ReviewBiomimetics (Basel, Switzerland)2023
A Review of Myoelectric Control for Prosthetic Hand Manipulation.
Review in Biomimetics (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 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
18 citing papers in PubMed.
- A Scalogram Image-Based Method for Continuous Estimation of Hand Kinematics from Surface Electromyography.Annals of biomedical engineering · 2026Article
- Upper limb compensatory strategies across tasks with an ultrasound-controlled prosthesis.Scientific reports · 2026Article
- Upper limb prostheses: a narrative review of hand, wrist, and elbow devices.Frontiers in rehabilitation sciences · 2026Review
- Active Rehabilitation Technologies for Post-Stroke Patients.Biosensors · 2025Review
- Skin-Integrated Soft Wearable XR Interfaces for Seamless and Realistic User Experience.Chemical reviews · 2025Review
- Upper Limb Motor Function Rehabilitation System Leveraging Pressure-Sensitive Intent Recognition.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- A Highly Efficient HMI Algorithm for Controlling a Multi-Degree-of-Freedom Prosthetic Hand Using Sonomyography.Sensors (Basel, Switzerland) · 2025Article
- Article
- Investigating the Feasibility and Safety of Osseointegration With Neural Interfaces for Advanced Prosthetic Control.Cureus · 2025Review
- Advances in HD-EMG interfaces and spatial algorithms for upper limb prosthetic control.Frontiers in neuroscience · 2025Review
- Gaussian process latent variable models-ANN based method for automatic features selection and dimensionality reduction for control of EMG-driven systems.Frontiers in artificial intelligence · 2025Article
- Biomimetic Strategies of Slip Sensing, Perception, and Protection in Prosthetic Hand Grasp.Biomimetics (Basel, Switzerland) · 2024Article
- Continuous reach-to-grasp motion recognition based on an extreme learning machine algorithm using sEMG signals.Physical and engineering sciences in medicine · 2024Article
- Unravelling Influence Factors in Pattern Recognition Myoelectric Control Systems: The Impact of Limb Positions and Electrode Shifts.Sensors (Basel, Switzerland) · 2024Article
- Simultaneous Three-Degrees-of-Freedom Prosthetic Control Based on Linear Regression and Closed-Loop Training Protocol.Sensors (Basel, Switzerland) · 2024Article
- Shoulder Movement-Centered Measurement and Estimation Scheme for Underarm-Throwing Motions.Sensors (Basel, Switzerland) · 2024Article
- Machine learning for hand pose classification from phasic and tonic EMG signals during bimanual activities in virtual reality.Frontiers in neuroscience · 2024Article
- Multi-branch deep learning neural network prediction model for the development of angular biosensors based on sEMG.Frontiers in bioengineering and biotechnology · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
Myoelectric control for prosthetic hands is an important topic in the field of rehabilitation. Intuitive and intelligent myoelectric control can help amputees to regain upper limb function. However, current research efforts are primarily focused on developing rich myoelectric classifiers and biomimetic control methods, limiting prosthetic hand manipulation to simple grasping and releasing tasks, while rarely exploring complex daily tasks. In this article, we conduct a systematic review of recent achievements in two areas, namely, intention recognition research and control strategy research. Specifically, we focus on advanced methods for motion intention types, discrete motion classification, continuous motion estimation, unidirectional control, feedback control, and shared control. In addition, based on the above review, we analyze the challenges and opportunities for research directions of functionality-augmented prosthetic hands and user burden reduction, which can help overcome the limitations of current myoelectric control research and provide development prospects for future research.
Indexed as
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.