Evidence map›Paper›PMID 42343330›Full record

ArticleJournal of neuroengineering and rehabilitation2026

Intention-driven functional electrical stimulation therapy using a wearable high-density electrode sleeve in chronic stroke: a case report.

Ian W Baumgart, Michael J Darrow, Nicholas J Tacca, Collin F Dunlap, Samuel C Colachis, Ashwini Kamath, Bryan R Schlink, Philip T Putnam, Joshua Branch, David A Friedenberg and 2 more

Registry-linked trialAbstract readCase Reports
In one paragraph

Article in Journal of neuroengineering and rehabilitation, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT06207240 (Efficacy and Feasibility of Using the NeuroLife Sleeve System to Improve Hand Function in Stroke Survivors), which is not on this map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from 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.

2 · The registry

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.

NCT06207240 nacompletednot on this map

Efficacy and Feasibility of Using the NeuroLife Sleeve System to Improve Hand Function in Stroke Survivors

TypeinterventionalSponsorBattelle Memorial InstituteRan2022 to 2022Enrolled2ConditionsStrokeArmsNeuroLife FES Sleeve / NeuroLife EMG-FES Sleeve
3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors.

Ian W BaumgartNeurotechnology, Battelle Memorial Institute, Columbus, USA.
Michael J DarrowNeurotechnology, Battelle Memorial Institute, Columbus, USA.
Nicholas J TaccaNeurotechnology, Battelle Memorial Institute, Columbus, USA.
Collin F DunlapNeurotechnology, Battelle Memorial Institute, Columbus, USA.
Samuel C ColachisNeurotechnology, Battelle Memorial Institute, Columbus, USA.
Ashwini KamathNeurotechnology, Battelle Memorial Institute, Columbus, USA.
Bryan R SchlinkNeurotechnology, Battelle Memorial Institute, Columbus, USA.
Philip T PutnamNeurotechnology, Battelle Memorial Institute, Columbus, USA.
Joshua BranchNeurotechnology, Battelle Memorial Institute, Columbus, USA.
David A FriedenbergNeurotechnology, Battelle Memorial Institute, Columbus, USA.
Lauren R WengerdNeurotechnology, Battelle Memorial Institute, Columbus, USA.
Eric C MeyersNeurotechnology, Battelle Memorial Institute, Columbus, USA. eric.meyers@utdallas.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundFunctional electrical stimulation (FES) has been recognized for decades as a method to retrain the motor system after stroke. Benefits of FES rehabilitation can be enhanced by (1) combining FES with task-oriented therapy (i.e. FES therapy (FEST)), (2) timing FES with the user's volitional motor intention and (3) incorporating multiple trained tasks, as opposed to high repetitions of single tasks. Using a novel wearable FES technology, we tested therapy incorporating these elements in two chronic stroke survivors.

methodsOur group has developed the NeuroLife Sleeve, a wearable forearm sleeve that contains a high-density grid of embedded FES electrodes, that may be controlled by an operator or by the wearer's own electromyographic (EMG) signals. The system enables rapid software-based switching between stimulation configurations for different functional movements without repeated electrode repositioning. During eight weeks of FEST, intention-driven FES enabling multiple movements was delivered via operator control twice weekly and EMG control once weekly.

resultsAt the end of the therapy period, subjects A and B had both improved their scores: Box and Blocks Test (A: +5, B: +7), the Action Research Arm Test (A: +7, B: +12), the Fugl Meyer Upper Extremity section (A: +11, B: +9), and the 9-Hole Peg Test (A: 158 s, B: 54 s, both previously unable). Clinical improvements persisted during the 10-week follow-up period, during which FES exposure was reduced by more than 80%.

conclusionsThis case report provides a proof-of-concept demonstration of the NeuroLife Sleeve to support FEST and preliminary evidence that intention-driven FEST may support motor recovery in chronic stroke survivors. The NeuroLife Sleeve is a novel device designed to deliver this therapy through the easily donned wearable sleeve interface, support for both operator-triggered and EMG-controlled FES paradigms, and efficient transitions between tasks with programmable FES placement and parameters. Because both control modes were used throughout the intervention, the relative therapeutic contribution of each cannot be distinguished.

trial registrationWe retrospectively registered the trial with ClinicalTrials.gov (16/01/2024, NCT06207240).

Indexed as

Electric Stimulation TherapyIntentionStrokeStroke RehabilitationWearable Electronic DevicesAgedChronic DiseaseElectrodesElectromyographyFemaleHumansMaleMiddle AgedElectromyography-driven electrical stimulation.Functional electrical stimulation therapyIntention-driven electrical stimulation

Identifiers

PMID42343330
PMCPMC13551793

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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.