Handheld Device for Burn Depth Analysis Through Skin Hydration: A Proof of Concept

About 500,000 Americans seek treatment for burns annually, but burn depth, used to create treatment plans and determine whether surgery is needed for treatment, is only correctly found about 50-80% of the time in the US. In the UK and other countries, clinicians have used laser doppler imaging (LDI) with clinical evaluation to increase diagnostic accuracy, however US based physicians tend to just use clinical evaluation, citing cost and difficulty of use as reasons for not using this technology. The purpose of this thesis is to present an innovative, cheap, and easy to use device that can be used to evaluate burn depth in a non-contact modality. When researching the pathophysiology of burn injuries, I found Jackson’s thermal wound theory, postulating that besides the degradation of proteins in the immediate environment, poor fluid flow is the next biggest challenge, without fixing more tissue will die. LDI uses this idea to look for fluid movement, while I planned to use this by finding water. The macro scale seemed to support this as well, burn victims with a significant amount of skin area burned lose so much fluid that they require IV fluid resuscitation for recovery. Based on this detection method, I created a device with a pair of LEDs that emit light at 910 and 970 nm, where 970 nm is a water absorption peak. To ensure that the device meets standards, a mathematical model was created and tested.

Publication Details

Journal
ScholarWorks@UMassAmherst (University of Massachusetts Amherst)
Published
2025-11-14
DOI
https://doi.org/10.7275/ard6-z845
Primary Topic
Burn Injury Management and Outcomes
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Handheld Device for Burn Depth Analysis Through Skin Hydration: A Proof of Concept

ScholarWorks@UMassAmherst (University of Massachusetts Amherst)
Burn Injury Management and Outcomes
article

Handheld Device for Burn Depth Analysis Through Skin Hydration: A Proof of Concept

article en

Abstract

About 500,000 Americans seek treatment for burns annually, but burn depth, used to create treatment plans and determine whether surgery is needed for treatment, is only correctly found about 50-80% of the time in the US. In the UK and other countries, clinicians have used laser doppler imaging (LDI) with clinical evaluation to increase diagnostic accuracy, however US based physicians tend to just use clinical evaluation, citing cost and difficulty of use as reasons for not using this technology. The purpose of this thesis is to present an innovative, cheap, and easy to use device that can be used to evaluate burn depth in a non-contact modality. When researching the pathophysiology of burn injuries, I found Jackson’s thermal wound theory, postulating that besides the degradation of proteins in the immediate environment, poor fluid flow is the next biggest challenge, without fixing more tissue will die. LDI uses this idea to look for fluid movement, while I planned to use this by finding water. The macro scale seemed to support this as well, burn victims with a significant amount of skin area burned lose so much fluid that they require IV fluid resuscitation for recovery. Based on this detection method, I created a device with a pair of LEDs that emit light at 910 and 970 nm, where 970 nm is a water absorption peak. To ensure that the device meets standards, a mathematical model was created and tested.

ScholarWorks@UMassAmherst (University of Massachusetts Amherst)
Openalex Percentile: Top 36%
Burn Injury Management and Outcomes
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.