high dimensional parameter spaces, in: 2018 IEEE International Conference on Robotics and Automation (ICRA), IEEE. pp. 5380– 5385.
  179. Thatte N, Geyer H, 2015. Toward balance recovery with leg prostheses using neuromuscular model control. IEEE Transactions on Biomedical Engineering 63, 904– 913. 26315935 PMC4854805
  180. Thatte N, Geyer H, 2022. Comparison of balance recovery among current control strategies for robotic leg prostheses, in: Moreno JC, Masood J, Schneider U, Maufroy C, Pons JL (Eds.), Wearable Robotics: Challenges and Trends, Springer International Publishing, Cham. pp. 63– 67.
  181. Thatte N, Shah T, Geyer H, 2019a. Robust and adaptive lower limb prosthesis stance control via extended kalman filter-based gait phase estimation. IEEE Robotics and Automation Letters 4, 3129– 3136.
  182. Torburn L, Schweiger G, Perry J, Powers C, 1994. Below-knee amputee gait in stair ambulation: A comparison of stride characteristics using five different prosthetic feet. Clinical orthopaedics and related research, 185– 92. 8194232
  183. Tran M, Gabert L, Cempini M, Lenzi T, 2019. A lightweight, efficient fully powered knee prosthesis with actively variable transmission. IEEE Robotics and Automation Letters 4, 1186– 1193.
  184. Ulf Holmberg WS, 2006. An autonomous control system for a prosthetic foot ankle. IFAC Proceedings Volumes 39, 856– 861. 4th IFAC Symposium on Mechatronic Systems.
  185. Vack HJ, Nielsen DH, Shurp DG, 1999. Kinetic patterns during stair ascent in patients with transtibial amputations using three different prostheses. Jpo Journal of Prosthetics and Orthotics 11, 57– 62.
  186. Vaskov AK, Vu PP, North N, Davis AJ, Kung TA, Gates DH, Cederna PS, Chestek CA, 2022. Surgically implanted electrodes enable real-time finger and grasp pattern recognition for prosthetic hands. IEEE Transactions on Robotics. PMC10168021 37193351
  187. Vathsangam H, Emken A, Spruijt-Metz D, Sukhatme GS, 2010. Toward free-living walking speed estimation using gaussian process-based regression with on-body accelerometers and gyroscopes, in: 2010 4th International Conference on Pervasive Computing Technologies for Healthcare, IEEE. pp. 1– 8.
  188. Villarreal D, Gregg R, 2016. Unified phase variables of relative degree two for human locomotion, in: 2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), IEEE. pp. 6262– 6267. PMC5324719 28261013
  189. Villarreal DJ, Gregg RD, 2014. A survey of phase variable candidates of human locomotion, in: 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, pp. 4017– 4021. PMC4288014 25570873
  190. Villarreal DJ, Poonawala HA, Gregg RD, 2017. A robust parameterization of human gait patterns across phase-shifting perturbations. IEEE Transactions on Neural Systems and Rehabilitation Engineering 25, 265– 278. 27187967 PMC5107364
  191. Vrieling A, Van Keeken H, Schoppen T, Otten E, Halbertsma J, Hof A, Postema K, 2007. Obstacle crossing in lower limb amputees. Gait & posture 26, 587– 594. 17275306
  192. Vu HTT, Dong D, Cao HL, Verstraten T, Lefeber D, Vanderborght B, Geeroms J, 2020. A review of gait phase detection algorithms for lower limb prostheses. Sensors 20, 3972. 32708924 PMC7411778
  193. Vu HTT, Gomez F, Cherelle P, Lefeber D, Nowé A, Vanderborght B, 2018. Ed-fnn: A new deep learning algorithm to detect percentage of the gait cycle for powered prostheses. Sensors 18, 2389. 30041421 PMC6068484
  194. Wang J, Kannape OA, Herr HM, 2013. Proportional emg control of ankle plantar flexion in a powered transtibial prosthesis, in: 2013 IEEE 13th International Conference on Rehabilitation Robotics (ICORR), pp. 1– 5. 24187210
  195. Waters RL, Mulroy S, 1999. The energy expenditure of normal and pathologic gait. Gait & Posture 9, 207– 231. 10575082
  196. Waters RL, Perry J, Antonelli DJ, Hislop HJ, 1976a. Energy cost of walking of amputees: the influence of level of amputation. The Journal of bone and joint surgery. American volume 58 1, 42– 6. 1249111
  197. Waters RL, Perry J, Antonelli DJ, Hislop HJ, 1976b. Energy cost of walking of amputees: the influence of level of amputation. The Journal of bone and joint surgery. American volume 58 1, 42– 6. 1249111
  198. Welker CG, Voloshina AS, Chiu VL, Collins SH, 2021. Shortcomings of human-in-the-loop optimization of an ankle-foot prosthesis emulator: a case series. Royal Society open science 8, 202020. 34035945 PMC8097204
  199. Wen Y, Li M, Si J, Huang H, 2020. Wearer-prosthesis interaction for symmetrical gait: a study enabled by reinforcement learning prosthesis control. IEEE transactions on neural systems and rehabilitation engineering 28, 904– 913. 32149646 PMC7250159
  200. Wen Y, Si J, Brandt A, Gao X, Huang HH, 2019. Online reinforcement learning control for the personalization of a robotic knee prosthesis. IEEE transactions on cybernetics 50, 2346– 2356. 30668514

200 of 221 shown

Cited by

Sorted by citations

Authors
Gehlhar, R., Tucker, M., Young, A. J., & Ames, A. D.
Affiliations
  • California Institute of Technology (US)
  • Georgia Institute of Technology (US)
Corresponding author
Gehlhar, Rachel
Venue
Annual Reviews in Control
Publisher
Elsevier BV
Published
2023
Volume
55
Pages
142-164
ISSN
1367-5788 (ISSN-L)
OpenAlex
W4362576326
Cited by
131
References
6
Citations by year
2026: 24 · 2025: 50 · 2024: 46 · 2023: 11
FWCI
10.35
Type
journal article
Language
en
Open access
Locations
  • Annual Reviews in Control (acceptedVersion)
  • PubMed (publishedVersion)
  • PubMed Central (acceptedVersion)
Funders
  • National Science Foundation (1923239, 1924526)
  • National Institutes of Health (DP2-HD111709)
Topics
  • Physical Sciences › Engineering › Biomedical Engineering › Prosthetics and Rehabilitation Robotics
  • Physical Sciences › Engineering › Biomedical Engineering › Muscle activation and electromyography studies
  • Physical Sciences › Engineering › Biomedical Engineering › Robotic Locomotion and Control
Keywords
prosthetic control, lower limb amputation, gait phase estimation, reference trajectory, high-level control, low-level control, sensory feedback

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review