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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Vydáno v:	IEEE/ASME transactions on mechatronics Ročník 20; číslo 2; s. 618 - 630
Hlavní autoři:	Yuan, Kebin, Wang, Qining, Wang, Long
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	New York IEEE 01.04.2015 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:	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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Abstract	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.
AbstractList	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 [Formula Omitted] 0.02 ms (mean [Formula Omitted] 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%[Formula Omitted] 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% [Formula Omitted] 3.46% of one gait cycle. 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. 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 plus or minus 0.02 ms (mean plus or minus 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% plus or minus 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% plus or minus 3.46% of one gait cycle.
Author	Wang, Long Wang, Qining Yuan, Kebin
Author_xml	– sequence: 1 givenname: Kebin surname: Yuan fullname: Yuan, Kebin email: kebin.yuan@pku.edu.cn organization: Intelligent Control Laboratory, College of Engineering, Peking University, Beijing, China – sequence: 2 givenname: Qining surname: Wang fullname: Wang, Qining email: qiningwang@pku.edu.cn organization: Intelligent Control Laboratory, College of Engineering, Peking University, Beijing, China – sequence: 3 givenname: Long surname: Wang fullname: Wang, Long email: longwang@pku.edu.cn organization: Intelligent Control Laboratory, College of Engineering, Peking University, Beijing, China
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SubjectTerms	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
Title	Fuzzy-Logic-Based Terrain Identification with Multisensor Fusion for Transtibial Amputees
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