ReviewCyborg and bionic systems (Washington, D.C.)2021
Noninvasive Human-Prosthesis Interfaces for Locomotion Intent Recognition: A Review.
Review in Cyborg and bionic systems (Washington, D.C.), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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.
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.
Who cites it
16 citing papers in PubMed, 41 citations in OpenAlex.
- A Deep Learning Framework With Domain Generalization and Few-Shot Learning for Locomotion Mode Classification Across Users, Sessions, and Prostheses.IEEE transactions on medical robotics and bionics · 2026Article
- Electroencephalography Enables Continuous Decoding of Hand Motion Angles in Polar Coordinates.Cyborg and bionic systems (Washington, D.C.) · 2026Article
- Active Rehabilitation Technologies for Post-Stroke Patients.Biosensors · 2025Review
- Vibrotactile Haptic and Gesture Feedback in a Smartwatch for Controlling a Multi-Activity Powered Knee-Ankle Prosthesis.Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference · 2025Article
- Level-Ground and Stair Adaptation for Hip Exoskeletons Based on Continuous Locomotion Mode Perception.Cyborg and bionic systems (Washington, D.C.) · 2025Article
- Lateral Walking Gait Recognition and Hip Angle Prediction Using a Dual-Task Learning Framework.Cyborg and bionic systems (Washington, D.C.) · 2025Article
- Ambilateral Activity Recognition and Continuous Adaptation with a Powered Knee-Ankle Prosthesis.IEEE transactions on robotics : a publication of the IEEE Robotics and Automation Society · 2025Article
- Human factors considerations of Interaction between wearers and intelligent lower-limb prostheses: a prospective discussion.Journal of neuroengineering and rehabilitation · 2024Review
- Transfer Learning for Efficient Intent Prediction in Lower-Limb Prosthetics: A Strategy for Limited Datasets.IEEE robotics and automation letters · 2024Article
- EEGNet-based multi-source domain filter for BCI transfer learning.Medical & biological engineering & computing · 2024Article
- Controlling Powered Prosthesis Kinematics Over Continuous Inter-Leg Transitions Between Walking and Stair Ascent/Descent.IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society · 2024Article
- Adaptive Gait Training of a Lower Limb Rehabilitation Robot Based on Human-Robot Interaction Force Measurement.Cyborg and bionic systems (Washington, D.C.) · 2024Article
- Recent progress in three-terminal artificial synapses based on 2D materials: from mechanisms to applications.Microsystems & nanoengineering · 2023Review
- Time-Varying Functional Connectivity of Rat Brain during Bipedal Walking on Unexpected Terrain.Cyborg and bionic systems (Washington, D.C.) · 2023Article
- Predictive neuromodulation of cingulo-frontal neural dynamics in major depressive disorder using a brain-computer interface system: A simulation study.Frontiers in computational neuroscience · 2023Article
- Characterizing Prosthesis Control Fault during Human-Prosthesis Interactive Walking Using Intrinsic Sensors.IEEE robotics and automation letters · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 1 institution in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The lower-limb robotic prostheses can provide assistance for amputees' daily activities by restoring the biomechanical functions of missing limb(s). To set proper control strategies and develop the corresponding controller for robotic prosthesis, a prosthesis user's intent must be acquired in time, which is still a major challenge and has attracted intensive attentions. This work focuses on the robotic prosthesis user's locomotion intent recognition based on the noninvasive sensing methods from the recognition task perspective (locomotion mode recognition, gait event detection, and continuous gait phase estimation) and reviews the state-of-the-art intent recognition techniques in a lower-limb prosthesis scope. The current research status, including recognition approach, progress, challenges, and future prospects in the human's intent recognition, has been reviewed. In particular for the recognition approach, the paper analyzes the recent studies and discusses the role of each element in locomotion intent recognition. This work summarizes the existing research results and problems and contributes a general framework for the intent recognition based on lower-limb prosthesis.
Identifiers
What OpenQuestion holds
Registered trials
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.