Evidence map›Paper›PMID 36904695›Full record

ArticleSensors (Basel, Switzerland)2023

Development and Demonstration of a Wireless Ultraviolet Sensing Network for Dose Monitoring and Operator Safety in Room Disinfection Applications.

Michael F Cullinan, Robert Scott, Joe Linogao, Hannah Bradwell, Leonie Cooper, Conor McGinn

Full text read
In one paragraph

Article in Sensors (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Impact of UV-C on material degradation: a scoping literature review.Antimicrobial stewardship & healthcare epidemiology : ASHE · 2025
    Review
  3. Review
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

6 authors.

Michael F CullinanAkara Robotics Ltd., D08 TCV4 Dublin, Ireland.ORCID 0000-0002-2716-1539
Robert ScottAkara Robotics Ltd., D08 TCV4 Dublin, Ireland.
Joe LinogaoDepartment of Mechanical and Manufacturing Engineering, Trinity College Dublin, D02 PN40 Dublin, Ireland.ORCID 0000-0003-3083-8181
Hannah BradwellFaculty of Health, University of Plymouth, Plymouth PL4 8AA, UK.ORCID 0000-0002-9103-1069
Leonie CooperFaculty of Health, University of Plymouth, Plymouth PL4 8AA, UK.ORCID 0000-0002-6382-5224
Conor McGinnAkara Robotics Ltd., D08 TCV4 Dublin, Ireland.ORCID 0000-0001-9019-6809

Funding

DIH-hero( Digital Innovation Hubs in Healthcare Robotics) 825003European Innovation Council Accelerator 190106381
6 · The paper itself

Abstract

The use of mobile ultraviolet-C (UV-C) disinfection devices for the decontamination of surfaces in hospitals and other settings has increased dramatically in recent years. The efficacy of these devices relies on the UV-C dose they deliver to surfaces. This dose is dependent on the room layout, the shadowing, the position of the UV-C source, lamp degradation, humidity and other factors, making it challenging to estimate. Furthermore, since UV-C exposure is regulated, personnel in the room must not be exposed to UV-C doses beyond occupational limits. We proposed a systematic method to monitor the UV-C dose administered to surfaces during a robotic disinfection procedure. This was achieved using a distributed network of wireless UV-C sensors that provide real-time measurements to a robotic platform and operator. These sensors were validated for their linearity and cosine response. To ensure operators could safely remain in the area, a wearable sensor was incorporated to monitor the UV-C exposure of an operator, and it provided an audible warning upon exposure and, if necessary, ceased the UV-C emission from the robot. Enhanced disinfection procedures could then be conducted as items in the room could be rearranged during the procedure to maximise the UV-C fluence delivered to otherwise inaccessible surfaces while allowing UVC disinfection to occur in parallel with traditional cleaning. The system was tested for the terminal disinfection of a hospital ward. During the procedure, the robot was manually positioned in the room by the operator repeatedly, who then used feedback from the sensors to ensure the desired UV-C dose was achieved while also conducting other cleaning tasks. An analysis verified the practicality of this disinfection methodology while highlighting factors which could affect its adoption.

Indexed as

DisinfectionPatients' RoomsHospitalsUltraviolet Raysbluetooth low energy (BLE)disinfection robothealthcareIOT sensorsafetyultraviolet (UV) disinfectionwearable

Identifiers

PMID36904695
PMCPMC10007517

What OpenQuestion holds

Textfull text, public
LicenceCC BY
measurements read7
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.