Evidence map›Paper›PMID 42502609›Full record

ArticleHardwareX2026

Low-cost head-mounted camera system for medication-error detection.

Solomon Nsumba, Joan Kaitesi, Dianah Namutosi, Pius Kavuma Mugagga, Joyce Nakatumba-Nabende, Peter Nabende

Abstract read
In one paragraph

Article in HardwareX, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. 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

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.

Solomon NsumbaCollege of Computing & Information Sciences, Makerere University, Kampala, Uganda.
Joan KaitesiCollege of Computing & Information Sciences, Makerere University, Kampala, Uganda.
Dianah NamutosiCollege of Computing & Information Sciences, Makerere University, Kampala, Uganda.
Pius Kavuma MugaggaLavingtonData, Mauritius.
Joyce Nakatumba-NabendeCollege of Computing & Information Sciences, Makerere University, Kampala, Uganda.
Peter NabendeCollege of Computing & Information Sciences, Makerere University, Kampala, Uganda.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We present a low-cost, reproducible head-mounted wearable system for first-person video capture and real-time medication-workflow monitoring. The device combines a Raspberry Pi Zero W, Pi Camera Module v3, PiSugar 2 Pro battery board, active buzzer, tactile push button, and a modular 3-D-printed PLA enclosure with elastic head straps. Weighing approximately 145 g and costing about USD 100 for the core wearable components (USD 168.78 for the complete development and configuration bill of materials), the system is designed for offline operation, local storage, and low-power embedded processing. The enclosure was modeled in DesignSpark Mechanical and fabricated as modular panels with integrated mounting, ventilation, and access features. The software stack runs on Raspberry Pi OS Lite with Python/OpenCV scripts for autonomous capture, local event flagging, and audible feedback. Pilot deployment confirmed stable operation, up to 7 h of battery-powered use, and practical wearability in clinical settings. This work provides a reproducible open-hardware platform for wearable monitoring in low-resource operating room environments.

Indexed as

Additive manufacturingEdge computingEmbedded systemsHead-mounted devicesLow-resource settingsOn-device inference

Identifiers

PMID42502609
PMCPMC13400407

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.