Ways to increase precision and accuracy of wound area measurement using smart devices: Advanced app Planimator

Accreditation of the handheld 3-dimensional scanner and conventional photo images for area measurement

Accurate assessment of wound areas is crucial in making therapeutic decisions, as the prognosis and changes in the size of the wound over time play a significant role. An ideal assessment method should possess qualities such as speed, affordability, accuracy, user-friendliness for both patients and healthcare professionals, and suitability for daily clinical practice. This study aims to introduce a handheld 3-dimensional (3D) scanner and evaluate its accuracy in measuring wound areas. Engineers from the Industrial Technology Research Institute in Taiwan developed a handheld 3D scanner with the intention of extending its application to the medical field. A project was conducted to validate the accuracy of this 3D scanner. We utilized a smartphone (Asus ZenFone 2 with a 13-million-pixel rear camera), a digital single-lens reflex digital camera (Nikon, D5000, Tokyo, Japan), and the 3D scanner to repeatedly measure square papers of known size that were affixed to the curved surface of life-size facial mask or medical teaching breast models. The "Image J" software was employed for 2-dimensional image measurements, while the "3D Edit" software was used to assess the "area of interest" on 3D objects. By using square papers with predetermined dimensions, the measurement-associated error rate (ER) could be calculated for each image. Three repeated measurements were performed using the "Image J" software for each square paper. The ERs of the 3D scan images were all below 3%, with an average ER of 1.64% in this study. The close-up mode of the smartphone exhibited the highest ER. It was observed that as the area increased, the ER also increased in the digital single-lens reflex camera group. The extension distortion effect caused by the wide-angle lens on the smartphone may increase the ER. However, the definition of a healthy skin edge may vary, and different algorithms for calculating the measurement area are employed in various 3D measurement software. Therefore, further validation of their accuracy for medical purposes is necessary. Effective communication with software engineers and discussions on meeting clinical requirements are crucial steps in enhancing the functionality of the 3D scanner.

Measurement of perineal tears as an additional tool for laceration assessment during vaginal birth

INTRODUCTION

Spontaneous lacerations at vaginal birth are everyday events, but their classification and management still challenge midwifery care. This study aims to measure and describe first-degree and second-degree perineal lacerations resulting from vaginal birth, describe their repair, and the education provided for care.

METHODS

A descriptive study was conducted in a public maternity hospital in São Paulo, Brazil, with 87 parturients. Data were collected between October 2017 and June 2018 using a structured instrument containing obstetric variables and a description of lacerations. The obstetricians and nurse midwives assisted with births, determining the degree of laceration and intervention, and the researchers measured and reported them.

RESULTS

The majority of parturients (82.7%) had lacerations only in the anterior region, 8% had them in the posterior region, and 9.2% in both regions. The lacerations were classified as first-degree (78.1%) or second-degree (21.8%). Among the 32 nulliparous parturients, 27.6% had first-degree lacerations, and 9.2% had second-degree. Of the 55 multiparous parturients, 50.6% had first-degree, and 12.6% had second-degree. Among the lacerations assessed as first-degree, 25% had deeper tissue layers compromised in addition to the skin and mucosa. There were 180 lacerations, with an average length of 33.1 mm, depth of 19.8 mm, and width of 23.8 mm. Half of the parturients did not receive guidance on laceration care. There was no association between parity and size, number, location, or degree classification of lacerations.

CONCLUSIONS

This study provides a broad description of the characteristics of perineal lacerations and presents measurement techniques as a complementary resource for evaluating lacerations.

Understanding progressive tissue loss and wound burden in combat casualties: lessons learnt for future operational capability

Understanding tissue loss following injury is important due to its prevalence among the war-wounded and the impact it has on subsequent treatment and rehabilitation. Progressive tissue loss is a type of tissue loss that has complicated extremity injury in recent conflicts. It has resulted in more proximal residual limb lengths and has influenced rehabilitation. Quantifying wound burden in combat casualties remains a challenge due to poor quality of data sets that lack the capacity for detailed analysis. The aims of this article are to outline the current hurdles in attempting to quantify wound burden in combat casualties and to propose simple interventions to improve data capture for future analysis.

Determining the measurement accuracy in assessing the progress of wound healing

Introduction

Wound management is a challenge in terms of the way, duration and cost of treatment both for the patient and health providers. The healing of skin wounds is a highly multi-step coordinated process. Objective monitoring of treatment at every stage is necessary to assess the applied therapy.

Aim

To show the possibility of using the AutoCad software (ACS) as a tool with a slight measurement error for accurate measurement of the venous leg ulcers on the lower limbs.

Material and methods

To determine the error of the measurement method Circle Templates For Drafting for four different sizes were used as ulcer models. Seventy-six wounds of various sizes from patients with venous leg ulcers (VLUs) were photographed and outlined with a marker on a transparent foil. The wounds were measured both using ACS and digital planimetry with C-Geo software (CGS). Data were analysed using Wilcoxon test, intraclass correlation coefficient (ICC) and Bland-Altman analysis.

Results

The mean relative error of the surface wound model area measured by the ACS was 0.30 ±0.31% (range: 0.004-1.25) and a median of 0.18%. Areas and perimeters measured with ACS were higher than areas and perimeters measured with CGS, and the difference was statistically significant.

Conclusions

The analysis of the wound images obtained in the ACS showed a very high potential of the software in terms of the accuracy of the analysed areas, which significantly increases the possibility of the analysis and reduces the measurement error in relation to planimetry using a digital digitizer.

COMPUTER SYSTEMS TO AID IN WOUND HEALING: SCOPE REVIEW

Objective: To investigate studies that present computational systems to aid healing and systems which refer to the use of low-level laser.Method: Scope review that aimed to answer the question: Which computer systems help in wound healing? A subquestion was: Which of the computer systems refer to the use of low-level laser? Results: From the search, applying the eligibility criteria, 49 articles made up the final sample. The systems served multiple purposes in support of wound healing; the majority presented the health professional as a user of the system; medicine was the most mentioned professional area despite nursing being involved in the management of care for people with wounds. Innovation in care using the computer system was frequently reported, demonstrating the importance of this type of tool for clinical practice. There was a high frequency of the mobile platform, showing that this is a current trend. Conclusion:Computer systems have been used as tools to support patients and especially professionals in wound healing. Regarding the systems aimed at the low intensity laser, there was a shortage of computer systems for this purpose, with a study.

SISTEMAS COMPUTACIONAIS PARA AUXÍLIO NA CICATRIZAÇÃO DE FERIDAS: REVISÃO DE ESCOPO

Objetivo:Investigar estudos que apresentem sistemas computacionais de auxílio à cicatrização de feridas e quais sistemas se referem ao uso de laser de baixa intensidade. Método: Revisão de escopo que visou responder à questão de pesquisa: Quais sistemas computacionais auxiliam na cicatrização de feridas? Uma subquestão foi: quais sistemas computacionais se referem ao uso do laser de baixa intensidade? Resultados: A partir da busca, aplicando os critérios de elegibilidade, 49 artigos compuseram a amostra final. Os sistemas apresentaram várias finalidades de apoio à cicatrização de feridas, em que a maioria apresentou como usuário do sistema o profissional de saúde, sendo a medicina a área profissional mais mencionada, embora a enfermagem esteja envolvida com o manejo do cuidado às pessoas com feridas. Foi relatada com frequência a inovação na assistência a partir do uso do sistema computacional, o que demonstra a importância desse tipo de ferramenta para a prática clínica. Verificou-se com frequência o uso de plataforma mobile, como tendência da atualidade. Conclusão: Os sistemas computacionais têm sido utilizados como ferramentas para apoiar pacientes e principalmente profissionais na cicatrização de feridas. Quanto ao laser de baixa intensidade, houve escassez de sistemas computacionais com essa finalidade, com apenas um estudo.

A time motion study of manual versus artificial intelligence methods for wound assessment

Objectives

This time-motion study explored the amount of time clinicians spent on wound assessments in a real-world environment using wound assessment digital application utilizing Artificial Intelligence (AI) vs. manual methods. The study also aimed at comparing the proportion of captured quality wound images on the first attempt by the assessment method.

Methods

Clinicians practicing at Valley Wound Center who agreed to join the study were asked to record the time needed to complete wound assessment activities for patients with active wounds referred for a routine evaluation on the follow-up days at the clinic. Assessment activities included: labelling wounds, capturing images, measuring wounds, calculating surface areas, and transferring data into the patient’s record.

Results

A total of 91 patients with 115 wounds were assessed. The average time to capture and access wound image with the AI digital tool was significantly faster than a standard digital camera with an average of 62 seconds (P<0.001). The digital application was significantly faster by 77% at accurately measuring and calculating the wound surface area with an average of 45.05 seconds (P<0.001). Overall, the average time to complete a wound assessment using Swift was significantly faster by 79%. Using the AI application, the staff completed all steps in about half of the time (54%) normally spent on manual wound evaluation activities. Moreover, acquiring acceptable wound image was significantly more likely to be achieved the first time using the digital tool than the manual methods (92.2% vs. 75.7%, P<0.004).

Conclusions

Using the digital assessment tool saved significant time for clinicians in assessing wounds. It also successfully captured quality wound images at the first attempt.

Non-contact wound area assessment by digital planimetry using photo editing software

To objectively assess wound healing utilizing a novel digital photo planimetry method. 58 wounds mostly of traumatic origin were studied. In method I (control or gold standard), a transparent plastic graph paper sheet with 2.5 mm squares was placed on the wound to trace the wound edges. This was scanned and analyzed in Adobe Photoshop (PS6) to estimate the area. In the novel method (method II), we clicked a photo with one-inch lines marked (on either side of the wound). This photo was similarly assessed in PS6. A two-sample t-test was used for analysis. Photos were clicked every third day. The time taken to calculate the resultant area was also noted. 484 photos and 1936 values were analyzed. The mean areas obtained were 10690 mm 2 and 10859 mm 2 respectively by methods I and II. The mean difference was 0.824%, 95% CI [-0.05, 1.60] and p = 0.923. The inter and intra- observer variation was < 2% for all readings. The time taken by the novel method was much lesser than the time-tested method (mean = 82 sec vs 178 sec; p < 0.01). The difference in area by the two methods is not statistically significant. The accuracy of both methods is therefore comparable. Our novel method is easier, more cost-effective, equally accurate, safer and repro- ducible in comparison with the transparency squares method, especially for flat or 2-dimensional wounds.

Digital Planimetry With a New Adaptive Calibration Procedure Results in Accurate and Precise Wound Area Measurement at Curved Surfaces

BACKGROUND

The purpose of this study was to determine the accuracy of wound area measurement at a curved surface using a digital planimetry (DP) with the newly proposed adaptive calibration.

METHODS

Forty wound shapes were printed and placed at the side surfaces of cylinders with diameters of 9.4 and 6.2 cm. Area measurements were carried out using a commercial device SilhouetteMobile (Aranz, New Zealand) and the planimetric app Planimator. Planimetric area measurements were carried out using 2 one-dimensional calibration markers placed above and below the wound shape. The method of adaptive calibration for DP was described. Reference area values of wound shapes were obtained by pixel counting on digital scans made with an optical scanner. Relative errors (REs) and relative differences (RDs) for area measurements were analyzed.

RESULTS

The median of REs for the DP with adaptive calibration (DPwAC) was equal to 0.60% and was significantly smaller than the median for the SilhouetteMobile device (SMD) (2.65%), and significantly smaller than the median for the DP (2.23%). The SD of RDs for the DPwAC of 0.87% was considerably lower than for the SMD (6.45%), and for the DP without adaptive calibration (2.51%). The mean of RDs for the DPwAC (0.082%) was not significantly different from zero, which means that the systematic error was not present for the DPwAC.

CONCLUSIONS

The use of the adaptive calibration in DP to measure the areas at curved surface resulted in a significant increase of accuracy and precision, and removal of systematic error. The DPwAC revealed 4.4 times lower error and 7.4 times higher precision of area measurement at curved surfaces than the SMD.

Wound Size Imaging: Ready for Smart Assessment and Monitoring

Significance: We introduce and evaluate emerging devices and modalities for wound size imaging and also promising image processing tools for smart wound assessment and monitoring. Recent Advances: Some commercial devices are available for optical wound assessment but with limited possibilities compared to the power of multimodal imaging. With new low-cost devices and machine learning, wound assessment has become more robust and accurate. Wound size imaging not only provides area and volume but also the proportion of each tissue on the wound bed. Near-infrared and thermal spectral bands also enhance the classical visual assessment. Critical Issues: The ability to embed advanced imaging technology in portable devices such as smartphones and tablets with tissue analysis software tools will significantly improve wound care. As wound care and measurement are performed by nurses, the equipment needs to remain user-friendly, enable quick measurements, provide advanced monitoring, and be connected to the patient data management system. Future Directions: Combining several image modalities and machine learning, optical wound assessment will be smart enough to enable real wound monitoring, to provide clinicians with relevant indications to adapt the treatments and to improve healing rates and speed. Sharing the wound care histories of a number of patients on databases and through telemedicine practice could induce a better knowledge of the healing process and thus a better efficiency when the recorded clinical experience has been converted into knowledge through deep learning.

Hard-to-heal wounds: a randomised trial of an oral proline-containing supplement to aid repair

OBJECTIVE

We evaluated the effects of a specialised oral nutritional supplement (ONS) containing arginine and proline, with high vitamin A, C and E, zinc and selenium content, on the repair of hard-to-heal wounds.

METHOD

Patients with hard-to-heal wounds were evaluated at five timepoints (S0-S4) over four consecutive weeks. At S0 patients were randomised to the specialised ONS (n=15; 25 wounds) or control (n=15; 25 wounds) groups. Posology was 200ml twice daily over the research period. Wound surface area and perimeter were monitored. In addition to the metric data, it was also possible to calculate the rate of wound contraction and the linear growth of the wound edges, looking for wound-healing predictive factors.

RESULTS

A total of 30 patients took part in the study. Mean age was 65 years and 50% of patients had diabetes. Of the total evaluated wounds, 78% were <50cm², 14% were 50-150cm² and 8% were >250cm². In 96% of cases, the wounds were in the lower limbs. A statistically significant reduction (p=0.004) in surface area of the wounds due to the specialised ONS, with a performance peak between S1 and S2, was observed. This specialised ONS did not induce changes in blood pressure, blood glucose level or renal function. A mean weekly wound edge growth of 1.85mm in patients with diabetes and 3.0mm in those without diabetes was observed. These results were 2.9 and 4.6 times, respectively, higher than expected, according to the literature.

CONCLUSION

Specialised ONS can be a therapeutic option for hard-to-heal wounds.

SfM-3DULC: Reliability of a new 3D wound measurement procedure and its accuracy in projected area

Three‐dimensional (3D) wound measurement lacks a gold standard to test accuracy. It is useful to develop procedures to scan wounds and reconstruct their 3D model with low‐cost techniques. We present a new procedure (Structure from Motion [SfM]‐3DULC) that uses photographs for measuring nine wound variables. We also propose a new variant of ImageJ in which an orthophoto is used to measure the projected area (Ortho‐ImageJ). In addition, we compare the wound measurements made by dermatologists and non‐experts. A group of five experts in dermatology and five non‐specialists measured 33 leg wounds five times per procedure. Intra‐rater and inter‐rater reliability scores of SfM‐3DULC were evaluated with the intraclass correlation coefficient (ICC 2,1). The accuracy of the two new procedures (SfM‐3DULC and Ortho‐ImageJ) in the measurement of projected area was assessed by comparing their values with those obtained using ImageJ, with the Wilcoxon matched‐pairs signed rank test (α = 0.05). This test was also used to analyse the differences between the measurements made by dermatologists and non‐experts. All the variables measured by dermatologists using SfM‐3DULC showed excellent scores of intra‐rater reliability (ICC > 0.99) and inter‐rater reliability (ICC > 0.98). No significant differences between the three procedures were found when comparing their projected area values. Significant differences between the measurements of dermatologists and non‐experts were found in most of the variables: circularity coefficient, perimeter, projected area, surface area, and reference surface area. The wound measurement procedure SfM‐3DULC has an excellent reliability, is accurate for the measurement of projected area, and can be used by dermatologists for wound monitoring in everyday clinical practice.

The UTrack framework for segmenting and measuring dermatological ulcers through telemedicine

Chronic dermatological ulcers cause great discomfort to patients, and while monitoring the size of wounds over time provides significant clues about the healing evolution and the clinical condition of patients, the lack of practical applications in existing studies impairs users' access to appropriate treatment and diagnosis methods. We propose the UTrack framework to help with the acquisition of photos, the segmentation and measurement of wounds, the storage of photos and symptoms, and the visualization of the evolution of ulcer healing. UTrack-App is a mobile app for the framework, which processes images taken by standard mobile device cameras without specialized equipment and stores all data locally. The user manually delineates the regions of the wound and the measurement object, and the tool uses the proposed UTrack-Seg segmentation method to segment them. UTrack-App also allows users to manually input a unit of measurement (centimeter or inch) in the image to improve the wound area estimation. Experiments show that UTrack-Seg outperforms its state-of-the-art competitors in ulcer segmentation tasks, improving F-Measure by up to 82.5% when compared to superpixel-based approaches and up to 19% when compared to Deep Learning ones. The method is unsupervised, and it semi-automatically segments real-world images with 0.9 of F-Measure, on average. The automatic measurement outperformed the manual process in three out of five different rulers. UTrack-App takes at most 30 s to perform all evaluation steps over high-resolution images, thus being well-suited to analyze ulcers using standard mobile devices.

A toolkit for the quantitative evaluation of chronic wounds evolution for early detection of non-healing wounds

BACKGROUND

Chronic wounds resulting from a number of conditions do not heal properly and can pose serious health problems. Beyond clinician visual inspection, an objective evaluation of the wound is required to assess wound evolution and the effectiveness of therapies.

AIM

Our objective is to provide a methodology for the analysis of wound area vs. time for the early prediction of non-healing wounds evolution.

METHODS

We propose a two-step approach consisting of: i) wound area quantification from planimetries and ii) classification of wound healing through the inference of characteristic parameters. For the first step, we describe a user-friendly software (Woundaries) to automatically calculate the wound area and other geometric parameters from hand-traced planimetries. For the second, we use a procedure for the objective classification of wound time evolution and the early assessment of treatment efficacy. The methodology was tested on simulations and retrospectively applied to data from 85 patients to compare the effect of a biological therapy with respect to general basic therapeutics.

RESULTS

Woundaries provides measurements of wound surface equivalent to a validated device. The two-step methodology allows to determine if a wound is healing with high sensitivity, even with limited amount of data. Therefore, it allows the early assessment of the efficacy of a therapy.

CONCLUSION

The performance of this methodology for the quantification and the objective evaluation of wound area evolution suggest it as a useful toolkit to assist clinicians in the early assessment of the efficacy of treatments, leading to a timely change of therapy.

Smartphone application for wound area measurement in clinical practice

A total of 85 consecutive patients had their wound area measured. The procedure was executed in two parts. The first was to take photographs of the wound using a smartphone and measure the area using the imitoMeasure application (imito; imito AG, Zurich, Switzerland) by two raters. The second was to take photographs of the same wound using a 10-megapixel digital camera and posterior measurement of the area using ImageJ software (National Institutes of Health, Bethesda, Md) by one operator. The mean area of the wounds was 12.20 ± 10.45 cm² for imito and 12.67 ± 10.86 cm² for ImageJ measurement. The interclass correlation coefficient (ICC) between ImageJ and imito was 0.978 for a single measure and 0.989 for the average measure. Considering the two measurements, the ICC demonstrated excellent interobserver correlation using imito (0.987). Larger wounds had a greater difference between the methods (4.28% greater with the ImageJ measurement when considering areas >9 cm²). No difference was found between iOS (ICC, 0.995) and android (ICC, 0.970) smartphone operating systems. The smartphone application is a useful method for area measurement with excellent accuracy compared with digital photography and the ImageJ processing tool.

Insulin, but Not Metformin, Supports Wound Healing Process in Rats with Streptozotocin-Induced Diabetes

PURPOSE

Optimal glycemic control is crucial for proper wound healing in patients with diabetes. However, it is not clear whether other antidiabetic drugs support wound healing in mechanisms different from the normalization of blood glucose control. We assessed the effect of insulin and metformin administration on the wound healing process in rats with streptozotocin-induced diabetes.

METHODS

The study was conducted on 200 male Wistar rats with streptozotocin-induced diabetes. In the last phase of the study, 45 rats, with the most stable glucose levels in the range of 350-500 mg/dL, were divided into three groups: group I received human non-protamine insulin subcutaneously (5 IU/kg body mass) once a day, group II received metformin intragastrically (500 mg/kg b.m.), and group III (control) was given saline subcutaneously. After 14 days of antidiabetic treatment, a 2 cm × 2 cm thin layer of skin was cut from each rat's dorsum and a 4 cm disk with a hole in its center was sewn in to stabilize the skin and standardize the healing process. The wound healing process was followed up for 9 days, with assessment every 3 days. Biopsy samples were subjected to hematoxylin and eosin staining and immunohistochemical assays.

RESULTS

Analysis of variance revealed significant influence of treatment type (insulin, control, or metformin) on the relative change in wound surface area. The wound healing process in rats treated with insulin was more effective than in the metformin and control groups. Wound tissue samples taken from the insulin-treated animals presented significantly lower levels of inflammatory infiltration. Immunohistochemical assessment showed the greatest density of centers of proliferation Ki-67 in insulin-treated animals.

CONCLUSION

These results suggest that an insulin-based treatment is more beneficial than metformin, in terms of accelerating the wound healing process in an animal model of streptozocin-induced diabetes.

Augmented reality: a novel means of measurement in dermatology

Accurate measurement of skin lesions influences diagnosis, treatment, disease monitoring, prognosis, and even reimbursement in the practice of dermatology. As dermatologists expand technology that is integrated in patient care, measurement has the opportunity to become more accurate, more easily integrated into daily practice, and more easily incorporated into the realm of research. Herein, we review the benefits, limitations, and future direction of augmented reality (AR) in relationship to measurement of dermatologic conditions. This can include simple linear dimensions, area calculations, and even assessments that will drive clinical interventions. Additionally, we highlight current baseline mobile application tools that may lay the groundwork for further validation, augmentation, and utility of these technologies.

Measurement of wound area for early analysis of the scar predictive factor

Objective:

to evaluate the use of the 2D-FlexRuler as a facilitating tool for the early calculation of the predictive scar factor of chronic wounds.

Method:

a descriptive study with a quantitative, experimental, longitudinal and prospective approach. The sample consisted of 22 outpatients. 32 chronic wounds were analyzed. The wound edges were identified and drawn on the 2D-FlexRuler. The calculations of the areas of chronic wounds were obtained by manual, traditional methods, by software and Matlab algorithm. These areas were compared with each other to determine the efficiency of the proposed ruler in relation to traditional methods.

Results:

the calculation of the wound area by the traditional method and Kundin’s coefficient show average errors greater than 40%. The manual estimation of the area with the 2D-FlexRuler is more accurate in relation to traditional measurement methods, which were considered quantitatively disqualified. When compared with the reference method, for example, the Klonk software, the data obtained by 2D-FlexRuler resulted in an error of less than 1.0%.

Conclusion:

the 2D-FlexRuler is a reliable metric platform for obtaining the anatomical limits of chronic wounds. It facilitated the calculation of the wound area under monitoring and allowed to obtain the scar predictive factor of chronic wounds with precocity in two weeks.

Wound area measurement with 3D transformation and smartphone images

BACKGROUND

Quantitative areas is of great measurement of wound significance in clinical trials, wound pathological analysis, and daily patient care. 2D methods cannot solve the problems caused by human body curvatures and different camera shooting angles. Our objective is to simply collect wound areas, accurately measure wound areas and overcome the shortcomings of 2D methods.

RESULTS

We propose a method with 3D transformation to measure wound area on a human body surface, which combines structure from motion (SFM), least squares conformal mapping (LSCM), and image segmentation. The method captures 2D images of wound, which is surrounded by adhesive tape scale next to it, by smartphone and implements 3D reconstruction from the images based on SFM. Then it uses LSCM to unwrap the UV map of the 3D model. In the end, it utilizes image segmentation by interactive method for wound extraction and measurement. Our system yields state-of-the-art results on a dataset of 118 wounds on 54 patients, and performs with an accuracy of 0.97. The Pearson correlation, standardized regression coefficient and adjusted R square of our method are 0.999, 0.895 and 0.998 respectively.

CONCLUSIONS

A smartphone is used to capture wound images, which lowers costs, lessens dependence on hardware, and avoids the risk of infection. The quantitative calculation of the 3D wound area is realized, solving the challenges that 2D methods cannot and achieving a good accuracy.

The impact of an mHealth app on knowledge, skills and anxiety about dressing changes: A randomized controlled trial

AIMS

To evaluate the effectiveness of a mobile health (mHealth) application, based on self-regulation theory, on patients' knowledge of wound care, skills in changing dressings and anxiety.

DESIGN

A prospective randomized controlled trial.

METHODS

Seventy patients (or family members) at a 1,500-bed university hospital in Taiwan were randomized into an experimental (N = 35) or control group (N = 35) from March to December 2016. The experimental group used a mHealth application for wound care; the control group received verbal instructions and a booklet. Instruments to collect data were a wound care knowledge scale, wound care skills scale, State-Trait Anxiety Inventory, and a digital heart variability device. Data were collected at baseline, after three additional demonstrations and before discharge. The generalized estimating equation was used for statistical analysis.

RESULTS

The experimental group showed significantly higher levels of wound care knowledge, improved wound care skills, lower levels of state anxiety, and lower heart rate variability than the control group after baseline data collection.

CONCLUSIONS

Results support hat a mHealth application may be effective in health education. Clinicians can use the results to promote patients' wound care knowledge, enhance their wound care skills, and reduce anxiety related to dressing changes.

IMPACT

Lack of wound care knowledge and skills can affect the willingness and ability to perform effective wound dressing changes, producing anxiety and having an impact on a patient's self-care after hospital discharge. mHealth applications (apps) have the potential to deliver health information in targeted and tailored ways that strengthen the self-management of diseases. mHealth app can increase wound care knowledge, improve care skills, and reduce anxiety related to wound care. mHealth app effectively supports self-monitoring of the wound healing process, self-judgement of the wound condition, and self-reaction of wound care accuracy. mHealth app provides step-by-step visual tutorials on wound care that allow patients and family caregivers to take pictures of the wounds and monitor the wound healing process. mHealth app for wound care knowledge is an effective and individualized method for learning.

CLINICAL TRIAL

This study was registered by U.S. National Library of Medicine, ClinicalTrials.gov (ID: NCT03683303).

Measuring Surface Area of Skin Lesions with 2D and 3D Algorithms

Purpose

The treatment of skin lesions of various kinds is a common task in clinical routine. Apart from wound care, the assessment of treatment efficacy plays an important role. In this paper, we present a new approach to measure the skin lesion surface in two and three dimensions.

Methods

For the 2D approach, a single photo containing a flexible paper ruler is taken. After semi-automatic segmentation of the lesion, evaluation is based on local scale estimation using the ruler. For the 3D approach, reconstruction is based on Structure from Motion. Roughly outlining the region of interest around the lesion is required for both methods.

Results

The measurement evaluation was performed on 117 phantom images and five phantom videos for 2D and 3D approach, respectively. We found an absolute error of 0.99±1.18  cm² and a relative error 9.89± 9.31% for 2D. These errors are <1  cm² and <5% for five test phantoms in our 3D case. As expected, the error of 2D surface area measurement increased by approximately 10% for wounds on the bent surface compared to wounds on the flat surface. Using our method, the only user interaction is to roughly outline the region of interest around the lesion.

Conclusions

We developed a new wound segmentation and surface area measurement technique for skin lesions even on a bent surface. The 2D technique provides the user with a fast, user-friendly segmentation and measurement tool with reasonable accuracy for home care assessment of treatment. For 3D only preliminary results could be provided. Measurements were only based on phantoms and have to be repeated with real clinical data.