Toward Design of an Environment-aware Adaptive Locomotion-mode-recognition System

Overview

Journal IEEE Trans Biomed Eng

Specialties Biomedical Engineering
Biophysics

Date 2012 Sep 22

PMID 22996721

Citations 14

Authors

Lin Du

Fan Zhang

Ming Liu

He Huang

Affiliations

Soon will be listed here.

Abstract

In this study, we aimed to improve the performance of a locomotion-mode-recognition system based on neuromuscular-mechanical fusion by introducing additional information about the walking environment. Linear-discriminant-analysis-based classifiers were first designed to identify a lower limb prosthesis user's locomotion mode based on electromyographic signals recorded from residual leg muscles and ground reaction forces measured from the prosthetic pylon. Nine transfemoral amputees who wore a passive hydraulic knee or powered prosthetic knee participated in this study. Information about the walking terrain was simulated and modeled as prior probability based on the principle of maximum entropy and integrated into the discriminant functions of the classifier. When the correct prior knowledge of walking terrain was simulated, the classification accuracy for each locomotion mode significantly increased and no task transitions were missed. In addition, simulated incorrect prior knowledge did not significantly reduce system performance, indicating that our design is robust against noisy and imperfect prior information. Furthermore, these observations were independent of the type of prosthesis applied. The promising results in this study may assist the further development of an environment-aware adaptive system for locomotion-mode recognition for powered lower limb prostheses or orthoses.

Citing Articles

Review on Portable-Powered Lower Limb Exoskeletons.

Jiang C, Xiao J, Wei H, Wang M, Chen C Sensors (Basel). 2025; 24(24.

PMID: 39771825 PMC: 11679449. DOI: 10.3390/s24248090.

Bilateral Elimination Rule-Based Finite Class Bayesian Inference System for Circular and Linear Walking Prediction.

Sheng W, Gao T, Liang K, Wang Y Biomimetics (Basel). 2024; 9(5).

PMID: 38786476 PMC: 11118229. DOI: 10.3390/biomimetics9050266.

Comparison of machine learning and deep learning-based methods for locomotion mode recognition using a single inertial measurement unit.

Vu H, Cao H, Dong D, Verstraten T, Geeroms J, Vanderborght B Front Neurorobot. 2022; 16:923164.

PMID: 36524219 PMC: 9745042. DOI: 10.3389/fnbot.2022.923164.

Ambulation Mode Classification of Individuals with Transfemoral Amputation through A-Mode Sonomyography and Convolutional Neural Networks.

Murray R, Mendez J, Gabert L, Fey N, Liu H, Lenzi T Sensors (Basel). 2022; 22(23).

PMID: 36502055 PMC: 9736589. DOI: 10.3390/s22239350.

EMG-driven control in lower limb prostheses: a topic-based systematic review.

Cimolato A, Driessen J, Mattos L, Momi E, Laffranchi M, De Michieli L J Neuroeng Rehabil. 2022; 19(1):43.

PMID: 35526003 PMC: 9077893. DOI: 10.1186/s12984-022-01019-1.

References

Vukobratovic M, Hristic D, Stojiljkovic Z . Development of active anthropomorphic exoskeletons. Med Biol Eng. 1974; 12(1):66-80. DOI: 10.1007/BF02629836. View

Huang H, Kuiken T, Lipschutz R . A strategy for identifying locomotion modes using surface electromyography. IEEE Trans Biomed Eng. 2009; 56(1):65-73. PMC: 3025288. DOI: 10.1109/TBME.2008.2003293. View

Au S, Berniker M, Herr H . Powered ankle-foot prosthesis to assist level-ground and stair-descent gaits. Neural Netw. 2008; 21(4):654-66. DOI: 10.1016/j.neunet.2008.03.006. View

Patla A, Vickers J . How far ahead do we look when required to step on specific locations in the travel path during locomotion?. Exp Brain Res. 2002; 148(1):133-8. DOI: 10.1007/s00221-002-1246-y. View

Zhang F, Fang Z, Liu M, Huang H . Preliminary design of a terrain recognition system. Annu Int Conf IEEE Eng Med Biol Soc. 2012; 2011:5452-5. PMC: 3718465. DOI: 10.1109/IEMBS.2011.6091391. View

Martinez-Villalpando E, Herr H . Agonist-antagonist active knee prosthesis: a preliminary study in level-ground walking. J Rehabil Res Dev. 2009; 46(3):361-73. View

Englehart K, Hudgins B . A robust, real-time control scheme for multifunction myoelectric control. IEEE Trans Biomed Eng. 2003; 50(7):848-54. DOI: 10.1109/TBME.2003.813539. View

Sup F, Varol H, Mitchell J, Withrow T, Goldfarb M . Preliminary Evaluations of a Self-Contained Anthropomorphic Transfemoral Prosthesis. IEEE ASME Trans Mechatron. 2010; 14(6):667-676. PMC: 2801882. DOI: 10.1109/TMECH.2009.2032688. View

Farris R, Quintero H, Goldfarb M . Preliminary evaluation of a powered lower limb orthosis to aid walking in paraplegic individuals. IEEE Trans Neural Syst Rehabil Eng. 2011; 19(6):652-9. PMC: 3367884. DOI: 10.1109/TNSRE.2011.2163083. View

10.

Gordon K, Ferris D . Learning to walk with a robotic ankle exoskeleton. J Biomech. 2007; 40(12):2636-44. DOI: 10.1016/j.jbiomech.2006.12.006. View

11.

Hudgins B, Parker P, Scott R . A new strategy for multifunction myoelectric control. IEEE Trans Biomed Eng. 1993; 40(1):82-94. DOI: 10.1109/10.204774. View

12.

Huang H, Zhang F, Hargrove L, Dou Z, Rogers D, Englehart K . Continuous locomotion-mode identification for prosthetic legs based on neuromuscular-mechanical fusion. IEEE Trans Biomed Eng. 2011; 58(10):2867-75. PMC: 3235670. DOI: 10.1109/TBME.2011.2161671. View

13.

Ha K, Varol H, Goldfarb M . Volitional control of a prosthetic knee using surface electromyography. IEEE Trans Biomed Eng. 2010; 58(1):144-51. DOI: 10.1109/TBME.2010.2070840. View

14.

Varol H, Sup F, Goldfarb M . Multiclass real-time intent recognition of a powered lower limb prosthesis. IEEE Trans Biomed Eng. 2009; 57(3):542-51. PMC: 2829115. DOI: 10.1109/TBME.2009.2034734. View

15.

Zhang F, Liu M, Huang H . Preliminary study of the effect of user intent recognition errors on volitional control of powered lower limb prostheses. Annu Int Conf IEEE Eng Med Biol Soc. 2013; 2012:2768-71. PMC: 3686281. DOI: 10.1109/EMBC.2012.6346538. View

16.

Wilkinson E, Sherk H . The use of visual information for planning accurate steps in a cluttered environment. Behav Brain Res. 2005; 164(2):270-4. DOI: 10.1016/j.bbr.2005.06.023. View

17.

Hargrove L, Simon A, Lipschutz R, Finucane S, Kuiken T . Real-time myoelectric control of knee and ankle motions for transfemoral amputees. JAMA. 2011; 305(15):1542-4. DOI: 10.1001/jama.2011.465. View