<p>This paper reviews the latest methods for creating control interfaces for intention detection in active transfemoral prosthetic devices. A literature review over the past two decades identified several control algorithms for intention detection. Sources included scientific publications, books, and online resources focusing on knee prostheses. Three main areas of research were identified. The studies were assessed using the Downs and Black checklist, detailing their control techniques and performance assessments. Initially, 213 studies were retrieved; 33 were selected for this review. Fifteen (15) papers examined control strategy frameworks and goal outputs of active prosthetic legs. Two (2) papers discussed conventional control methods for transfemoral prosthetic legs. Four (4) studies explored potential implementations of intention detection, and twelve (12) papers investigated machine learning algorithms for active prosthetic legs. The review suggests using a simpler sensory system paired with innovative control algorithms to translate limited sensor data into a broader set of relevant information. Effective sensory systems and intention detection algorithms are crucial for active transfemoral prosthetic limbs. This review presents the feasibility of control interfaces that enable intention detection for active prosthetic legs, offering multiple references and classifying different works in the field.</p>

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Control interfaces for intention detection in active transfemoral prosthetics: a systematic review

  • Nur Hidayah Mohd Yusof,
  • Nur Azah Hamzaid,
  • Khin Wee Lai,
  • Farahiyah Jasni,
  • Fanny Oddon

摘要

This paper reviews the latest methods for creating control interfaces for intention detection in active transfemoral prosthetic devices. A literature review over the past two decades identified several control algorithms for intention detection. Sources included scientific publications, books, and online resources focusing on knee prostheses. Three main areas of research were identified. The studies were assessed using the Downs and Black checklist, detailing their control techniques and performance assessments. Initially, 213 studies were retrieved; 33 were selected for this review. Fifteen (15) papers examined control strategy frameworks and goal outputs of active prosthetic legs. Two (2) papers discussed conventional control methods for transfemoral prosthetic legs. Four (4) studies explored potential implementations of intention detection, and twelve (12) papers investigated machine learning algorithms for active prosthetic legs. The review suggests using a simpler sensory system paired with innovative control algorithms to translate limited sensor data into a broader set of relevant information. Effective sensory systems and intention detection algorithms are crucial for active transfemoral prosthetic limbs. This review presents the feasibility of control interfaces that enable intention detection for active prosthetic legs, offering multiple references and classifying different works in the field.