Authors:
J. C. Moreno
1
;
J. L. Pons
2
;
E. Rocon
2
and
Y. Demiris
3
Affiliations:
1
Bioengineering Group, Industrial Automation Institute, the Spanish National Research Council (CSIC); Technaid S.L., Spain
;
2
Bioengineering Group, Industrial Automation Institute, the Spanish National Research Council (CSIC), Spain
;
3
Intelligent Systems and Networks Group, Imperial College London, United Kingdom
Keyword(s):
Fuzzy inference systems, non-linear oscillators, inertial sensing, gait compensation.
Related
Ontology
Subjects/Areas/Topics:
Applications and Services
;
Artificial Intelligence
;
Biomedical Engineering
;
Biomedical Signal Processing
;
Computer Vision, Visualization and Computer Graphics
;
Cybernetics and User Interface Technologies
;
Data Manipulation
;
Devices
;
Health Engineering and Technology Applications
;
Health Information Systems
;
Human-Computer Interaction
;
Information and Systems Security
;
Medical Image Detection, Acquisition, Analysis and Processing
;
Methodologies and Methods
;
Neurocomputing
;
Neurotechnology, Electronics and Informatics
;
Pattern Recognition
;
Physiological Computing Systems
;
Sensor Networks
;
Soft Computing
;
Wearable Sensors and Systems
Abstract:
Robust generation of motor commands for real-time control of locomotion with artificial means is crucial for human safety. This paper addresses the combination of fuzzy inference for determination of rules with a non linear oscillator system, as generators of motor commands for the control of human leg joints during walking, by means of external gait compensators, e.g. exoskeletons, functional electrical stimulation or hybrid systems. The response of the proposed method is evaluated for variations in stride frequency and step length. The testing during gait conditions is performed considering inertial sensing as feedback in a simulation study. The reference data considered is obtained in multiple experiments with healthy subjects walking with a controllable exoskeleton designed to compensate quadriceps weakness. A model of the operation of the knee joint compensation provided by the exoskeleton is obtained as reference to evaluate the method based on real data. The results demonstrat
e the benefits of both incorporating a) the fuzzy inference system in cyclical decision making for generation of motor commands and b) the dynamic adaptation of the timing parameters of the external compensator provided by the van der Pol oscillator.
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