Evidence map›Paper›PMID 37545076›Full record

ArticleSichuan da xue xue bao. Yi xue ban = Journal of Sichuan University. Medical science edition2023

[An Integrated Audio-Visual-Olfactory Virtual Reality False Feeding Device: Research, Development, and Design].

Ka Li, Xingzhu Yuan, Yanjie Hu, Weihua Zhang, Yuwen Chen, Rui Hong, Jie Yang

Open access · greenAbstract readEnglish Abstract
In one paragraph

Article in Sichuan da xue xue bao. Yi xue ban = Journal of Sichuan University. Medical science edition, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed, 2 citations in OpenAlex.

  1. Article
  2. 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

7 authors at 1 institution in 1 country.

Ka LiWest China School of Nursing, Sichuan University/West China Hospital, Sichuan University, Chengdu 610041, China.
Xingzhu YuanWest China School of Nursing, Sichuan University/West China Hospital, Sichuan University, Chengdu 610041, China.
Yanjie HuWest China School of Nursing, Sichuan University/West China Hospital, Sichuan University, Chengdu 610041, China.
Weihua ZhangCollege of Computer Science, Sichuan University, Chengdu 610065, China.
Yuwen ChenWest China School of Nursing, Sichuan University/West China Hospital, Sichuan University, Chengdu 610041, China.
Rui HongWest China School of Nursing, Sichuan University/West China Hospital, Sichuan University, Chengdu 610041, China.
Jie YangCenter of Colorectal Cancer, West China Hospital, Sichuan University, Chengdu 610041, China.
Sichuan University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: To resolve the problem of the lack of sensory stimulation from the colors and aromas of food when patients are given enteral nutrition support by tube feeding or simple oral administration, an immersive virtual reality (VR) sham feeding device integrating audio, visual, and olfactory sense perceptions was developed independently and the usability of the device was tested. Methods: Relying on the multidisciplinary cooperation of nursing, mechanical engineering, and computer science and using as a reference the characteristics of gastric tube and oxygen tube placement in clinical patients, we carried out 3D modeling and printing of the exterior framework of the odor box. Unity 3d.5.x, a mainstream virtual engine tool, was used to create scenarios. The device could create visual stimulation through 3 VR dining scenarios, 23 kinds of food, and comfortable dining environment. The sound of chewing was played to simulate the dining process and provide auditory stimulation. Through the independently researched and developed olfactory odor box, corresponding food aromas were sprayed out for olfactory stimulation. After the equipment prototype was created, 10 patients were recruited to perform users' subjective evaluation of the usability of the equipment. Results: A VR sham feeding device integrating audio-visual-olfactory stimulation was successfully developed. In the visual effect evaluation, all users commented that the vision was clear and unimpeded, and that the menu program could follow their rotation movement. Eight people considered the scenes to be rather realistic. In the auditory effect evaluation, all users stated that the volume of the sound was appropriate, and that they would hear a chewing sound being played when the food was approaching. In the olfactory effect evaluation, 9 people stated that they smelled the food aromas when the food was approaching, and that they thought the odor was real or partially real. On the whole, the equipment was convenient to use and all users thought that the equipment had clear presentation and could run stably and smoothly. No adverse reactions, such as dizziness, occurred in any users. Conclusion: Successfully presenting visual, auditory, and olfactory stimuli, the prototype device passed the subjective usability test. The prototype device effectively expands the application prospects of VR in the medical field. In the future, it will be applied to patient populations, including surgical patients, patients with eating disorders, obesity, and loss of appetite, and other patients who cannot take in food through their mouths. The prototype device provides new ideas for promoting enhanced recovery after surgery and improving patient experience.

Indexed as

Enteral NutritionSmellSoundVirtual RealityHumansAudio, visual, and olfactory sensesEquipment research and developmentImprove patient experienceSham feedingVirtual reality

Identifiers

PMID37545076
PMCPMC10442627
OpenAlexW4385620334

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.