ReviewJournal of neuroengineering and rehabilitation2014
Non-invasive control interfaces for intention detection in active movement-assistive devices.
Review in Journal of neuroengineering and rehabilitation, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers, 3 of them syntheses that pooled 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.
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
32 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- Control interfaces for intention detection in active transfemoral prosthetics: a systematic review.Physical and engineering sciences in medicine · 2025Pooled it
- Intention Prediction for Active Upper-Limb Exoskeletons in Industrial Applications: A Systematic Literature Review.Sensors (Basel, Switzerland) · 2025Pooled it
- A survey of human shoulder functional kinematic representations.Medical & biological engineering & computing · 2019Pooled it
- Hands-free control of an assistive robotic arm for high-level paralysis.Journal of neuroengineering and rehabilitation · 2026Article
- An identification method of human joint interaction torque based on discrete EMG signals.Frontiers in bioengineering and biotechnology · 2025Article
- A usability study on mobile EMG-guided wrist extension training in subacute stroke patients-MyoGuide.Journal of neuroengineering and rehabilitation · 2024Article
- Novel neuromuscular controllers with simplified muscle model and enhanced reflex modulation: A comparative study in hip exoskeletons.Wearable technologies · 2024Article
- Development and evaluation of a soft pneumatic muscle for elbow joint rehabilitation.Frontiers in bioengineering and biotechnology · 2024Article
- Hybrid brain/neural interface and autonomous vision-guided whole-arm exoskeleton control to perform activities of daily living (ADLs).Journal of neuroengineering and rehabilitation · 2023Article
- Development of a Wearable Ultrasound Transducer for Sensing Muscle Activities in Assistive Robotics Applications.Biosensors · 2023Article
- Peripheral Nervous System Interfaces: Invasive or Non-invasive?Frontiers in neurorobotics · 2022Article
- A deep learning method to predict ankle joint moment during walking at different speeds with ultrasound imaging: A framework for assistive devices control.Wearable technologies · 2022Article
- Intention Detection Strategies for Robotic Upper-Limb Orthoses: A Scoping Review Considering Usability, Daily Life Application, and User Evaluation.Frontiers in neurorobotics · 2022Article
- Rethinking Autonomous Surgery: Focusing on Enhancement over Autonomy.European urology focus · 2021Review
- A low-cost transradial prosthesis controlled by the intention of muscular contraction.Physical and engineering sciences in medicine · 2021Article
- Biosignal Sensors and Deep Learning-Based Speech Recognition: A Review.Sensors (Basel, Switzerland) · 2021Review
- Elbow Motion Trajectory Prediction Using a Multi-Modal Wearable System: A Comparative Analysis of Machine Learning Techniques.Sensors (Basel, Switzerland) · 2021Article
- Human-Robot Interaction With Robust Prediction of Movement Intention Surpasses Manual Control.Frontiers in neurorobotics · 2021Article
- Validity and Reliability of Surface Electromyography Features in Lower Extremity Muscle Contraction in Healthy and Spinal Cord-Injured Participants.Topics in spinal cord injury rehabilitation · 2021Article
- Performance Analysis of a Head and Eye Motion-Based Control Interface for Assistive Robots.Sensors (Basel, Switzerland) · 2020Article
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
No grant is acknowledged in the PubMed record.
Abstract
Active movement-assistive devices aim to increase the quality of life for patients with neuromusculoskeletal disorders. This technology requires interaction between the user and the device through a control interface that detects the user's movement intention. Researchers have explored a wide variety of invasive and non-invasive control interfaces. To summarize the wide spectrum of strategies, this paper presents a comprehensive review focused on non-invasive control interfaces used to operate active movement-assistive devices. A novel systematic classification method is proposed to categorize the control interfaces based on: (I) the source of the physiological signal, (II) the physiological phenomena responsible for generating the signal, and (III) the sensors used to measure the physiological signal. The proposed classification method can successfully categorize all the existing control interfaces providing a comprehensive overview of the state of the art. Each sensing modality is briefly described in the body of the paper following the same structure used in the classification method. Furthermore, we discuss several design considerations, challenges, and future directions of non-invasive control interfaces for active movement-assistive devices.
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.