Evidence map›Paper›PMID 41171373›Full record

SynthesisPhysical and engineering sciences in medicine2025

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

Abstract readSystematic Review
PubMed Publisher
In one paragraph

Synthesis in Physical and engineering sciences in medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Nur Hidayah Mohd YusofBiomechatronics and Neuroprosthetics Laboratory, Department of Biomedical Engineering, Faculty of Engineering, Universiti Malaya, 50603, Kuala Lumpur, Malaysia.
Nur Azah HamzaidBiomechatronics and Neuroprosthetics Laboratory, Department of Biomedical Engineering, Faculty of Engineering, Universiti Malaya, 50603, Kuala Lumpur, Malaysia. azah.hamzaid@um.edu.my.ORCID http://orcid.org/0000-0002-4277-2813
Khin Wee LaiDepartment of Biomedical Engineering, Faculty of Engineering, Universiti Malaya, Kuala Lumpur, Malaysia.
Farahiyah JasniMechatronics Engineering Department, Kulliyyah of Engineering, International Islamic University Malaysia, Kuala Lumpur, Malaysia.
Fanny OddonMechanic & Interactive Design, Engineering School, Polytech Montpellier, Campus Triolet, 34000, Montpellier, France.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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.

Indexed as

Artificial LimbsAlgorithmsFemurHumansMachine LearningActive prosthetic deviceControl algorithmIntent recognitionSensory systemUser-intention

Identifiers

PMID41171373

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.