Fuzzy-Logic-Based Terrain Identification with Multisensor Fusion for Transtibial Amputees

Terrain identification is essential for the control of robotic transtibial prostheses to realize smooth locomotion transitions. In this paper, we present a real-time fuzzy-logic-based terrain identification method with multisensor fusion. Five locomotion features, including the foot inclination angl...

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Veröffentlicht in:IEEE/ASME transactions on mechatronics Jg. 20; H. 2; S. 618 - 630
Hauptverfasser: Yuan, Kebin, Wang, Qining, Wang, Long
Format: Journal Article
Sprache:Englisch
Veröffentlicht: New York IEEE 01.04.2015
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:
Accuracy
Correlation
Foot
Fuzzy logic
Identification methods
Inclination angle
Legged locomotion
Locomotion
locomotion transitions
multisensor fusion
Prosthetics
Ramps
Real-time systems
Sensors
Strikes
Surgical implants
Terrain
terrain identification
transtibial prostheses
ISSN:1083-4435, 1941-014X
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Zusammenfassung:Terrain identification is essential for the control of robotic transtibial prostheses to realize smooth locomotion transitions. In this paper, we present a real-time fuzzy-logic-based terrain identification method with multisensor fusion. Five locomotion features, including the foot inclination angle at the first strike, the shank inclination angle at the first strike, foot strike sequence, the foot inclination angle at mid-stance, and the shank inclination angle at toe-off, are used to identify different terrains and terrain transitions. These features are measured by the fusion of two triaxis gyroscopes, two triaxis accelerometers, two force sensitive resistors, and a timer, which can be embedded into the prosthesis. Based on these features, a fuzzy-logic-based identification method is proposed to identify five terrains: level ground, stair ascent, stair descent, ramp ascent, and ramp descent. Moreover, a transition constraint function is developed to improve the identification performance. The execution time of the identification method is 0.79 ms ± 0.02 ms (mean ± standard error of mean) and continuous terrain identification results show that the method can be operated online in real time. The average identification accuracy of 98.74% ± 0.32% is obtained from experiments with six able-bodied and three amputee subjects during steady locomotion periods (no terrain transition). In locomotion transition periods, all the eight transitions we studied are correctly identified and the average identification delay is 9.06% ± 3.46% of one gait cycle.
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ISSN:1083-4435
1941-014X
DOI:10.1109/TMECH.2014.2309708