Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 3217

Search results for: skin detection

3217 Improved Skin Detection Using Colour Space and Texture

Authors: Medjram Sofiane, Babahenini Mohamed Chaouki, Mohamed Benali Yamina

Abstract:

Skin detection is an important task for computer vision systems. A good method for skin detection means a good and successful result of the system. The colour is a good descriptor that allows us to detect skin colour in the images, but because of lightings effects and objects that have a similar colour skin, skin detection becomes difficult. In this paper, we proposed a method using the YCbCr colour space for skin detection and lighting effects elimination, then we use the information of texture to eliminate the false regions detected by the YCbCr colour skin model.

Keywords: skin detection, YCbCr, GLCM, texture, human skin

Procedia PDF Downloads 279
3216 Towards Integrating Statistical Color Features for Human Skin Detection

Authors: Mohd Zamri Osman, Mohd Aizaini Maarof, Mohd Foad Rohani

Abstract:

Human skin detection recognized as the primary step in most of the applications such as face detection, illicit image filtering, hand recognition and video surveillance. The performance of any skin detection applications greatly relies on the two components: feature extraction and classification method. Skin color is the most vital information used for skin detection purpose. However, color feature alone sometimes could not handle images with having same color distribution with skin color. A color feature of pixel-based does not eliminate the skin-like color due to the intensity of skin and skin-like color fall under the same distribution. Hence, the statistical color analysis will be exploited such mean and standard deviation as an additional feature to increase the reliability of skin detector. In this paper, we studied the effectiveness of statistical color feature for human skin detection. Furthermore, the paper analyzed the integrated color and texture using eight classifiers with three color spaces of RGB, YCbCr, and HSV. The experimental results show that the integrating statistical feature using Random Forest classifier achieved a significant performance with an F1-score 0.969.

Keywords: color space, neural network, random forest, skin detection, statistical feature

Procedia PDF Downloads 296
3215 Burnout Recognition for Call Center Agents by Using Skin Color Detection with Hand Poses

Authors: El Sayed A. Sharara, A. Tsuji, K. Terada

Abstract:

Call centers have been expanding and they have influence on activation in various markets increasingly. A call center’s work is known as one of the most demanding and stressful jobs. In this paper, we propose the fatigue detection system in order to detect burnout of call center agents in the case of a neck pain and upper back pain. Our proposed system is based on the computer vision technique combined skin color detection with the Viola-Jones object detector. To recognize the gesture of hand poses caused by stress sign, the YCbCr color space is used to detect the skin color region including face and hand poses around the area related to neck ache and upper back pain. A cascade of clarifiers by Viola-Jones is used for face recognition to extract from the skin color region. The detection of hand poses is given by the evaluation of neck pain and upper back pain by using skin color detection and face recognition method. The system performance is evaluated using two groups of dataset created in the laboratory to simulate call center environment. Our call center agent burnout detection system has been implemented by using a web camera and has been processed by MATLAB. From the experimental results, our system achieved 96.3% for upper back pain detection and 94.2% for neck pain detection.

Keywords: call center agents, fatigue, skin color detection, face recognition

Procedia PDF Downloads 160
3214 Improvements in OpenCV's Viola Jones Algorithm in Face Detection–Skin Detection

Authors: Jyoti Bharti, M. K. Gupta, Astha Jain

Abstract:

This paper proposes a new improved approach for false positives filtering of detected face images on OpenCV’s Viola Jones Algorithm In this approach, for Filtering of False Positives, Skin Detection in two colour spaces i.e. HSV (Hue, Saturation and Value) and YCrCb (Y is luma component and Cr- red difference, Cb- Blue difference) is used. As a result, it is found that false detection has been reduced. Our proposed method reaches the accuracy of about 98.7%. Thus, a better recognition rate is achieved.

Keywords: face detection, Viola Jones, false positives, OpenCV

Procedia PDF Downloads 216
3213 Assessment of Image Databases Used for Human Skin Detection Methods

Authors: Saleh Alshehri

Abstract:

Human skin detection is a vital step in many applications. Some of the applications are critical especially those related to security. This leverages the importance of a high-performance detection algorithm. To validate the accuracy of the algorithm, image databases are usually used. However, the suitability of these image databases is still questionable. It is suggested that the suitability can be measured mainly by the span the database covers of the color space. This research investigates the validity of three famous image databases.

Keywords: image databases, image processing, pattern recognition, neural networks

Procedia PDF Downloads 95
3212 An Image Processing Scheme for Skin Fungal Disease Identification

Authors: A. A. M. A. S. S. Perera, L. A. Ranasinghe, T. K. H. Nimeshika, D. M. Dhanushka Dissanayake, Namalie Walgampaya

Abstract:

Nowadays, skin fungal diseases are mostly found in people of tropical countries like Sri Lanka. A skin fungal disease is a particular kind of illness caused by fungus. These diseases have various dangerous effects on the skin and keep on spreading over time. It becomes important to identify these diseases at their initial stage to control it from spreading. This paper presents an automated skin fungal disease identification system implemented to speed up the diagnosis process by identifying skin fungal infections in digital images. An image of the diseased skin lesion is acquired and a comprehensive computer vision and image processing scheme is used to process the image for the disease identification. This includes colour analysis using RGB and HSV colour models, texture classification using Grey Level Run Length Matrix, Grey Level Co-Occurrence Matrix and Local Binary Pattern, Object detection, Shape Identification and many more. This paper presents the approach and its outcome for identification of four most common skin fungal infections, namely, Tinea Corporis, Sporotrichosis, Malassezia and Onychomycosis. The main intention of this research is to provide an automated skin fungal disease identification system that increase the diagnostic quality, shorten the time-to-diagnosis and improve the efficiency of detection and successful treatment for skin fungal diseases.

Keywords: Circularity Index, Grey Level Run Length Matrix, Grey Level Co-Occurrence Matrix, Local Binary Pattern, Object detection, Ring Detection, Shape Identification

Procedia PDF Downloads 103
3211 A Convolutional Deep Neural Network Approach for Skin Cancer Detection Using Skin Lesion Images

Authors: Firas Gerges, Frank Y. Shih

Abstract:

Malignant melanoma, known simply as melanoma, is a type of skin cancer that appears as a mole on the skin. It is critical to detect this cancer at an early stage because it can spread across the body and may lead to the patient's death. When detected early, melanoma is curable. In this paper, we propose a deep learning model (convolutional neural networks) in order to automatically classify skin lesion images as malignant or benign. Images underwent certain pre-processing steps to diminish the effect of the normal skin region on the model. The result of the proposed model showed a significant improvement over previous work, achieving an accuracy of 97%.

Keywords: deep learning, skin cancer, image processing, melanoma

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3210 Human Skin Identification Using a Specific mRNA Marker at Different Storage Durations

Authors: Abla A. Ali, Heba A. Abd El Razik, Nadia A. Kotb, Amany A. Bayoumi, Laila A. Rashed

Abstract:

The detection of human skin through mRNA-based profiling is a very useful tool for forensic investigations. The aim of this study was definitive identification of human skin at different time intervals using an mRNA marker late cornified envelope gene 1C. Ten middle-aged healthy volunteers of both sexes were recruited for this study. Skin samples controlled with blood samples were taken from the candidates to test for the presence of our targeted mRNA marker. Samples were kept at dry dark conditions to be tested at different time intervals (24 hours, one week, three weeks and four weeks) for detection and relative quantification of the targeted marker by RT PCR. The targeted marker could not be detected in blood samples. The targeted marker showed the highest mean value after 24 hours (11.90 ± 2.42) and the lowest mean value (7.56 ± 2.56) after three weeks. No marker could be detected at four weeks. This study verified the high specificity and sensitivity of mRNA marker in the skin at different storage times up to three weeks under the study conditions.

Keywords: human skin, late cornified envelope gene 1C, mRNA marker, time intervals

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3209 Hand Detection and Recognition for Malay Sign Language

Authors: Mohd Noah A. Rahman, Afzaal H. Seyal, Norhafilah Bara

Abstract:

Developing a software application using an interface with computers and peripheral devices using gestures of human body such as hand movements keeps growing in interest. A review on this hand gesture detection and recognition based on computer vision technique remains a very challenging task. This is to provide more natural, innovative and sophisticated way of non-verbal communication, such as sign language, in human computer interaction. Nevertheless, this paper explores hand detection and hand gesture recognition applying a vision based approach. The hand detection and recognition used skin color spaces such as HSV and YCrCb are applied. However, there are limitations that are needed to be considered. Almost all of skin color space models are sensitive to quickly changing or mixed lighting circumstances. There are certain restrictions in order for the hand recognition to give better results such as the distance of user’s hand to the webcam and the posture and size of the hand.

Keywords: hand detection, hand gesture, hand recognition, sign language

Procedia PDF Downloads 178
3208 Analysis of Tactile Perception of Textiles by Fingertip Skin Model

Authors: Izabela L. Ciesielska-Wrόbel

Abstract:

This paper presents finite element models of the fingertip skin which have been created to simulate the contact of textile objects with the skin to gain a better understanding of the perception of textiles through the skin, so-called Hand of Textiles (HoT). Many objective and subjective techniques have been developed to analyze HoT, however none of them provide exact overall information concerning the sensation of textiles through the skin. As the human skin is a complex heterogeneous hyperelastic body composed of many particles, some simplifications had to be made at the stage of building the models. The same concerns models of woven structures, however their utilitarian value was maintained. The models reflect only friction between skin and woven textiles, deformation of the skin and fabrics when “touching” textiles and heat transfer from the surface of the skin into direction of textiles.

Keywords: fingertip skin models, finite element models, modelling of textiles, sensation of textiles through the skin

Procedia PDF Downloads 342
3207 Penetration Depth Study of Linear Siloxanes through Human Skin

Authors: K. Szymkowska, K. Mojsiewicz- Pieńkowska

Abstract:

Siloxanes are a common ingredients in medicinal products used on the skin, as well as cosmetics. It is widely believed that the silicones are not capable of overcoming the skin barrier. The aim of the study was to verify the possibility of penetration and permeation of linear siloxanes through human skin and determine depth penetration limit of these compounds. Based on the results it was found that human skin is not a barrier for linear siloxanes. PDMS 50 cSt was not identified in the dermis suggests that this molecular size of silicones (3780Da) is safe when it is used in the skin formulations.

Keywords: linear siloxanes, methyl siloxanes, skin penetration, skin permeation

Procedia PDF Downloads 290
3206 Hand Gesture Detection via EmguCV Canny Pruning

Authors: N. N. Mosola, S. J. Molete, L. S. Masoebe, M. Letsae

Abstract:

Hand gesture recognition is a technique used to locate, detect, and recognize a hand gesture. Detection and recognition are concepts of Artificial Intelligence (AI). AI concepts are applicable in Human Computer Interaction (HCI), Expert systems (ES), etc. Hand gesture recognition can be used in sign language interpretation. Sign language is a visual communication tool. This tool is used mostly by deaf societies and those with speech disorder. Communication barriers exist when societies with speech disorder interact with others. This research aims to build a hand recognition system for Lesotho’s Sesotho and English language interpretation. The system will help to bridge the communication problems encountered by the mentioned societies. The system has various processing modules. The modules consist of a hand detection engine, image processing engine, feature extraction, and sign recognition. Detection is a process of identifying an object. The proposed system uses Canny pruning Haar and Haarcascade detection algorithms. Canny pruning implements the Canny edge detection. This is an optimal image processing algorithm. It is used to detect edges of an object. The system employs a skin detection algorithm. The skin detection performs background subtraction, computes the convex hull, and the centroid to assist in the detection process. Recognition is a process of gesture classification. Template matching classifies each hand gesture in real-time. The system was tested using various experiments. The results obtained show that time, distance, and light are factors that affect the rate of detection and ultimately recognition. Detection rate is directly proportional to the distance of the hand from the camera. Different lighting conditions were considered. The more the light intensity, the faster the detection rate. Based on the results obtained from this research, the applied methodologies are efficient and provide a plausible solution towards a light-weight, inexpensive system which can be used for sign language interpretation.

Keywords: canny pruning, hand recognition, machine learning, skin tracking

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3205 Maximum Entropy Based Image Segmentation of Human Skin Lesion

Authors: Sheema Shuja Khattak, Gule Saman, Imran Khan, Abdus Salam

Abstract:

Image segmentation plays an important role in medical imaging applications. Therefore, accurate methods are needed for the successful segmentation of medical images for diagnosis and detection of various diseases. In this paper, we have used maximum entropy to achieve image segmentation. Maximum entropy has been calculated using Shannon, Renyi, and Tsallis entropies. This work has novelty based on the detection of skin lesion caused by the bite of a parasite called Sand Fly causing the disease is called Cutaneous Leishmaniasis.

Keywords: shannon, maximum entropy, Renyi, Tsallis entropy

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3204 Pre-Operative Tool for Facial-Post-Surgical Estimation and Detection

Authors: Ayat E. Ali, Christeen R. Aziz, Merna A. Helmy, Mohammed M. Malek, Sherif H. El-Gohary

Abstract:

Goal: Purpose of the project was to make a plastic surgery prediction by using pre-operative images for the plastic surgeries’ patients and to show this prediction on a screen to compare between the current case and the appearance after the surgery. Methods: To this aim, we implemented a software which used data from the internet for facial skin diseases, skin burns, pre-and post-images for plastic surgeries then the post- surgical prediction is done by using K-nearest neighbor (KNN). So we designed and fabricated a smart mirror divided into two parts a screen and a reflective mirror so patient's pre- and post-appearance will be showed at the same time. Results: We worked on some skin diseases like vitiligo, skin burns and wrinkles. We classified the three degrees of burns using KNN classifier with accuracy 60%. We also succeeded in segmenting the area of vitiligo. Our future work will include working on more skin diseases, classify them and give a prediction for the look after the surgery. Also we will go deeper into facial deformities and plastic surgeries like nose reshaping and face slim down. Conclusion: Our project will give a prediction relates strongly to the real look after surgery and decrease different diagnoses among doctors. Significance: The mirror may have broad societal appeal as it will make the distance between patient's satisfaction and the medical standards smaller.

Keywords: k-nearest neighbor (knn), face detection, vitiligo, bone deformity

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3203 Skin Care through Ayurveda

Authors: K. L. Virupaksha Gupta

Abstract:

Ayurveda offers a holistic outlook regarding skin care. Most Initial step in Ayurveda is to identify the skin type and care accordingly which is highly personalized. Though dermatologically there are various skin type classifications such Baumann skin types (based on 4 parameters i) Oily Vs Dry ii) Sensitive Vs Resistant iii) Pigmented Vs Non-Pigmented iv) Wrinkled Vs Tight (Unwrinkled) etc but Skin typing in Ayurveda is mainly determined by the prakriti (constitution) of the individual as well as the status of Doshas (Humors) which are basically of 3 types – i.e Vata Pitta and Kapha,. Difference between them is mainly attributed to the qualities of each dosha (humor). All the above said skin types can be incorporated under these three types. The skin care modalities in each of the constitution vary greatly. Skin of an individual of Vata constitution would be lustreless, having rough texture and cracks due to dryness and thus should be given warm and unctuous therapies and oil massage for lubrication and natural moisturizers for hydration. Skin of an individual of Pitta constitution would look more vascular (pinkish), delicate and sensitive with a fair complexion, unctuous and tendency for wrinkles and greying of hair at an early age and hence should be given cooling and nurturing therapies and should avoid tanning treatments. Skin of an individual of kapha constitution will have oily skin, they are delicate and look beautiful and radiant and hence these individuals would require therapies to mainly combat oily skin. Hence, the skin typing and skin care in Ayurveda is highly rational and scientific.

Keywords: Ayurveda, dermatology, Dosha, skin types

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3202 A Survey and Analysis on Inflammatory Pain Detection and Standard Protocol Selection Using Medical Infrared Thermography from Image Processing View Point

Authors: Mrinal Kanti Bhowmik, Shawli Bardhan Jr., Debotosh Bhattacharjee

Abstract:

Human skin containing temperature value more than absolute zero, discharges infrared radiation related to the frequency of the body temperature. The difference in infrared radiation from the skin surface reflects the abnormality present in human body. Considering the difference, detection and forecasting the temperature variation of the skin surface is the main objective of using Medical Infrared Thermography(MIT) as a diagnostic tool for pain detection. Medical Infrared Thermography(MIT) is a non-invasive imaging technique that records and monitors the temperature flow in the body by receiving the infrared radiated from the skin and represent it through thermogram. The intensity of the thermogram measures the inflammation from the skin surface related to pain in human body. Analysis of thermograms provides automated anomaly detection associated with suspicious pain regions by following several image processing steps. The paper represents a rigorous study based survey related to the processing and analysis of thermograms based on the previous works published in the area of infrared thermal imaging for detecting inflammatory pain diseases like arthritis, spondylosis, shoulder impingement, etc. The study also explores the performance analysis of thermogram processing accompanied by thermogram acquisition protocols, thermography camera specification and the types of pain detected by thermography in summarized tabular format. The tabular format provides a clear structural vision of the past works. The major contribution of the paper introduces a new thermogram acquisition standard associated with inflammatory pain detection in human body to enhance the performance rate. The FLIR T650sc infrared camera with high sensitivity and resolution is adopted to increase the accuracy of thermogram acquisition and analysis. The survey of previous research work highlights that intensity distribution based comparison of comparable and symmetric region of interest and their statistical analysis assigns adequate result in case of identifying and detecting physiological disorder related to inflammatory diseases.

Keywords: acquisition protocol, inflammatory pain detection, medical infrared thermography (MIT), statistical analysis

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3201 Computer Countenanced Diagnosis of Skin Nodule Detection and Histogram Augmentation: Extracting System for Skin Cancer

Authors: S. Zith Dey Babu, S. Kour, S. Verma, C. Verma, V. Pathania, A. Agrawal, V. Chaudhary, A. Manoj Puthur, R. Goyal, A. Pal, T. Danti Dey, A. Kumar, K. Wadhwa, O. Ved

Abstract:

Background: Skin cancer is now is the buzzing button in the field of medical science. The cyst's pandemic is drastically calibrating the body and well-being of the global village. Methods: The extracted image of the skin tumor cannot be used in one way for diagnosis. The stored image contains anarchies like the center. This approach will locate the forepart of an extracted appearance of skin. Partitioning image models has been presented to sort out the disturbance in the picture. Results: After completing partitioning, feature extraction has been formed by using genetic algorithm and finally, classification can be performed between the trained and test data to evaluate a large scale of an image that helps the doctors for the right prediction. To bring the improvisation of the existing system, we have set our objectives with an analysis. The efficiency of the natural selection process and the enriching histogram is essential in that respect. To reduce the false-positive rate or output, GA is performed with its accuracy. Conclusions: The objective of this task is to bring improvisation of effectiveness. GA is accomplishing its task with perfection to bring down the invalid-positive rate or outcome. The paper's mergeable portion conflicts with the composition of deep learning and medical image processing, which provides superior accuracy. Proportional types of handling create the reusability without any errors.

Keywords: computer-aided system, detection, image segmentation, morphology

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3200 Fabrication of Optical Tissue Phantoms Simulating Human Skin and Their Application

Authors: Jihoon Park, Sungkon Yu, Byungjo Jung

Abstract:

Although various optical tissue phantoms (OTPs) simulating human skin have been actively studied, their completeness is unclear because skin tissue has the intricate optical property and complicated structure disturbing the optical simulation. In this study, we designed multilayer OTP mimicking skin structure, and fabricated OTP models simulating skin-blood vessel and skin pigmentation in the skin, which are useful in Biomedical optics filed. The OTPs were characterized with the optical property and the cross-sectional structure, and analyzed by using various optical tools such as a laser speckle imaging system, OCT and a digital microscope to show the practicality. The measured optical property was within 5% error, and the thickness of each layer was uniform within 10% error in micrometer scale.

Keywords: blood vessel, optical tissue phantom, optical property, skin tissue, pigmentation

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3199 Classification of Red, Green and Blue Values from Face Images Using k-NN Classifier to Predict the Skin or Non-Skin

Authors: Kemal Polat

Abstract:

In this study, it has been estimated whether there is skin by using RBG values obtained from the camera and k-nearest neighbor (k-NN) classifier. The dataset used in this study has an unbalanced distribution and a linearly non-separable structure. This problem can also be called a big data problem. The Skin dataset was taken from UCI machine learning repository. As the classifier, we have used the k-NN method to handle this big data problem. For k value of k-NN classifier, we have used as 1. To train and test the k-NN classifier, 50-50% training-testing partition has been used. As the performance metrics, TP rate, FP Rate, Precision, recall, f-measure and AUC values have been used to evaluate the performance of k-NN classifier. These obtained results are as follows: 0.999, 0.001, 0.999, 0.999, 0.999, and 1,00. As can be seen from the obtained results, this proposed method could be used to predict whether the image is skin or not.

Keywords: k-NN classifier, skin or non-skin classification, RGB values, classification

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3198 The Effect of Skin to Skin Contact Immediately to Maternal Breastfeeding Self-Efficacy after Cesarean Section

Authors: D. Triana, I. N. Rachmawati, L. Sabri

Abstract:

Maternal breastfeeding self-efficacy is positively associated with increased duration of breastfeeding in different cultures and age groups. This study aims to determine the effect of skin-to-skin contact immediately after the cesarean section on maternal breastfeeding self-efficacy. The research design is Posttest quasi-experimental research design only with control groups involving 52 women with consecutive sampling in Langsa-Aceh. The data collected through breastfeeding Self-Efficacy Scale-Short Form. The results of Independent t-test showed a significant difference in the mean values of maternal breastfeeding self-efficacy in the intervention group and the control group (59.00 ± 6.54; 49.62 ± 7.78; p= 0.001). Skin to skin contact is proven to affect the maternal breastfeeding self-efficacy after cesarean section significantly.

Keywords: breastfeeding self-efficacy, cesarean section, skin to skin contact, immediately

Procedia PDF Downloads 228
3197 Noise Detection Algorithm for Skin Disease Image Identification

Authors: Minakshi Mainaji Sonawane, Bharti W. Gawali, Sudhir Mendhekar, Ramesh R. Manza

Abstract:

People's lives and health are severely impacted by skin diseases. A new study proposes an effective method for identifying the different forms of skin diseases. Image denoising is a technique for improving image quality after it has been harmed by noise. The proposed technique is based on the usage of the wavelet transform. Wavelet transform is the best method for analyzing the image due to the ability to split the image into the sub-band, which has been used to estimate the noise ratio at the noisy image. According to experimental results, the proposed method presents the best values for MSE, PSNR, and Entropy for denoised images. we can found in Also, by using different types of wavelet transform filters is make the proposed approach can obtain the best results 23.13, 20.08, 50.7 for the image denoising process

Keywords: MSE, PSNR, entropy, Gaussian filter, DWT

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3196 Quality Rabbit Skin Gelatin with Acetic Acid Extract

Authors: Wehandaka Pancapalaga

Abstract:

This study aimed to analyze the water content, yield, fat content, protein content, viscosity, gel strength, pH, melting and organoleptic rabbit skin gelatin with acetic acid extraction levels are different. The materials used in this study were Rex rabbit skin male. Treatments that P1 = the extraction of acetic acid 2% (v / v); P2 = the extraction of acetic acid 3% (v / v); P3 = the extraction of acetic acid 4 % (v / v). P5 = the extraction of acetic acid 5% (v / v). The results showed that the greater the concentration of acetic acid as the extraction of rabbit skin can reduce the water content and fat content of rabbit skin gelatin but increase the protein content, viscosity, pH, gel strength, yield and melting point rabbit skin gelatin. texture, color and smell of gelatin rabbits there were no differences with cow skin gelatin. The results showed that the quality of rabbit skin gelatin accordance Indonesian National Standard (SNI). Conclusion 5% acetic acid extraction produces the best quality gelatin.

Keywords: gelatin, skin rabbit, acetic acid extraction, quality

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3195 Dermatological Study on Risk Factors for Pruritic Skin: Skin Properties of Elderly

Authors: Dianis Wulan Sari, Takeo Minematsu, Mikako Yoshida, Hiromi Sanada

Abstract:

Introduction: Pruritus is diagnosed as itching without macroscopic abnormalities on skin. It is the most skin complaint of elderly people. In the present study, we conducted a dermatological study to examine the risk factors of pruritic skin and predicted how to prevent pruritus especially in the elderly population. Pruritus is caused several types of inflammation, including epidermal innate immunity based on keratinocyte responses and acquired immunity regulated by type 1 or 2 helper T (Th) cells. The triggers of pruritus differ among inflammation types, therefore we did separately assess the pruritus-associated factors of each inflammation type in an effort to contribute to the identification of intervention targets for preventing pruritus. Therefore, this study aimed to investigate the factors related with actual condition of pruritic skin by examine the skin properties. Method: This study was conducted in elderly population of Indonesian nursing home. Basic characteristics and behaviors were obtained by interview. The properties of pruritic skin were collected by examination of skin biomarker using skin blotting as novel method of non-invasive skin assessment method and examination of skin barrier function using stratum corneum hydration and skin pH. Result: The average age of participants was 74 years with independent status was 66.8%. Age (β = -0.130, p = 0.044), cumulative lifetime sun exposure (β = 0.145, p = 0.026), bathing duration (β = 0.151, p = 0.022), clothing change frequency (β = 0.135, p = 0.029), and clothing type (β = -0.139, p = 0.021) were risk factors of pruritic skin in multivariate analysis. Conclusion: Risk factors of pruritic skin in elderly population were caused by internal factors such as skin senescence and external factors such as sun exposure, hygiene care and skin care behavior.

Keywords: aging, hygiene care, pruritus, skin care, sun exposure

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3194 Skin Diseases in the Rural Areas in Nepal; Impact on Quality of Life

Authors: Dwarika P. Shrestha, Dipendra Gurung, Rushma Shrestha, Inger Rosdahl

Abstract:

Introduction: Skin diseases are one of the most common health problems in Nepal. The objectives of this study are to determine the prevalence of skin diseases and impact on quality of life in rural areas in Nepal. Materials and methods: A house-to-house survey was conducted, to obtain socio-demographic data and identify individuals with skin diseases, followed by health camps, where the villagers were examined. A pilot study was conducted in one village, which was then extended to 10 villages in 4 districts. To assess the impact on quality of life, the villagers were interviewed with Skin Disease Disability Index. This is a questionnaire developed and validated by the authors for use in Nepal. Results: In the pilot study, the overall prevalence of skin diseases was 20.1% (645/3207). In the additional 10 villages with 7348 (3651/3787 m/f) inhabitants, 1862 (721/1141 m/f, mean age 31.4 years) had one or more skin diseases. The overall prevalence of skin diseases was 25%. The most common skin disease categories were eczemas (13.7%, percentage among all inhabitants) pigment disorders (6.8%), fungal infections (4.9%), nevi (3.7%) and urticaria (2.9%). These five most common skin disease categories comprise 71% of all skin diseases seen in the study. The mean skin disease disability index score was 13.7, indicating very large impact on the quality of life. Conclusions: This population-based study shows that skin diseases are very common in the rural areas of Nepal and have significant impact on quality of life. Targeted intervention at the primary health care level should help to reduce the health burden due to skin diseases.

Keywords: prevalence and pattern of skin diseases, impact on quality of life, rural Nepal, interventions

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3193 Prevalence and Potential Risk Factors Associated with Skin Affection in Donkeys

Authors: Mohamed Z. Sayed-Ahmed, Ahmed M. Ahdy, Emad E. Younis, Sabry A. El-Khodary

Abstract:

Little research information is available on the prevalence of diseases of donkeys in Egypt. Across sectional study was undertaken between March 2009 and February 2010 to verify the prevalence of skin affection of donkeys. A total of 1134 donkeys in northern Egypt were investigated. A questionnaire was constructed to verify the number of infected contact animals as well as the associated factors. Physical examination was carried out, and the distribution of skin lesions was recorded. Skin scraping and biopsy were obtained to perform bacteriological, mycological, and histopathological examinations. Thirty-five (3.09%) out of 1134 noticed donkeys had skin affections including mange (18/35), dermatophytosis (6/35), bacterial dermatitis (6/35) urticaria (2/35) and allergic dermatitis (3/35). The present results indicate that mange and dermatophytosis are the prevalent skin diseases in donkeys. Contact with other animal species of contaminated environment may contribute to the occurrence of the diseases.

Keywords: donkeys, Egypt, prevalence, skin affection

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3192 Pufferfish Skin Collagens and Their Role in Inflation

Authors: Kirti, Samanta Sekhar Khora

Abstract:

Inflation serves different purposes in different organisms and adds beauty to their behavioral attributes. Pufferfishes are also known as blowfish, swellfish, and globefish due to their remarkable ability to puff themselves up like a balloon when threatened. This ability to inflate can be correlated with anatomical features that are unique to pufferfishes. Pufferfish skin provides a rigid framework to support the body contents and a flexible covering to allow whatever changes are necessary for remarkable inflation mechanism. Skin, the outer covering of animals is made up of collagen fibers arranged in more or less ordered arrays. The ventral skin of pufferfish stretches more than dorsal skin during inflation. So, this study is of much of the interest in comparing the structure and mechanical properties of these two skin regions. The collagen fibers were found to be arranged in different ordered arrays for ventral and dorsal skin and concentration of fibers were also found to be different for these two skin parts. Scanning electron microscopy studies of the ventral skin showed a unidirectional arrangement of the collagen fibers, which provide more stretching capacity. Dorsal skin, on the other hand, has an orthogonal arrangement of fibers. This provides more stiffness to the ventral skin at the time of inflation. In this study, the possible role of collagen fibers was determined which significantly contributed to the remarkable inflation mechanism of pufferfishes.

Keywords: collagen, histology, inflation, pufferfish, scanning electron microscopy, Small-Angle X-Ray Scattering (SAXS), transmission electron microscopy

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3191 Preparation and Characterization of Water-in-Oil Nanoemulsion of 5-Fluorouracil to Enhance Skin Permeation for Treatment of Skin Diseases.

Authors: P. S. Rajinikanth, Shobana Mariappan, Jestin Chellian

Abstract:

The objective of the study was to prepare and characterize a water-in-oil nano emulsion of 5-Fluorouracil (5FU) to enhance the skin penetration. The present study describes a nano emulsion of 5FU using Capyrol PGMC, Transcutol HP and PEG 400 as oil, surfactant and co-surfactant, respectively. The optimized formulations were further evaluated for heating cooling cycle, centrifugation studies, freeze thaw cycling, particle size distribution and zeta potential in order to confirm the stability of the optimized nano emulsions. The in-vitro characterization results showed that the droplets of prepared formulation were ~100 nm with ± 15 zeta potential. In vitro skin permeation studies was conducted in albino mice skin. Significant increase in permeability parameters was also observed in nano emulsion formulations (P<0.05). The steady-state flux (Jss), enhancement ration and permeability coefficient (Kp) for optimized nano emulsion formulation (FU2, FU1, 1:1 S mix were found to be 24.21 ±2.45 μg/cm2/h, 3.28±0.87 & 19.52±1.87 cm/h, respectively), which were significant compared with conventional gel. The in vitro and in vivo skin deposition studies in rat indicated that the amount of drug deposited from the nano emulsion (292.45 µg/cm2) in skin was significant (P<0.05) an increased as compared to a conventional 5FU gel (121.42 µg/cm2). The skin irritation study using rat skin showed that the mean irritation index of the nano emulsion reduced significantly (P<0.05) as compared with conventional gel contain 1% 5FU. The results from this study suggest that a water-in-oil nano emulsion could be safely used to promote skin penetration of 5FU following topical application.

Keywords: nano emulsion, controlled release, 5 fluorouracil, skin penetration, skin irritation

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3190 The Effects of Topically-Applied Skin Moisturizer on Striae Gravidarum in East Indian Women

Authors: Dipanshu Sur, Ratnabali Chakravorty

Abstract:

Background: Striae result from rapid expansion of the underlying tissue, e.g. during puberty, pregnancy or rapid weight gain. Prior data indicate that the incidence of stretch marks in Indian women is 77%.The hormonal and genetic factors are associated with their appearance. Recently that has been found skin extensibility, elasticity and rupture were strongly influenced by the water content of dermis and epidermis cells. Objective: The objectives were to assess the effects of topical treatments applied during pregnancy on the later development of stretch marks. Materials and methods: An open, prospective, randomized study was done on 120 pregnant women in whom skin elasticity and hydration as well as striae presence or apparition were measured at baseline and periodically until delivery. Patients were randomly assigned to application in wet skin cream, or in dry skin conditions. Results: The average basal hydration was 42 ±13 IU and the final was 46 ± 6 IU (P = 0.0325; 95% CI: -7.66 to -0.34), which difference was statistically significant. By measuring the moisture in the control region (forearm) a basal reading of 40 ± 9 IU and end of study of 38 ± 6; (p = 0.1547; 95% CI: -0.77 to 4.77) and this difference was considered to be not statistically significant. It was observed that at the end of the study, 55% women without ridges; mild ridges 5%; 36% moderate, and 4%, severe ridges. The proportion of women without grooves was 54% when the cream was applied studied wet skin and 45% when the cream was applied on dry skin. Conclusion: It was shown that cream under study increased hydration and elasticity of abdominal skin consequently in all subjects. This effect is more significant (54%) when the cream is applied to damp skin.

Keywords: striae gravidarum, skin moisturizer, skin hydration, skin elasticity

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3189 Clinical Factors of Quality Switched Ruby Laser Therapy for Lentigo Depigmentation

Authors: SunWoo Lee, TaeBum Lee, YoonHwa Park, YooJeong Kim

Abstract:

Solar lentigines appear predominantly on chronically sun-exposed areas of skin, such as the face and the back of the hands. Among the several ways to lentigines treatment, quality-switched lasers are well-known effective treatment for removing solar lentigines. The present pilot study was therefore designed to assess the efficacy of quality-switched ruby laser treatment of such lentigines compare between pretreatment and posttreatment of skin brightness. Twenty-two adults with chronic sun-damaged skin (mean age 52.8 years, range 37–74 years) were treated at the Korean site. A 694 nm Q-switched ruby laser was used, with the energy density set from 1.4 to 12.5 J/cm2, to treat solar lentigines. Average brightness of skin color before ruby laser treatment was 137.3 and its skin color was brightened after ruby laser treatment by 150.5. Also, standard deviation of skin color was decreased from 17.8 to 16.4. Regarding the multivariate model, age and energy were identified as significant factors for skin color brightness change in lentigo depigmentation by ruby laser treatment. Their respective odds ratios were 1.082 (95% CI, 1.007–1.163), and 1.431 (95% CI, 1.051–1.946). Lentigo depigmentation treatment using ruby lasers resulted in a high performance in skin color brightness. Among the relative factors involve with ruby laser treatment, age and energy were the most effective factors which skin color change to brighter than pretreatment.

Keywords: depigmentation, lentigine, quality switched ruby laser, skin color

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3188 Efficient Signal Detection Using QRD-M Based on Channel Condition in MIMO-OFDM System

Authors: Jae-Jeong Kim, Ki-Ro Kim, Hyoung-Kyu Song

Abstract:

In this paper, we propose an efficient signal detector that switches M parameter of QRD-M detection scheme is proposed for MIMO-OFDM system. The proposed detection scheme calculates the threshold by 1-norm condition number and then switches M parameter of QRD-M detection scheme according to channel information. If channel condition is bad, the parameter M is set to high value to increase the accuracy of detection. If channel condition is good, the parameter M is set to low value to reduce complexity of detection. Therefore, the proposed detection scheme has better trade off between BER performance and complexity than the conventional detection scheme. The simulation result shows that the complexity of proposed detection scheme is lower than QRD-M detection scheme with similar BER performance.

Keywords: MIMO-OFDM, QRD-M, channel condition, BER

Procedia PDF Downloads 205