Effects of Locomotion Mode Recognition Errors on Volitional Control of Powered Above-Knee Prostheses

Recent studies have reported various methods that recognize amputees' intent regarding locomotion modes, which is potentially useful for volitional control of powered artificial legs. However, occasional errors in locomotion mode recognition are inevitable. When these intent recognition decisions are used for volitional prosthesis control, the effects of the decision errors on the operation of the prosthesis and user's task performance is unknown. Hence, the goals of this study were to 1) systematically investigate the effects of locomotion mode recognition errors on volitional control of powered prosthetic legs and the user's gait stability, and 2) identify the critical mode recognition errors that impact safe and confident use of powered artificial legs in lower limb amputees. Five able-bodied subjects and two above-knee (AK) amputees were recruited and tested when wearing a powered AK prosthesis. Four types of locomotion mode recognition errors with different duration and at different gait phases were purposely applied to the prosthesis control. The subjects' gait stabilities were subjectively and objectively quantified. The results showed that not all of the mode recognition errors in volitional prosthesis control disturb the subjects' gait stability. The effects of errors on the user's balance depended on 1) the gait phase when the errors happened and 2) the amount of mechanical work change applied on the powered knee caused by the errors. Based on the study results, “critical errors” were defined and suggested as a new index to evaluate locomotion mode recognition algorithms for artificial legs. The outcome of this study might aid the future design of volitionally-controlled powered prosthetic legs that are reliable and safe for practice.

[1]  Robert D. Lipschutz,et al.  Robotic leg control with EMG decoding in an amputee with nerve transfers. , 2013, The New England journal of medicine.

[2]  Hugh Herr,et al.  Agonist-antagonist active knee prosthesis: a preliminary study in level-ground walking. , 2009, Journal of rehabilitation research and development.

[3]  Frank C. Sup,et al.  A powered self-contained knee and ankle prosthesis for near normal gait in transfemoral amputees. , 2009 .

[4]  Hugh M. Herr,et al.  Powered ankle-foot prosthesis to assist level-ground and stair-descent gaits , 2008, Neural Networks.

[5]  Neville Hogan,et al.  Impedance Control: An Approach to Manipulation: Part II—Implementation , 1985 .

[6]  Marko B. Popovic,et al.  Angular momentum regulation during human walking: biomechanics and control , 2004, IEEE International Conference on Robotics and Automation, 2004. Proceedings. ICRA '04. 2004.

[7]  Reed Ferber,et al.  Reactive balance adjustments to unexpected perturbations during human walking. , 2002, Gait & posture.

[8]  Ann M. Simon,et al.  An intent recognition strategy for transfemoral amputee ambulation across different locomotion modes , 2013, 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

[9]  Fan Zhang,et al.  Source Selection for Real-Time User Intent Recognition Toward Volitional Control of Artificial Legs , 2013, IEEE Journal of Biomedical and Health Informatics.

[10]  Michael Goldfarb,et al.  Design and Control of a Powered Transfemoral Prosthesis , 2008, Int. J. Robotics Res..

[11]  J. Czerniecki,et al.  Mechanical work adaptations of above-knee amputee ambulation. , 1996, Archives of physical medicine and rehabilitation.

[12]  Fan Zhang,et al.  Improving Finite State Impedance Control of Active-Transfemoral Prosthesis Using Dempster-Shafer Based State Transition Rules , 2014, J. Intell. Robotic Syst..

[13]  Fan Zhang,et al.  Continuous Locomotion-Mode Identification for Prosthetic Legs Based on Neuromuscular–Mechanical Fusion , 2011, IEEE Transactions on Biomedical Engineering.

[14]  He Huang,et al.  A Strategy for Identifying Locomotion Modes Using Surface Electromyography , 2009, IEEE Transactions on Biomedical Engineering.

[15]  L. Nashner Balance adjustments of humans perturbed while walking. , 1980, Journal of neurophysiology.

[16]  Marko B. Popovic,et al.  Angular momentum in human walking , 2008, Journal of Experimental Biology.

[17]  Michael Goldfarb,et al.  Multiclass Real-Time Intent Recognition of a Powered Lower Limb Prosthesis , 2010, IEEE Transactions on Biomedical Engineering.

[18]  Ernest P Hanavan,et al.  A mathematical model of the human body , 1964 .

[19]  P O Riley,et al.  Dynamic stability in elders: momentum control in locomotor ADL. , 1998, The journals of gerontology. Series A, Biological sciences and medical sciences.