Publications

Detailed Information

Tool to visualize and evaluate operator proficiency in laser hair-removal treatments

DC Field Value Language
dc.contributor.authorNoh, Seungwoo-
dc.contributor.authorKoh, Woo Seok-
dc.contributor.authorLim, Hyoung-woo-
dc.contributor.authorYoon, Chiyul-
dc.contributor.authorKim, Youdan-
dc.contributor.authorChung, Jin Ho-
dc.contributor.authorKim, Hee Chan-
dc.contributor.authorKim, Sungwan-
dc.date.accessioned2017-03-20T05:27:10Z-
dc.date.available2017-03-20T14:33:43Z-
dc.date.issued2014-04-08-
dc.identifier.citationBioMedical Engineering OnLine, 13(1):40ko_KR
dc.identifier.urihttps://hdl.handle.net/10371/109854-
dc.description.abstractBackground
The uniform delivery of laser energy is particularly important for safe and effective laser hair removal (LHR) treatment. Although it is necessary to quantitatively assess the spatial distribution of the delivered laser, laser spots are difficult to trace owing to a lack of visual cues. This study proposes a novel preclinic tool to evaluate operator proficiency in LHR treatment and applies this tool to train novice operators and compare two different treatment techniques (sliding versus spot-by-spot).

Methods
A simulation bed is constructed to visualize the irradiated laser spots. Six novice operators are recruited to perform four sessions of simulation while changing the treatment techniques and the presence of feedback (sliding without feedback, sliding with feedback, spot-by-spot without feedback, and spot-by-spot with feedback). Laser distribution maps (LDMs) are reconstructed through a series of images processed from the recorded video for each simulation session. Then, an experienced dermatologist classifies the collected LDMs into three different performance groups, which are quantitatively analyzed in terms of four performance indices.

Results
The performance groups are characterized by using a combination of four proposed indices. The best-performing group exhibited the lowest amount of randomness in laser delivery and accurate estimation of mean spot distances. The training was only effective in the sliding treatment technique. After the training, omission errors decreased by 6.32% and better estimation of the mean spot distance of the actual size of the laser-emitting window was achieved. Gels required operators to be trained when the spot-by-spot technique was used, and imposed difficulties in maintaining regular laser delivery when the sliding technique was used.

Conclusions
Because the proposed system is simple and highly affordable, it is expected to benefit many operators in clinics to train and maintain skilled performance in LHR treatment, which will eventually lead to accomplishing a uniform laser delivery for safe and effective LHR treatment.
ko_KR
dc.language.isoenko_KR
dc.publisherBioMed Centralko_KR
dc.subjectLaser visualizationko_KR
dc.subjectPerformance evaluationko_KR
dc.subjectPhotomedicineko_KR
dc.subjectSimulation bedko_KR
dc.subjectTraining toolko_KR
dc.titleTool to visualize and evaluate operator proficiency in laser hair-removal treatmentsko_KR
dc.typeArticleko_KR
dc.contributor.AlternativeAuthor노승우-
dc.contributor.AlternativeAuthor고우석-
dc.contributor.AlternativeAuthor임형우-
dc.contributor.AlternativeAuthor윤치열-
dc.contributor.AlternativeAuthor김유단-
dc.contributor.AlternativeAuthor정진호-
dc.contributor.AlternativeAuthor김희찬-
dc.contributor.AlternativeAuthor김성완-
dc.language.rfc3066en-
dc.rights.holderNoh et al.; licensee BioMed Central Ltd.-
dc.date.updated2017-01-06T10:40:59Z-
Appears in Collections:
Files in This Item:

Altmetrics

Item View & Download Count

  • mendeley

Items in S-Space are protected by copyright, with all rights reserved, unless otherwise indicated.

Share