ArticleFrontiers in neurology2026
Wearable robotic device for upper limb recovery and predictive algorithms to emPOWER the rehabilitation of stroke survivors: a protocol of safety and RCT study (POWER).
Article in Frontiers in neurology, 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
Introduction: Stroke remains a leading cause of long-term disability worldwide, with persistent upper limb (UL) impairment affecting approximately half of survivors. Robotic rehabilitation has shown efficacy comparable to conventional therapy, but most available devices are bulky, non-wearable, and limited to institutional settings. Wearable robotic solutions combined with artificial intelligence (AI) may overcome these barriers. The present protocol study will investigate the wearability and acceptance of a new soft, exosuit robotic device, the effect on the rehabilitation of paretic UL in stroke subjects and the role of AI for movement classification and actuation. Method: The study will be conducted in a single neurorehabilitation center and divided into 2 phases: phase A including 10 adult healthy subjects and 10 stroke survivors who will wear the experimental robot device. The usability and acceptance of device will be ascertained by System Usability Scale (SUS); User Experience Questionnaire (UEQ); Technology Assisted Rehabilitation Patient Perception Questionnaire (TARPP-Q) measures and will be considered successfully completed whether SUS and UEQ exceed 68 and 0.8 score, respectively. Phase B is a randomized controlled trial comparing wearable robotic rehabilitation with conventional therapy in stroke survivors. Neurological evaluation will be executed by the National Institutes of Health Stroke Scale (NIHSS). Functional evaluation will be quantified according to International Classification of Functioning, Disability and Health (ICF) domains by Fugl Meyer Assessment Scale-Upper extremity (FMA-UE); Motricity Index; modified Ashworth Scale; Numerical Rating Scale; Box & Block Test; Frenchay Activity Index. Functional measures will be taken at baseline, at 2 weeks, at 4 weeks, at discharge, and at follow-up, except FMA-UE. AI algorithms will be developed to automatically assess movement quality and predict assistance intensity. Discussion: The protocol tests a novel wearable device for the recovery of UL in stroke survivors overcoming the limitations of currently used robot equipment and promoting a new approach to rehabilitation outside the institutional setting. AI associated to robot rehabilitation could enhance the patient's recovery and open the way to novel therapeutic practices.
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.