In-socket sensory system with an adaptive neuro-based fuzzy inference system for active transfemoral prosthetic legs

Yusof, Nur Hidayah Mohd; Hamzaid, Nur Azah; Jasni, Farahiyah; Lai, Khin Wee

doi:10.1117/1.jei.28.2.021002

Cited by 2 publications

(3 citation statements)

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“…Therefore, this study indicated the reliability and compactness of advanced optimization methods for locomotion mode detection implemented in active prosthetic legs. Yusof et al (Yusof et al, 2018) proposed user gait mode recognition based on seven phases of classi cation from the in-socket sensory system that allows one to mimic a normal healthy walking gait. The purpose of the in-socket sensory system was to derive the user's intention to actively actuate the knee and thus reduce the user's metabolic energy consumption.…”

Section: Locomotion Mode Recognition Strategymentioning

confidence: 99%

“…The mechanism of the sensory system can be addressed using a wide range of approaches and varying degrees of invasiveness. Generally, two types of sensory systems have been adopted for user intention detection: prosthetic device-oriented (Sup et al, 2008b;Sup et al, 2007a;Varol et al, 2010;Yusof et al, 2018) and biologicaloriented (Furuya et al, 2013;Alzaydi et al, 2011;Bai et al, 2016).…”

Section: Sensors In Transfemoral Prosthesis For Intention Detectionmentioning

confidence: 99%

“…Simulation studies have also been used as one method to assess the behavior of prosthetic legs. Yusof et al (Yusof et al, 2018) used this method to validate a control algorithm for an active prosthetic leg. The purpose of using physical simulation is to estimate the dynamic behavior of the system and simulate the movement of the prosthetic leg.…”

Section: Performance Assessmentmentioning

confidence: 99%

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Control Interfaces for Intention Detection in Active Transfemoral Prosthetics: A Systematic Review

Yusof

Hamzaid

Wee

et al. 2023

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In this paper, a cutting-edge method for creating control interfaces for intention detection in active transfemoral prosthetic devices is presented. Given the current trend in the prosthetics industry, a review of the literature over the last two decades has found a number of control algorithms utilized for intention detection implementation. Scientific publications, books, and online resources were evaluated for published material on knee prosthesis. Based on the materials, three areas of scientific inquiry involving control interfaces for intention detection in active prosthetic legs have been identified. The studies were assessed using the Downs and Black checklist, and their control techniques as well as the performance assessment for these control interfaces are described. After screening, 211 studies were retrieved and examined, however only 39 publications were included and examined in this review. An active prosthetic leg's control strategy framework and goal output were examined in fifteen (15) papers. In two (2) papers, conventional control methods for transfemoral prosthetic legs were examined. Eight (8) further research looked at the potential implementation of intent detection in the transfemoral prosthetic leg, while fourteen (14) papers explored the active prosthetic leg's machine learning algorithm. As a result, our research showed that using a less complex sensory system to control an active transfemoral prosthetic limb is possible when paired with a creative approach and control algorithm that can translate the restricted sensor data into a larger set of relevant data. Therefore, an effective sensory system (practicality and quality of the sensory input) and intention detection algorithm were required for an active transfemoral prosthetic limb. It is considered a complex activity because of the connected biomechanics of human gait, which the brain governs unconsciously. No prosthetic device has been able to replace a human limb in the same way that the original one would operate due to the ongoing challenges in prosthetic technology. Even with something as simple as walking, there are several components to the difficulty that may be broken down into different study areas. No matter how little, this calls for input from many different domains of knowledge. Considerations for future development might be based on this current analysis of the intention-detecting control interface of active knee prosthetic devices and prosthetic technology. This evaluation of the literature includes not only a study of the viability of control interfaces that support intention detection for an active prosthetic limb, but it also suggests a framework for categorizing various works in the subject.

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Section: Locomotion Mode Recognition Strategymentioning

confidence: 99%