Evidence map›Paper›PMID 40545503›Full record

SynthesisJournal of medical systems2025

Enhancing Surgical Precision: A Systematic Review of Wearable Medical Devices for Assisted Surgery.

Houneida Sakly, Ramzi Guetari, Naoufel Kraiem, Nada Abdulaziz Alasbali, Ali Algarni

Erratum issuedAbstract readSystematic Review
PubMed Publisher
In one paragraph

Synthesis in Journal of medical systems, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors.

Houneida SaklyCenter for Research on Microelectronics and Nanotechnology (CRMN), Technopole, Sahloul Sousse, Tunisia. Houneida.sakly@esiee.fr.
Ramzi GuetariSERCOM Laboratory, Polytechnic School of Tunisia, University of Carthage, La Marsa, 2078, Tunisia.
Naoufel KraiemCollege of Computer Science, King Khalid University, Abha, 61413, Saudi Arabia.
Nada Abdulaziz AlasbaliCollege of Computer Science, King Khalid University, Abha, 61413, Saudi Arabia.
Ali AlgarniCollege of Computer Science, King Khalid University, Abha, 61413, Saudi Arabia.

Funding

Deanship of Scientific Research, King Khalid University RGP2/428/46
6 · The paper itself

Abstract

The integration of wearable medical devices into surgical practice has transformed the field, enabling enhanced precision, informed decision-making, and improved patient outcomes. These devices, which include biosensors and augmented reality (AR) headsets, continuously collect and provide real-time data to support surgeons during complex procedures. A key advancement in this domain is the incorporation of artificial intelligence (AI), which enables these devices to analyze large datasets, generate predictive insights, and adapt to changing clinical scenarios, thus assisting in surgical decision-making. AI-driven analytics, combined with wearable technology, optimize surgical performance by detecting potential complications early and allowing for dynamic adjustments to surgical plans. However, widespread adoption faces challenges, including data privacy concerns, device interoperability issues, and regulatory compliance requirements. This paper presents a comprehensive review of wearable medical devices in surgery, examining their applications, limitations, and transformative role of AI in advancing surgical care. Additionally, the paper discusses strategies to overcome barriers, supporting the integration of these technologies into future surgical practices.

Indexed as

Artificial IntelligenceWearable Electronic DevicesAugmented RealityHumansAIAssisted SurgeryDiagnosisMedical DataMonitoringWearable Devices

Identifiers

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.