ReviewCureus2026
Comparative Evaluation of Myography Techniques for Prosthetic Hand Control.
Review in Cureus, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This review evaluates electromyography (EMG), force myography (FMG), sonomyography (SMG), and optical myography (OMG) for prosthetic hand control, comparing the modalities across signal propagation, signal accuracy, noise resistance, real-time processing, suitability for prosthetic control, and relative cost and system complexity. Upper limb loss affects a substantial and growing population worldwide, yet prosthesis abandonment remains common, in part because of limitations in control, functionality, and intuitive operation. Surface EMG is the most clinically established modality and supports real-time control, but its performance can be affected by noise, electrode-related factors, and reduced classification stability across recording sessions. FMG, including optical fiber implementations, has demonstrated high gesture classification performance in controlled studies and offers resistance to electromagnetic interference together with relatively simple signal processing; however, reported results vary according to sensor configuration, task, participant population, and validation method. SMG provides access to deformation of both superficial and deeper muscle structures but is limited by transducer position sensitivity and comparatively greater acquisition and processing requirements. OMG provides a noninvasive optical approach, with near-infrared implementations showing potential for wearable sensing, although evidence for long-term prosthetic hand control remains limited. Because the available studies differ substantially in participant populations, gesture sets, sensing configurations, classification algorithms, and validation procedures, their reported performance values cannot be interpreted as direct head-to-head comparisons. Among the approaches reviewed, optical fiber FMG is a promising option for portable prosthetic hand control under the conditions evaluated in existing studies, although current evidence does not establish a universally superior modality.
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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.