Evidence map›Paper›PMID 39767709›Full record

ReviewBiomedicines2024

Haptic Technology: Exploring Its Underexplored Clinical Applications-A Systematic Review.

Kevin Pacheco-Barrios, Jorge Ortega-Márquez, Felipe Fregni

Registry-linked trialAbstract readReview
In one paragraph

Review in Biomedicines, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT07077460 (Innovative Hand Rehabilitation System With Synchronized Contralateral Haptic Feedback), which is not on this map. Cited by 11 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 1 pooled it
–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.

NCT07077460 narecruitingnot on this map

Innovative Hand Rehabilitation System With Synchronized Contralateral Haptic Feedback

TypeinterventionalSponsorNational Cheng-Kung University HospitalRan2024 to 2025Enrolled100ConditionsHealthy ElderlyArmsTIPr, Mirror Visual Feedback Device, Mirror Visual Feedback Device(Blocked mirror), Graded-Pressure Haptic Device (Passive press-feedback cushion)
3 · Its place in the literature

Who cites it

11 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Review
  4. Review
  5. Article
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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

3 authors.

Kevin Pacheco-BarriosNeuromodulation Center and Center for Clinical Research Learning, Spaulding Rehabilitation Hospital and Massachusetts General Hospital, Harvard Medical School, Boston, MA 02115, USA.
Jorge Ortega-MárquezNeuromodulation Center and Center for Clinical Research Learning, Spaulding Rehabilitation Hospital and Massachusetts General Hospital, Harvard Medical School, Boston, MA 02115, USA.
Felipe FregniNeuromodulation Center and Center for Clinical Research Learning, Spaulding Rehabilitation Hospital and Massachusetts General Hospital, Harvard Medical School, Boston, MA 02115, USA.ORCID 0000-0002-1703-7526

Funding

Pragmatic Trial of Remote tDCS and Somatosensory Training for Phantom Limb Pain with Machine Learning to Predict Treatment ResponseR01HD082302 · NICHD · SPAULDING REHABILITATION HOSPITAL · PI Felipe Fregni · 2015 to 2026
$4.7M
Mechanisms of Open and Hidden Placebo in Stroke RecoveryR21NS131635 · NINDS · SPAULDING REHABILITATION HOSPITAL · PI FREGNI, FELIPE · 2023 to 2024
$490k
NICHD NIH HHS R01 HD082302NIH HHS 5R21NS131635-02 and 5R01HD082302-08NINDS NIH HHS R21 NS131635
6 · The paper itself

Abstract

BACKGROUND/

objectivesHaptic technology has transformed interactions between humans and both tangible and virtual environments. Despite its widespread adoption across various industries, the potential therapeutic applications of this technology have yet to be fully explored.

methodsA systematic review of randomized controlled trials (RCTs) and randomized crossover trials was conducted, utilizing databases such as PubMed, Embase, Cochrane Library, and Web of Science. This review included studies reporting clinical applications of haptic technology in rehabilitation, cognition, wellness, and mental health among adult subjects.

resultsThis systematic review included 34 studies, of which 20 focused on clinical outcomes and 14 on learning clinical skills. The results showed that haptic devices, both robotic and non-robotic, enhance sensorimotor performance and motor function in rehabilitation settings, especially in post-stroke recovery, with reported effect sizes ranging from 0.2 to 0.7. The majority of the haptic technologies reported were integrated into robotic systems (40%). Haptic devices were also reported to improve clinical skills training by providing tactile feedback that enhances procedural performance and trainee self-efficacy. In fact, surgical simulations accounted for 79% of all the modalities used for medical training.

conclusionsThis review underscores the potential yet underexplored applications of haptic technology in healthcare, including medical education, rehabilitation, cognition, and mental health. The key limitations of this review include heterogeneity across studies, small sample sizes, and a scarcity of comprehensive, long-term investigations. Therefore, future research should aim to validate these findings further and expand the applications of haptic technology to maximize its utility in the healthcare industry and clinical practice.

Indexed as

cognitionhapticshaptic technologyhaptic trainingmedical devicesmedical innovationmental healthmultisensory training systemsrehabilitation

Identifiers

PMID39767709
PMCPMC11673350

What OpenQuestion holds

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LicenceCC BY
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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.