ArticleIEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society2026
The Electronic Grip Gauge (EGG): Automated Assessment of Sensorimotor Hand Function Using an Instrumented Fragile Object.
Article in IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society, 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
10 authors.
Funding
Abstract
Hand dexterity assessments play a crucial role in informing the rehabilitative care of individuals with upper-limb hemiparesis. However, current assessments often struggle to evaluate the hand's ability to precisely control grip force, a skill vital for daily activities like handling fragile objects. Here we describe the design of the Electronic Grip Gauge (EGG), an adjustable-weight, instrumented "fragile" object that measures grip force, load force, acceleration, orientation, and relative position. Embedded sensors enable automatic segmentation and analysis of EGG transfers in various modes. In "Non-Fragile" mode, there is no break threshold; the EGG serves as an automated variant of the Box-and-Blocks test. In "Fragile" mode, the EGG simulates fragility by playing a "break" noise if grip force exceeds a set threshold, requiring grip control to prevent breaks. In "Fragile-Feedback" mode, audio-visual feedback is provided proportional to applied grip force to supplement potentially impaired tactile feedback. Demonstrating functionality, we evaluated sensorimotor differences between 26 hemiparetic and 26 age-matched healthy participants. In "Fragile" mode, paretic hands were significantly slower, applied excessive force, and broke the EGG more frequently than contralateral and healthy control hands. In "Fragile-Feedback" mode, a subset of paretic hands improved, transferring the EGG faster and/or with less force. This work demonstrates the EGG's utility in automatically quantifying sensorimotor deficits and that, for a subset of hemiparetic patients, audiovisual feedback could potentially coach and rehabilitate hand function. Collectively, this work showcases the EGG's potential as both an assessment and rehabilitation device for grip force control-a critical skill in hand therapy.
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.