Mobile Camera Research Articles

Nonwoven fiber meshes for oxygen sensing

Accurate oxygen sensing and cost-effective fabrication are crucial for the adoption of wearable devices inside and outside the clinical setting. Here we introduce a simple strategy to create nonwoven polymeric fibrous mats for a notable contribution towards addressing this need. Although morphological manipulation of polymers for cell culture proliferation is commonplace, especially in the field of regenerative medicine, non-woven structures have not been used for oxygen sensing. We used an airbrush spraying, i.e. solution blowing, to obtain nonwoven fiber meshes embedded with a phosphorescent dye. The fibers serve as a polymer host for the phosphorescent dye and are shown to be non-cytotoxic. Different composite fibrous meshes were prepared and favorable mechanical and oxygen-sensing properties were demonstrated. A Young's modulus of 9.8 MPa was achieved and the maximum oxygen sensitivity improved by a factor of ∼2.9 compared to simple drop cast film. The fibers were also coated with silicone rubbers to produce mechanically robust sensing films. This reduced the sensing performance but improved flexibility and mechanical properties. Lastly, we are able to capture oxygen concentration maps via colorimetry using a smartphone camera, which should offer unique advantages in wider usage. Overall, the introduced composite fiber meshes show a potential to significantly improve cell cultures and healthcare monitoring via absolute oxygen sensing.

A hybrid catalyst-triggered cascade reaction for cholesterol detection using a smartphone-based miniature fluorescent apparatus

A new hybrid biological-chemical catalyst, magnetic nanoparticles functionalized with cholesterol oxidase (Fe3O4/APTES/ChOx), was developed for cholesterol detection. In the presence of cholesterol, the enzyme produced H2O2, which facilitated the generation of fluorescent molecules from the fluorogenic substrate with the assistance of Fe3O4 nanoparticles. A smartphone camera with a miniature fluorescent apparatus was used to assess fluorescence emission. Then, a smartphone application was employed to translate the fluorescence intensity to the red, green, and blue (RGB) domain. The developed approach achieved excellent selectivity and acceptable performances while supporting an onsite analysis approach. The practical operational range spanned from 5 to 100 nM, with a detection limit of 0.85 nM. Fe3O4/APTES/ChOx was applied for up to four replicates of reuse and demonstrated stability for at least 30 days. The applicability of the method was evaluated in milk samples, and the results were in accordance with the reference method.

TinyMSI: A cost-effective handheld device for non-contact diabetic wound monitoring

Devices characterizing diabetic foot ulcers and other wounds currently fall into two categories. Expensive clinically-oriented devices that use mature technologies such as X-ray CT and hyperspectral imaging or low-cost solutions that leverage deep learning to infer wound characterization from conventional smartphone camera images or simple surrogate markers. Mature medical-grade devices are too expensive for primary care and assisted living facilities. Low-cost solutions rely too much on indirect statistical inference to be clinically suitable. Therefore, we propose a device that leverages mature, clinically suitable optical technologies to provide a solution for these facilities. Recognizing that individual combinations of 1–2 bands of active illumination are used individually to capture pulsation, vascular, and oxygenation images. We combine all these bands into a single multispectral lighting source to create a multi-functional, reliable device for wound assessment. We selected these bands to leverage CMOS cameras near orthogonality between the RGB channels and leverage that CMOS cameras can also sense near IR light if a filter is not present, reducing overall system complexity and needed bands. For each function, the necessary lights are turned on, and the captured raw video is then fed to the corresponding sequence of image processing steps. No deep learning models are used, so large training datasets are not required. Our device is also small, lightweight, and handheld.

Development of GWIDO: An Augmented Reality-based Mobile Application for Historical Tourism

This research aimed to design and reconstruct a business model for an augmented reality (AR) camera mobile application for historical tourism at Keraton Kasepuhan Cirebon. The goal was to utilize AR technology to provide an immersive and informative experience for tourists. The research addressed several main problems, including navigation and historical information through object tracking, by implementing an online application with features such as Indonesian and English language instructions to better serve domestic and foreign tourists. The research also aimed to investigate the benefits of using AR technology for object tracking and navigation and to explore how these aspects could be related to creating a formula that supports each other in addressing the formulated problems. Through the development of the GWIDO application, a positive impact on the development of historical tourist attractions was observed. This can be seen from the usefulness of its features such as AR navigation, which can be used as a virtual guide. The data collected was used to design and reconstruct the business model, which was implemented and tested to collect additional data for analysis. The final results of the research showed that the AR camera mobile application was effective in providing an immersive and informative experience for tourists. The redesigned business model improved the utilization of AR technology in the tourism industry. Based on the test results, the average response time for object distance between 0.1 meters to 0.5 meters was between 1.45 to 2.07 seconds, and the average time for object distance from visitors was between 3.15 to 4.71 seconds with a confidence level of 95%. Meanwhile, testing for navigation features using augmented reality is very dependent on the internet signal used on the user's device. The level of accuracy of objects that have been placed at certain coordinates is determined by how well the internet network performs, allowing objects to appear precisely according to their coordinates.

Estimating drinking water turbidity using images collected by a smartphone camera

ABSTRACT The lack of robust water quality data in drinking water services in many low-income settings can be attributed to inadequate funding for regular monitoring using analytical equipment. Turbidity is an indicator that is relatively quick and easy to measure; however, it still requires a turbidimeter and a trained operator. This study developed an entire smartphone camera-based application to measure turbidity in drinking water, removing both the need for external equipment and skilled labour. The application was created using a convolutional neural network, able to classify water samples into eight turbidity bins ranging from 0 to 40 NTU. The turbidity of the samples was created using formazine and kaolin clay suspensions. The in-built camera of a smartphone was used to capture images of water samples with known turbidity values. This algorithm was then embedded in a smartphone application, thereby providing an easy-to-use tool for users to estimate turbidity. Specifically, the protocol for using this application was developed with the intention that it will be used in low-resource settings by laypersons. Formazine samples achieved a turbidity classification accuracy of 98.7%, while kaolin clay samples achieved 90.9% accuracy using this method, which provides an encouraging proof of concept, as justification for further testing and improvements.

Monolingual Used on The Historical Sites in Dili, Timor-Leste: A Study of Linguistics Landscape

Timor-Leste which is further called (TL) is also well-known as a multilingual and multicultural country. Besides, Timor-Leste also has 32 local languages and 3 foreign languages such as Portuguese, Bahasa Indoenesia and English. Portuguese is used as the official language however, Bahasa Indonesia and English are used as working languages. This research aimed to determine and to explore the predominant language used in historical sites in Dili. This is a qualitative research and the data were collected by using taking pictures technique with a mobile phone camera. After all the data were collected then, they were analyzed by using qualitaive descriptive method. The Results in this research showed that there are 6 historical sites found in Dili. Tetum language is used as monolingual to describe and explain the brutal action done by the Indonesian Military during the Indonesian occupation in Timor-Leste.

Towards Automating Personal Exercise Assessment and Guidance with Affordable Mobile Technology.

Physical activity (PA) offers many benefits for human health. However, beginners often feel discouraged when introduced to basic exercise routines. Due to lack of experience and personal guidance, they might abandon efforts or experience musculoskeletal injuries. Additionally, due to phenomena such as pandemics and limited access to supervised exercise spaces, especially for the elderly, the need to develop personalized systems has become apparent. In this work, we develop a monitored physical exercise system that offers real-time guidance and recommendations during exercise, designed to assist users in their home environment. For this purpose, we used posture estimation interfaces that recognize body movement using a computer or smartphone camera. The chosen pose estimation model was BlazePose. Machine learning and signal processing techniques were used to identify the exercise currently being performed. The performances of three machine learning classifiers were evaluated for the exercise recognition task, achieving test-set accuracy between 94.76% and 100%. The research methodology included kinematic analysis (KA) of five selected exercises and statistical studies on performance and range of motion (ROM), which enabled the identification of deviations from the expected exercise execution to support guidance. To this end, data was collected from 57 volunteers, contributing to a comprehensive understanding of exercise performance. By leveraging the capabilities of the BlazePose model, an interactive tool for patients is proposed that could support rehabilitation programs remotely.

A cost-effective approach to measurements of fluorophore temperature sensitivity and temperature change with reasonable accuracy

The demand for measuring fluorophore temperature sensitivity and temperature change in chemical or biological samples has spurred the search for effective methods. While infrared (IR) light-based thermal devices are popular, they are limited to surface temperature measurement. Fluorescence-based thermometry, which utilizes intensity, lifetime, polarization, and spectrum change, provides the temperature information directly from the samples and can have high temporal and spatial resolution. However, measuring fluorescence can be tricky and expensive. A cost-effective approach to achieving reasonable accuracy is highly desired. This study introduces such an approach, employing a light-emitting diode (LED) for fluorophore excitation and a laser diode (LD) for sample heating, with a phone camera recording fluorescence changes. A data processing method converts the video into digital data, processed through digital filters. Utilizing a small-volume cuvette enhances heating efficiency. This study serves as a practical guide for inexperienced individuals, including students, instructors, and researchers, facilitating entry into the field and navigating the complexities of fluorescence-based thermometry.

Identification of Pests and Diseases on Anthurium Jemani Ornamental Plants in the Ngledoksari Tawangmangu Tourism

Anthurium decorative plants are presently exceptionally famous among fancy plant darlings, both from the appeal of the kind and variety and the exorbitant cost. In spite of the fact that nuisances and sicknesses in anthurium are not extremely upsetting, assuming left unrestrained it will significantly impede the magnificence, hinder development and be unfavorable to authorities and venders/business people of these elaborate plants. The motivation behind this study was to decide the sorts of nuisances and sicknesses that assault anthurium plants. This exploration was completed in the Desa Wisata NgledoksariTourism Town, Tawangmangu Regime, Karanganyar Rule, for 30 days from Saturday, December 01 to December 30, 2023. This study utilized 17 examples of Anthurium plants. The apparatuses utilized were cellphone cameras and writing material. The factors that will be noticed are nuisances and sicknesses that assault Anthurium. This examination utilized perception and interview methode, the information got were broke down by subjective clear. The consequences of this study found a few vermin and illnesses on anthurium establishes that made the plant leaves and blossoms have openings, withered, yellowed spots, foul, and caused hindered development. The irritations found were caterpillars and snails, while the sicknesses included growth, chlorisis, leaf rust, anthracnose, wavy leaves, and consumed leaves.

UbiHeart: A novel approach for non-invasive blood pressure monitoring through real-time facial video

Monitoring blood pressure (BP) is an essential component of evaluating cardiovascular health, aiding in the early detection and management of hypertension-related complications. Traditional methods of BP measurement often involve invasive or cumbersome devices, leading to discomfort and reduced compliance. We propose a framework to monitor BP non-invasively, analyzing the face video captured by a webcam or smartphone camera leveraging the relationship of image-based Pulse Transit Time (iPTT) and Heart Rate Variability (HRV) with BP. We have built a dataset of 90 sets of collected videos using a mobile phone front camera and BP data from a standard digital BP monitor from 12 individuals from an approved Institutional Review Board (IRB) to evaluate our system. We have got a Mean Absolute Error (MAE) of 10.35+/−2.5 mmHg for systolic BP (SBP) and 7.8+/−1.5 mmHg for diastolic BP (DBP) while using the HRV representation RMSSD. On the other hand, an MAE of 8.25+/−3.5 mmHg for SBP and 7.7+/−2.5 mmHg for DBP while using the HRV representation SDRR. Finally, we have developed a framework and built a real-time system to monitor BP as a mobile and web-based application that can facilitate early detection of trends and anomalies, allowing healthcare providers to intervene promptly and personalize treatment plans.

AI Somatotype System Using 3D Body Images: Based on Deep-Learning and Transfer Learning

Humans share a similar body structure, but each individual possesses unique characteristics, which we define as one’s body type. Various classification methods have been devised to understand and assess these body types. Recent research has applied artificial intelligence technology utilizing noninvasive measurement tools, such as 3D body scanner, which minimize physical contact. The purpose of this study was to develop an artificial intelligence somatotype system capable of predicting the three body types proposed by Heath-Carter’s somatotype theory using 3D body images collected using a 3D body scanner. To classify body types, measurements were taken to determine the three somatotype components (endomorphy, mesomorphy, and ectomorphy). MobileNetV2 was utilized as the transfer learning model. The results of this study are as follows: first, the AI somatotype model showed good performance, with a training accuracy around 91% and a validation accuracy around 72%. The respective loss values were 0.26 for the training set and 0.69 for the validation set. Second, validation of the model’s performance using test data resulted in accurate predictions for 18 out of 21 new data points, with prediction errors occurring in three cases, indicating approximately 85% classification accuracy. This study provides foundational data for subsequent research aiming to predict 13 detailed body types across the three body types. Furthermore, it is hoped that the outcomes of this research can be applied in practical settings, enabling anyone with a smartphone camera to identify various body types based on captured images and predict obesity and diseases.

Broadband nonlinear modulation of incoherent light using a transparent optoelectronic neuron array

Nonlinear optical processing of ambient natural light is highly desired for computational imaging and sensing. Strong optical nonlinear response under weak broadband incoherent light is essential for this purpose. By merging 2D transparent phototransistors (TPTs) with liquid crystal (LC) modulators, we create an optoelectronic neuron array that allows self-amplitude modulation of spatially incoherent light, achieving a large nonlinear contrast over a broad spectrum at orders-of-magnitude lower intensity than achievable in most optical nonlinear materials. We fabricated a 10,000-pixel array of optoelectronic neurons, and experimentally demonstrated an intelligent imaging system that instantly attenuates intense glares while retaining the weaker-intensity objects captured by a cellphone camera. This intelligent glare-reduction is important for various imaging applications, including autonomous driving, machine vision, and security cameras. The rapid nonlinear processing of incoherent broadband light might also find applications in optical computing, where nonlinear activation functions for ambient light conditions are highly sought.

PPCL-RSE: Point prediction for counting and localization of litopenaeus vannamei fry with region-based super-resolution enhancement

Accurate locating and counting of litopenaeus vannamei fry can provide substantial support for vannamei fry sales and scientific feeding. However, traditional methods not only require visual observation by experts, but also are time-consuming and labor-intensive, with no guarantee to reach consensus between salesmen and customers. In contrast, more innovative methods require more expensive equipment or are only effective under specific conditions. The small size and high density nature of the shrimp fry makes its counting even more challenging. In this study, a point prediction method for counting and localization of litopenaeus vannamei fry with region-based super-resolution enhancement (PPCL-RSE) is proposed. Through the inclusion of three modules of density partitioning, high-density region expansion and regional super-resolution, the accuracy of fry counting and locating is improved. The model is deployed on a cloud server for convenient fry counting and localization based on images taken by smartphone cameras. To achieve this, we create a dataset called Vannamei-983 which contains images with more than 1,000,000 fry labeled. The proposed method shows accuracies of 99.04 % and 97.71 % in counting and localization of shrimp fry in low- and high-density images, respectively. The excellent model performance also demonstrate the effectiveness of the strategies considered in the study.

Objective demonstration of eyelid spasm relief with smartphone and custom software in hemifacial spasm patients.

To objectively demonstrate eyelid spasms relief in hemifacial spasm (HFS) patients using a smartphone and a custom-made software. Nineteen patients with HFS had standardized videos recorded with a smartphone (iPhone 6S, Apple) camera before and 15days after receiving onabotulinumtoxinA injections. Nineteen age-matched control subjects were also assessed. The Eye Aspect Ratio (EAR) is an algorithm previously described to determine whether the eye is opened or closed. When the eye is closed, EAR tends to be closer to zero. Analogously, if the eye is wide open, values are greater. A custom-made software using the EAR concept was developed and pre- and post-treatment EARs were analyzed to assess HFS patients. Botulinum toxin (BoNT) injections led to a significant increase inthe average EAR of the affected side: + 10.4% (p = 0.0175) of HFS patients, compared to baseline. MeanEAR before BoNT applications were significantly lower (16.2%) on the affected side (0.25 ± 0.05) of HFS patients when compared to controls (0.30 ± 0.05, p = 0.004). After BoNT injections, no statistically significant difference was observed forthe average EAR between the affected side of HFS patients (0.27 ± 0.04) and controls (p = 0.20). Use of a smartphone and custom-made software objectively demonstrated eyelid spasm relief in patients with HFS. Additional refinement of this system could permit more accurate assessments of treatment response rates for each patient, making it possible to be used in clinical practice.

Rekonstruksi bentuk lambung kapal dalam format tiga dimensi (3D) dengan teknik fotogrametri

Fishing boat has unique characteristics, such as seaworthiness, maneuvering, boat’s velocity, displacement, fishing gear layout, and catch storage facilities. With increasing development of photographic technology, photography is not merely an art but it has become a field of mathematics, making it a technique that can be integrated with software technology designed to produce digital data objects in the form of 3D images called Photogrammetric technique. This study is to obtain the reconstruction of the boat's hull based on the Photogrammetric software, to determine the effect of photography to obtain a 3D image, and to know the weakness and strength of 3D reconstruction of the boat’s hull. The images in this study were obtained using a POCO F3 smartphone camera integrated with the PIX4Dcatch application and analyzed with Agisoft Metashape Professional (Trial Version). From this research, we concluded that 1) the reconstruction of the boat hull can be obtained by using Photogrammetric techniques in the PIX4Dcatch application followed by the Agisoft Metashape Professional (Trial Ver.) software analysis; 2). With photographic equipment and several data processing software, the boat’s shape could be produced in 3D images, and 3). There are several advantages in reconstructing the ship's hull with the Photogrammetric technique, namely producing the ship's reconstruction of 3D images, obtaining the principal dimensions of the boat, such as the area and volume of the boat, that could be as the basic data for boat resistance and ship stability calculation, and the work could be done by one person only.

Patient Comfort with Before and After Photography at Plastic Surgery Offices.

Before and after (B&A) photographs are a sensitive part of patients' medical records, and the use of smartphones may pose risks to confidentiality and comfort. The purpose of this study was to assess patient comfort depending on the circumstances under which these photographs being taken. Amazon's Mechanical Turk crowdsourcing service and REDCap's survey manager were used to recruit survey participants. An anonymous survey was distributed to ascertain demographics and comfort in various B&A scenarios using a five-point Likert scale. T tests and ANOVA testing were used to compare groups. There were 411 respondents with an average age of 36.1 years old. Of them, 46% were female and the majority were White (90%) and non-Hispanic (64%). Nearly one-third had previously undergone plastic surgery, with 80% receiving B&A photography. Surgeons took these photographs 51% of the time with similar rates of smartphone cameras use (47%) versus professional cameras (52%). The public had similar levels of comfort when a nurse or a surgeon took the clinical photographs (p=0.08). Patients were significantly less comfortable when non-medically trained office staff captured their photographs (p=0.0041). The public had similar comfort levels with the use of smartphones and professional cameras when dressed but were significantly less comfortable with the use of a smartphone when unclothed (p=<0.001). To ensure the best patient experience, B&A photography should be taken by a medical professional. If photographs are to be taken when the patient is unclothed, the use of a professional-grade camera may help ease patient discomfort. This journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266 .

The Development of Augmented Reality As English Learning Media in Junior High School

The existence of learning media on various platforms provides variety and assistance for teachers in delivering learning materials. Not much has been developed in educational media compared to entertainment media such as gaming, films, songs, dance, and music. Educational media need to be packaged in a simple, effective, and efficient manner and respond to the needs of today’s students. In the context of the world of learning English at the junior high school level, learning media is needed as an effort to provide real experience in terms of honing English communication skills. Augmented Reality is one of the media that is able to bridge the needs of students, namely making abstract learning experiences feel concrete. Therefore, this research aims to design learning media for junior high school English on the basis of Augmented Reality with content containing stories from North Sumatra. The research method applied in this study is Research &amp; Development. Data acquisition techniques used were documentation, questionnaires, interviews, and tests which were applied in accordance with nine research stages, namely: (1) identification and analysis of media needs; (2) collection of media materials and tools; (3) development of media prototype designs; (4) implementation media prototype; (5) media prototype validation; (6) media prototype revision; (7) media trial on junior high school students; (8) final revision; and (9) media prototype that has been tested. The final result of this study contains AR in the form of flash cards. AR markers are printed on cards and students only focus their smartphone cameras on markers that have been printed in card form. After the camera has successfully scanned the marker, a learning video will appear. There are five cards (markers) in this study, and each card will play a different learning video.&#x0D; Keywords: augmented reality, media, English, junior high school

Recognition of Angry and Happy Facial Expressions with Local Binary Pattern and Support Vector Machine

Looks are a huge sort of nonverbal correspondence for getting a handle on a singular's opinions and sentiments. Look affirmation has various potential applications, including security, tutoring, and prosperity systems. The justification for this assessment is for a look affirmation system using area twofold model and sponsorship vector machine techniques. It is typical that this structure can perceive two kinds of sentiments, to be explicit angry and delighted to get the right assumption. First accumulate fundamental data and assistant data from Kaggle and phone cameras, second preprocessing data with grayscale and resizing, third surface features using Area equal model extraction, fourth assist vector with machining about look request used, finally structure evaluation considering precision, exactness, survey, and F-1 worth. The results show that the look affirmation system works honorably on area matched model and sponsorship vector machine. On this investigation dataset, support vector machine gathering on direct part has favored execution over winding reason ability segment. The most significant precision was achieved with the straight part at 86.25%. This study assumes that the look affirmation structure can work outstandingly with neighborhood matched model and sponsorship vector machine. The straight part shows better execution on this investigation dataset. This assessment can be also advanced by adding more looks, incorporate extraction methods, and plan.

Quantitative Fluorescent Lateral Flow Strip Sensor for Myocardial Infarction Using Purity-Color Upconversion Nanoparticles.

Acute myocardial infarction is a serious cardiovascular disease and poses significant risks to human health. Its early diagnosis and real-time detection are of great importance. Herein, we design a low-cost device that has a high sensitivity of cTnT and cTnI detection. Dual-color upconversion nanoparticles (UCNPs) are prepared as probes, which not only have high-purity red upconversion luminescence (UCL) under 980 or 808 nm excitation but also achieve good temperature sensing. Temperature-dependent multicolor emission excitation is obtained, and the color turns from white to orange and red with increasing temperature. In particular, the maximum SR and SA values based on nonthermally coupled levels are 4.76% K-1 and 8.6% K-1, which are higher than those based on thermally coupled levels. With the UCNPs-based lateral flow strip (LFS), the specific detection of cTnI and cTnT antigens in samples is achieved with a detection limit of 0.001 ng/mL, which is 1 order of magnitude lower than that of their clinical cutoff. The UCNPs-LFS device has a low-cost laser diode and a simplified laser and permits a mobile-phone camera to collect the results, which has an important influence on the field of biomarker sensing.

Mobile phone applications for 3-dimensional scanning and digital anthropometry: a precision comparison with traditional scanners.

The precision of digital anthropometry through 3-dimensional (3D) scanning has been established for relatively large, expensive, non-portable systems. The comparative performance of modern mobile applications is unclear. Forty-six adults (age: 23.3 ± 5.3 y; BMI: 24.4 ± 4.1 kg/m2) were assessed in duplicate using: (1) a mobile phone application capturing two individual 2D images, (2) a mobile phone application capturing serial images collected during a subject's complete rotation, (3) a traditional scanner with a time of flight infrared sensor collecting visual data from a subject being rotated on a mechanical turntable, and (4) a commercial measuring booth with structured light technology using 20 infrared depth sensors positioned in the booth. The absolute and relative technical error of measurement (TEM) and intraclass correlation coefficient (ICC) for each method were established. Averaged across circumferences, the absolute TEM, relative TEM, and ICC were (1) 0.9 cm, 1.5%, and 0.975; (2) 0.5 cm, 0.9%, and 0.986; (3) 0.8 cm, 1.5%, and 0.974; and (4) 0.6 cm, 1.1%, and 0.985. For total body volume, these values were (1) 2.2 L, 3.0%, and 0.978; (2) 0.8 L, 1.1%, and 0.997; (3) 0.7 L, 0.9%, and 0.998; and (4) 0.8 L, 1.1%, and 0.996, with segmental volumes demonstrating higher relative errors. A 3D scanning mobile phone application involving full rotation of subjects in front of a smartphone camera exhibited similar reliability to larger, less portable, more expensive 3D scanners. In contrast, larger errors were observed for a mobile scanning application utilizing two 2D images, although the technical errors were acceptable for some applications.