Abstract
This paper outlines sensory system specifications and requirements to measure lower limb inclination angles, and addresses a novel method of human gait phase recognition necessary for cadence control. The implementation of a wireless system to transfer data between the active prosthetic knee and a healthy leg is discussed. A control mechanism is developed that takes advantage of an adaptive-network-based fuzzy inference system (FIS) to determine knee torque as a function of the echoing angular state of the able leg. The FIS membership function parameters and rules define the knowledge-base of the system. This knowledge is based on existing experience and known facts about the walking cycle. The RMS error of the testing data for the body-mass-normalized knee torque and the knee angle were calculated as 0.1269 (N m/kg) and 3.2784 (degree), respectively, i.e., 14.16% with respect to the required range of 0.896 (N m/kg), and 5.10% with respect to the travelling range of 73.01 (degree). The introduced post processing block plays a significant role in reducing the magnitude of the aforementioned errors.
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Abbreviations
- APK:
-
Active prosthetic knee
- FIS:
-
Fuzzy inference systems
- TSK:
-
Takagi Sugeno Kang
- ANFIS:
-
Adaptive-network-based fuzzy inference system
- ADC:
-
Analog to digital converter
- DAC:
-
Digital to analog converter
- PID:
-
Proportional–integral–derivative
References
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Acknowledgments
The authors would like to acknowledge the contributions of fourth-year undergraduate students, Alex Yakub, Daniel Charbonneau, Rob Espiritusanto, and Saad Mazahir
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Borjian, R., Khamesee, M.B. & Melek, W. Feasibility study on echo control of a prosthetic knee: sensors and wireless communication. Microsyst Technol 16, 257–265 (2010). https://doi.org/10.1007/s00542-009-0853-y
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DOI: https://doi.org/10.1007/s00542-009-0853-y