Real-Time Spatial Mapping in Architectural Visualization: A Comparison among Mixed Reality Devices.

Recent advancements in communication technology have catalyzed the widespread adoption of realistic content, with augmented reality (AR) emerging as a pivotal tool for seamlessly integrating virtual elements into real-world environments. In construction, architecture, and urban design, the integration of mixed reality (MR) technology enables rapid interior spatial mapping, providing clients with immersive experiences to envision their desires. The rapid advancement of MR devices, or devices that integrate MR capabilities, offers users numerous opportunities for enhanced entertainment experiences. However, to support designers at a high level of expertise, it is crucial to ensure the accuracy and reliability of the data provided by these devices. This study explored the potential of utilizing spatial mapping within various methodologies for surveying architectural interiors. The objective was to identify optimized spatial mapping procedures and determine the most effective applications for their use. Experiments were conducted to evaluate the interior survey performance, using HoloLens 2, an iPhone 13 Pro for spatial mapping, and photogrammetry. The findings indicate that HoloLens 2 is most suited for the tasks examined in the scope of these experiments. Nonetheless, based on the acquired parameters, the author also proposes approaches to apply the other technologies in specific real-world scenarios.

Analysis of the performance of the CorneAI for iOS in the classification of corneal diseases and cataracts based on journal photographs.

CorneAI for iOS is an artificial intelligence (AI) application to classify the condition of the cornea and cataract into nine categories: normal, infectious keratitis, non-infection keratitis, scar, tumor, deposit, acute primary angle closure, lens opacity, and bullous keratopathy. We evaluated its performance to classify multiple conditions of the cornea and cataract of various races in images published in the Cornea journal. The positive predictive value (PPV) of the top classification with the highest predictive score was 0.75, and the PPV for the top three classifications exceeded 0.80. For individual diseases, the highest PPVs were 0.91, 0.73, 0.42, 0.72, 0.77, and 0.55 for infectious keratitis, normal, non-infection keratitis, scar, tumor, and deposit, respectively. CorneAI for iOS achieved an area under the receiver operating characteristic curve of 0.78 (95% confidence interval [CI] 0.5-1.0) for normal, 0.76 (95% CI 0.67-0.85) for infectious keratitis, 0.81 (95% CI 0.64-0.97) for non-infection keratitis, 0.55 (95% CI 0.41-0.69) for scar, 0.62 (95% CI 0.27-0.97) for tumor, and 0.71 (95% CI 0.53-0.89) for deposit. CorneAI performed well in classifying various conditions of the cornea and cataract when used to diagnose journal images, including those with variable imaging conditions, ethnicities, and rare cases.

Development of a Subjective Visual Vertical Test System Using a Smartphone With Virtual Reality Goggles for Screening of Otolithic Dysfunction: Observational Study.

BACKGROUND: The subjective visual vertical (SVV) test can evaluate otolith function and spatial awareness and is performed in dedicated vertigo centers using specialized equipment; however, it is not otherwise widely used because of the specific equipment and space requirements. An SVV test smartphone app was developed to easily perform assessments in outpatient facilities. OBJECTIVE: This study aimed to verify whether the SVV test smartphone app with commercially available virtual reality goggles can be used in a clinical setting. METHODS: The reference range was calculated for 15 healthy participants. We included 14 adult patients with unilateral vestibular neuritis, sudden sensorineural hearing loss with vertigo, and Meniere disease and investigated the correlation between the SVV test results and vestibular evoked myogenic potential (VEMP) results. RESULTS: The SVV reference range of healthy participants for the sitting front-facing position was small, ranging from -2.6º to 2.3º. Among the 14 patients, 6 (43%) exceeded the reference range for healthy participants. The SVV of patients with vestibular neuritis and sudden sensorineural hearing loss tended to deviate to the affected side. A total of 9 (64%) had abnormal cervical VEMP (cVEMP) values and 6 (43%) had abnormal ocular VEMP (oVEMP) values. No significant difference was found between the presence or absence of abnormal SVV values and the presence or absence of abnormal cVEMP and oVEMP values; however, the odds ratios (ORs) suggested a higher likelihood of abnormal SVV values among those with abnormal cVEMP and oVEMP responses (OR 2.40, 95% CI 0.18-32.88; P>.99; and OR 2, 95% CI 0.90-4.45; P=.46, respectively). CONCLUSIONS: The SVV app can be used anywhere and in a short period while reducing directional bias by using virtual reality goggles, thus making it highly versatile and useful as a practical otolith dysfunction screening tool.

Indoor Mapping with Entertainment Devices: Evaluating the Impact of Different Mapping Strategies for Microsoft HoloLens 2 and Apple iPhone 14 Pro.

Due to their low cost and portability, using entertainment devices for indoor mapping applications has become a hot research topic. However, the impact of user behavior on indoor mapping evaluation with entertainment devices is often overlooked in previous studies. This article aims to assess the indoor mapping performance of entertainment devices under different mapping strategies. We chose two entertainment devices, the HoloLens 2 and iPhone 14 Pro, for our evaluation work. Based on our previous mapping experience and user habits, we defined four simplified indoor mapping strategies: straight-forward mapping (SFM), left-right alternating mapping (LRAM), round-trip straight-forward mapping (RT-SFM), and round-trip left-right alternating mapping (RT-LRAM). First, we acquired triangle mesh data under each strategy with the HoloLens 2 and iPhone 14 Pro. Then, we compared the changes in data completeness and accuracy between the different devices and indoor mapping applications. Our findings show that compared to the iPhone 14 Pro, the triangle mesh accuracy acquired by the HoloLens 2 has more stable performance under different strategies. Notably, the triangle mesh data acquired by the HoloLens 2 under the RT-LRAM strategy can effectively compensate for missing wall and floor surfaces, mainly caused by furniture occlusion and the low frame rate of the depth-sensing camera. However, the iPhone 14 Pro is more efficient in terms of mapping completeness and can acquire a complete triangle mesh more quickly than the HoloLens 2. In summary, choosing an entertainment device for indoor mapping requires a combination of specific needs and scenes. If accuracy and stability are important, the HoloLens 2 is more suitable; if efficiency and completeness are important, the iPhone 14 Pro is better.

Assessing iPhone LiDAR & Recon-3D for determining area of origin in bloodstain pattern analysis.

Bloodstain pattern analysis (BPA) has proven to be a useful tool in forensic and criminal investigations for quite some time. Traditionally, documenting a crime scene for a bloodletting event was completed using manual techniques, physical strings, and a tape measure. In more recent years, laser scanners and 3D software programs have become a preferred method to capture accurate data that improves the validity and reliability of BPA. The initial cost of laser scanning equipment is relatively high, rendering these systems inaccessible to some police and smaller agencies. Recon-3D is a newly developed iPhone application that utilizes the iPhone LiDAR sensor in combination with video data to create 3D point clouds of crime scenes. To assess the viability of Recon-3D for area of origin analysis, two tests were performed. One was a series of bloodstain impacts which were analyzed in FARO Zone 3D software, while the second was a series of 6 repeated Recon-3D scans of two 90-degree walls which was then compared to the FARO Focus S350 scanner using CloudCompare software. A total of eight impact patterns were made at three different distances from a wall. The area of origin was measured and compared to the known location of the blood source. The average total 3D error for the area of origin set at 25, 50, and 100 cm from two perpendicular walls was found to be 6.04, 15.16, and 36.59 cm, respectively. These results are similar to past studies where programs such as HemoSpat have been used. The results of the point cloud comparison show that on average, 95% of the points from Recon-3D fall below a threshold of 3.6 mm when compared to a FARO Focus S350 laser scanner. Thus, the results of this test suggest that Recon-3D is an accurate and affordable scanning application for bloodstain patterns at crime scenes and the data provide acceptable results for area of origin analysis in BPA programs which accept laser scanner data.

Development of a Prototype Video Head Impulse Test System Using an iPhone for Screening of Peripheral Vestibular Dysfunction.

Introduction: Head impulse, nystagmus, and test of skew (HINTS) is more accurate for the early diagnosis of occipital fossa stroke than magnetic resonance imaging. However, the head impulse test (HIT) is relatively challenging to perform, as it is subjective. Herein, we developed a prototype video HIT (vHIT) system using an iPhone (Apple, Cupertino, CA, USA) that is compact, easy to operate, and analyzable by our iPhone application. Methods: The iPhone-vHIT and a vHIT using EyeSeeCam (Interacoustics, Eden Prairie, NM, USA) were performed on a healthy man in his 30s and on a patient with vestibular neuritis who visited the Mejiro University Ear Institute Clinic. For the iPhone-vHIT, eye movements were detected by analyzing high-speed videos captured using an iPhone camera, and head movements were followed using an iPhone gyro sensor. An iPhone fixation brace was used to capture the video without any blurring. Results: The iPhone-vHIT system obtained vHIT waveforms similar to those of the EyeSeeCam-vHIT system in the healthy man and the patient with vestibular neuritis. The iPhone-vHIT system effectively detected the reduced vestibulo-ocular reflex gain in patients with vestibular neuritis. The iPhone-vHIT system at 120 frames per second was less sensitive to catch-up saccades than the EyeSeeCam. Conclusion: vHIT systems using a smartphone have been reported but are currently unavailable. At present, the iPhone-vHIT application in this study is the only available smartphone-based vHIT system for screening of peripheral vestibular dysfunction. We believe that the prototype iPhone-vHIT with a high-speed camera will be clinically used to perform the vHIT, even though it only examines the lateral semicircular canal.

Is a smartphone application as accurate as a traditional goniometer for assessing finger joint angles in Dupuytren's disease?

OBJECTIVES: Smartphone applications are available using the smartphone accelerometer to measure angles. This study compared finger joint angle measurements using a traditional goniometer (TG) versus a smartphone application (SPA) in a group of patients with Dupuytren's disease, to determine if they were equally accurate. This was a clinical measurement case series. A group of patients with Dupuytren's disease were invited to participate. MATERIAL AND METHODS: The Apple iPhone 7 "Measure" application was used. Participants were asked to place their hand as flat as possible on the table in a clinic room. Each joint of the ring and little fingers was measured using the TG and the SPA. Power calculation by paired t-test determined a sample size of 25. RESULTS: 28 hands were measured. The Pearson correlation coefficients for the various finger joints were: metacarpophalangeal joint (MCPJ), 0.989; proximal interphalangeal joint (PIPJ), 0.997; and distal interphalangeal joint (DIPJ), 0.977. The root mean square errors (RMSE) for the various joints were: MCPJ, 3.190; PIPJ, 2.019; and DIPJ, 1.897. Bland-Altman analysis showed the two methods to be in agreement. CONCLUSION: The SPA was consistent, reliable and in agreement with a TG for assessing ring and little finger joint angles. The SPA could be used by healthcare professionals instead of a TG.

Characterization of the iPhone LiDAR-Based Sensing System for Vibration Measurement and Modal Analysis.

Portable depth sensing using time-of-flight LiDAR principles is available on iPhone 13 Pro and similar Apple mobile devices. This study sought to characterize the LiDAR sensing system for measuring full-field vibrations to support modal analysis. A vibrating target was employed to identify the limits and quality of the sensor in terms of noise, frequency, and range, and the results were compared to a laser displacement transducer. In addition, properties such as phone-to-target distance and lighting conditions were investigated. It was determined that the optimal phone-to-target distance range is between 0.30 m and 2.00 m. Despite an indicated sampling frequency equal to the 60 Hz framerate of the RGB camera, the LiDAR depth map sampling rate is actually 15 Hz, limiting the utility of this sensor for vibration measurement and presenting challenges if the depth map time series is not downsampled to 15 Hz before further processing. Depth maps were processed with Stochastic Subspace Identification in a Monte Carlo manner for stochastic modal parameter identification of a flexible steel cantilever. Despite significant noise and distortion, the natural frequencies were identified with an average difference of 1.9% in comparison to the laser displacement transducer data, and high-resolution mode shapes including uncertainty ranges were obtained and compared to an analytical solution counterpart. Our findings indicate that mobile LiDAR measurements can be a powerful tool in modal identification if used in combination with prior knowledge of the structural system. The technology has significant potential for applications in structural health monitoring and diagnostics, particularly where non-contact vibration sensing is useful, such as in flexible scaled laboratory models or field scenarios where access to place physical sensors is challenging.

Reliability of the assessment of scapular posterior tilt angle using the smartphone and scapular movement during arm elevation in healthy individuals and patients with frozen shoulder: a cross-sectional study.

Background: Frozen shoulders are associated with abnormal scapular movements. However, scapular posterior tilt movement in frozen shoulders has not been investigated using simple clinical methods. This study aimed to clarify the reliability of scapular posterior tilting movement using a smartphone and scapular posterior tilting movement in healthy individuals and patients with frozen shoulder. Methods: The participants were 22 healthy young (age 25.9 ± 4.1 years), 22 healthy middle-aged (age 52.6 ± 4.4 years), and 37 individuals with frozen shoulder (age 56.0 ± 7.0 years). Scapular posterior tilting movement was measured at shoulder flexion 0° (0° posterior tilt), shoulder flexion 90° (90° posterior tilt), and scapular tilt excursion using a smartphone. The intrarater reliability was calculated using the intraclass correlation coefficient (1, 3). Results: Intrarater reliability at 0° posterior tilt and 90° posterior tilt was 0.76 and 0.84, respectively. The 0° posterior tilt was not significantly different among the three groups (P = .90). The 90° posterior tilt was not significantly different among the three groups (P = .06). The scapular tilt excursions were significantly greater in the frozen shoulder group than in the middle-aged group (P = .03). Conclusion: Measurement of scapular posterior tilting movement using a smartphone was highly reliable. The frozen shoulder might compensate for the limited arm elevation of the glenohumeral joint by scapular posterior tilting movement.

High-Fidelity 3D Stray Magnetic Field Mapping of Smartphones to Address Safety Considerations with Active Implantable Electronic Medical Devices.

Case reports indicate that magnets in smartphones could be a source of electromagnetic interference (EMI) for active implantable medical devices (AIMD), which could lead to device malfunction, compromising patient safety. Recognizing this challenge, we implemented a high-fidelity 3D magnetic field mapping (spatial resolution 1 mm) setup using a three-axis Hall probe and teslameter, controlled by a robot (COSI Measure). With this setup, we examined the stray magnetic field of an iPhone 13 Pro, iPhone 12, and MagSafe charger to identify sources of magnetic fields for the accurate risk assessment of potential interferences with AIMDs. Our measurements revealed that the stray fields of the annular array of magnets, the wide-angle camera, and the speaker of the smartphones exceeded the 1 mT limit defined by ISO 14117:2019. Our data-driven safety recommendation is that an iPhone 13 Pro should be kept at least 25 mm away from an AIMD to protect it from unwanted EMI interactions. Our study addresses safety concerns due to potential device-device interactions between smartphones and AIMDs and will help to define data-driven safety guidelines. We encourage vendors of electronic consumer products (ECP) to provide information on the magnetic fields of their products and advocate for the inclusion of smartphones in the risk assessment of EMI with AIMDs.

Facial Soft Tissue Ptosis: A Quantitative Analysis using 3d Facial Scan App For iPhone.

Although the modifications of the aging face have been widely described, to our knowledge, there are no studies that quantitatively analyze the degree of soft tissues facial ptosis. Using a specific iPhone application, the faces of a heterogeneous group of volunteers were scanned and studied with the aim to virtually measure the entity of facial ptosis.Two facial scans, upright and supine, were performed by using the Bellus3D Face app for iPhone in a sample of 60 volunteers. We virtually superimposed the two scans, and then, we calculated the discrepancy between them through the Geomagic Design X 3D software. A multivariate regression statistical model was used to analyze the correlation between the mean discrepancy values compared to three main variables: age, BMI and gender. Mean ptosis increases with age (coeff. = 0.02; 95% CI = 0.01-0.02, p < 0.001), BMI (coeff. = 0.03; 95% CI = 0.01-0.05; p < 0.001) and has been found higher in females (female versus male: coeff. = 0.22; 95% CI = 0.13-0.31; p < 0.001). The method we used allowed us to measure the degree of ptosis, and to make a complete morphological study of the effect of gravity on the facial surface in a very accurate, low cost and easily reproducible way.

Accuracy of low-cost alternative facial scanners: a prospective cohort study.

INTRODUCTION: Three-dimensional facial scans have recently begun to play an increasingly important role in the peri-therapeutic management of oral and maxillofacial and head and neck surgery cases. Face scan images can be generated by optical facial scanners utilizing line-laser, stereophotography, or structured light modalities, as well as from volumetric data: for example, from cone beam computed tomography (CBCT). This study aimed to evaluate whether two low-cost procedures for the creation of three-dimensional face scan images were capable of producing sufficiently accurate data sets for clinical analysis. MATERIALS AND METHODS: Fifty healthy volunteers were included in the study. Two test objects with defined dimensions (Lego bricks) were attached to the forehead and the left cheek of each volunteer. Facial anthropometric values (i.e., the distances between the medial canthi, the lateral canthi, the nasal alae, and the angles of the mouth) were first measured manually. Subsequently, face scans were performed with a smart device and manual photogrammetry and the values obtained were compared with the manually measured data sets. RESULTS: The anthropometric distances deviated, on average, 2.17 mm from the manual measurements (smart device scanning deviation 3.01 mm, photogrammetry deviation 1.34 mm), with seven out of eight deviations being statistically significant. For the Lego brick, from a total of 32 angles, 19 values demonstrated a significant difference from the original 90° angles. The average deviation was 6.5° (smart device scanning deviation 10.1°, photogrammetry deviation 2.8°). CONCLUSION: Manual photogrammetry demonstrated greater accuracy when creating three-dimensional face scan images; however, smart devices are more user-friendly. Dental professionals should monitor camera and smart device technical improvements carefully when choosing and adequate technique for 3D scanning.

Motion-capture Analysis of Mice Using a Video Recorded on an iPhone Camera.

When focusing on quick movements in the analysis of animal behavior, a high-speed camera can be used as a powerful tool. There are many options for high-speed cameras to record movement. In recent years, the quality and sophistication of videos captured on cell phones have evolved so much that the iPhone's slow-motion video system can function as a tool for behavior analysis. Here, we describe a method to analyze the movement of the ankle joint and jump speed during the jumping action of mice, using an iPhone.

Smartphone Color Vision Testing as an Alternative to the Conventional Ishihara Booklet.

Introduction Color vision testing was first seen as a parameter to be tested in the 1700s. Nowadays, it is a well-known phenomenon with significant quality-of-life implications. Structures involved in color vision include the lens, pupil, retinal cone photopigments, and several photoreceptor processes that translate the incoming spectrum of different light wavelengths into a processed colored image. An initial color vision assessment was made simply by comparing the color perception of the individual to that of the examiner. The most commonly used tools to screen for color vision defects today are color plates, such as the Ishihara color plates. In the modern age, smartphones have evolved to become an essential part of our everyday lives with applications such as Eye Handbook, which allow easier access to color vision testing using color plates displayed on smartphone screens. In this study, we compared color vision testing on Android and iOS devices to the standard Ishihara booklet. Materials and methods A cross-sectional validation study was performed on patients presenting to the Armed Forces Institute of Ophthalmology, Rawalpindi, Pakistan for six months. The sample size collected was 162 with a 95% confidence interval. The age range of the sample population was kept at 12-70 years. A patient was selected for participation in the study, and a color vision assessment was performed using the Ishihara color plates and Android and iOS smartphones. The collected data was then entered into IBM SPSS (Statistical Package for the Social Sciences) Statistics 25 for analysis, with the p-value being kept at 0.05. Results The sample size was 162, with the gender distribution being predominantly male (69.14%). The average age of the participants was 35.94 (SD = 12.04). The result of the two-tailed paired sample z-testwas not significant based on a p-value of 0.565, indicating the null hypothesis cannot be rejected. This finding suggests the difference between the mean of Ishihara and the mean of the iPhone was not significantly different from zero. Similar results were found for comparisons between Android smartphones and the Ishihara booklet. Conclusions Previous studies conducted showed nearly 60% of subjects with normal color vision correctly identified all colors on standard Ishihara color plates. The two-tailed paired sample t-test conducted in our study showed no significant difference between either of the smartphone groups (iPhone or Android) and the Ishihara booklet group, indicating that smartphones present a viable alternative to standard Ishihara booklet testing. However, there are certain limitations to our study. Different types of smartphone screens present a challenge in standardization while testing color vision, something that is not a problem when using the Ishihara booklet. However, smartphones are more widely available, more versatile, and present far greater ease of access. Both these factors should be considered when comparing the two in future studies.

Flash Characterization of Smartphones Used in Point-of-Care Diagnostics.

Rapidly growing interest in smartphone cameras as the basis of point-of-need diagnostic and bioanalytical technologies increases the importance of quantitative characterization of phone optical performance under real-world operating conditions. In the context of our development of lateral-flow immunoassays based on phosphorescent nanoparticles, we have developed a suite of tools for characterizing the temporal and spectral profiles of smartphone torch and flash emissions, and their dependence on phone power state. In this work, these tools are described and documented to make them easily available to others, and demonstrated by application to characterization of Apple iPhone 5s, iPhone 6s, iPhone 8, iPhone XR, and Samsung Note8 flash performance as a function of time and wavelength, at a variety of power settings. Flash and torch intensity and duration vary with phone state and among phone models. Flash has high variability when the battery charge is below 10%, thus, smartphone-based Point-of-Care (POC) tests should only be performed at a battery level of at least 15%. Some output variations could substantially affect the results of assays that rely on the smartphone flash.

Information Seeking Practices and Availability of Smart Devices Among Healthcare Professionals in a Lower-Middle-Income Country: An Analysis From Pakistan.

Introduction Evidence-based medicine (EBM) is a principle that integrates clinical experience with relevant information available to provide adequate healthcare. It requires access to current medical literature. This paper analyzes the information requirements of a lower-middle-income country (LMIC) and the resources available and preferred by medical professionals. Methods A survey-based cross-sectional study was carried out among 160 participants, ranging in expertise from students to attending physicians in Karachi, Pakistan. The survey comprised questions to assess the clinical background, technology access, need for health-related information, and the preference for resources to obtain that information in different scenarios. They were also asked if they use PubMed and their recommended methods to improve information access. Statistical Package for the Social Sciences (SPSS; IBM, NY, USA) software was used for all analyses. Results A basic mobile phone (with limited internet connectivity) was the most common device used at home (n=159; 99.4%) and work (n=141; 88.1%). No smart devices were available to 28 (17.5%) participants at work. Internet connectivity was available for 155 (96.9%) participants at home but only for 118 (73.7%) participants at work. About one-third (n=49; 30.6%) experienced questions arising in practice two to four times a day, and half of the participants (n=80; 50%) were very likely to look up a reference. The most common resource for the majority of given clinical scenarios was a senior colleague. At the same time, medical websites (Medscape, Up-to-Date, WebMD) were the first choice for a non-specific general medical query. About 68.75% (n=110) of participants claimed to use PubMed in daily practice. The most common reason for not using PubMed was the ease of using other search engines (like Google). Conclusions Improved access to the internet and well-reputed journals can enhance the practice of EBM in Pakistan. Limitations of technological access must be considered while designing information resources in lower-middle-income countries.

Examining the Profile of Noise-Induced Cochlear Synaptopathy Using iPhone Health App Data and Cochlear and Brainstem Electrophysiological Responses to Fast Clicks Rates.

Little is known about objective classifying of noise exposure risk levels in personal listening device (PLD) users and electrophysiologic evidence of cochlear synaptopathy at very fast click rates. The aim of the study was to objectively classify noise exposure risk using iPhone Health app and identify signs of cochlear synaptopathy using behavioral and electrophysiologic measures. Thirty normal-hearing females (aged 18-26 years) were grouped based on their iPhone Health app's 6-month listening level and noise exposure data into low-risk and high-risk groups. They were assessed using a questionnaire, extended high-frequency (EHF) audiometry, QuickSIN test, distortion-product otoacoustic emission (DPOAE), and simultaneous recording of electrocochleography (ECochG) and auditory brainstem response (ABR) at three click rates (19.5/s, 97.7/s, 234.4/s). A series of ANOVAs and independent samples t -test were conducted for group comparison. Both groups had within-normal EHF hearing thresholds and DPOAEs. However, the high-risk participants were over twice as likely to suffer from tinnitus, had abnormally large summating potential to action potential amplitude and area ratios at fast rates, and had slightly smaller waves I and V amplitudes. The high-risk group demonstrated a profile of behavioral and objective signs of cochlear synaptopathy based on ECochG and ABR recordings at fast click rates. The findings in this study suggest that the iPhone Health app may be a useful tool for further investigation into cochlear synaptopathy in PLD users.

Colorimetric Detection of the SARS-CoV-2 Virus (COVID-19) in Artificial Saliva Using Polydiacetylene Paper Strips.

The spread and resurgence of the SARS-CoV-2 virus (COVID-19 disease) threatens human health and social relations. Prevention of COVID-19 disease partly relies on fabricating low-cost, point-of-care (POC) sensing technology that can rapidly and selectively detect the SARS-CoV-2 virus. We report a colorimetric, paper-based polydiacetylene (PDA) biosensor, designed to detect SARS-CoV-2 spike protein in artificial saliva. Analytical characterizations of the PDA sensor using NMR and FT-IR spectroscopy showed the correct structural elucidation of PCDA-NHS conjugation. The PDA sensor platform containing the N-Hydroxysuccinimide ester of 10, 12-pentacosadiynoic acid (PCDA-NHS) was divided into three experimental PCDA-NHS concentration groups of 10%, 20%, and 30% to optimize the performance of the sensor. The optimal PCDA-NHS molar concentration was determined to be 10%. The PDA sensor works by a color change from blue to red as its colorimetric output when the immobilized antibody binds to the SARS-CoV-2 spike protein in saliva samples. Our results showed that the PDA sensing platform was able to rapidly and qualitatively detect the SARS-CoV-2 spike protein within the concentration range of 1 to 100 ng/mL after four hours of incubation. Further investigation of pH and temperature showed minimal influence on the PDA sensor for the detection of COVID-19 disease. After exposure to the SARS-CoV-2 spike protein, smartphone images of the PDA sensor were used to assess the sensor output by using the red chromatic shift (RCS) of the signal response. These results indicate the potential and practical use of this PDA sensor design for the rapid, colorimetric detection of COVID-19 disease in developing countries with limited access to medical testing.

Workflow to develop 3D designed personalized neonatal CPAP masks using iPhone structured light facial scanning.

BACKGROUND: Continuous positive airway pressure (CPAP) is a common mode of respiratory support used in neonatal intensive care units. In preterm infants, nasal CPAP (nCPAP) therapy is often delivered via soft, biocompatible nasal mask suitable for long-term direct skin contact and held firmly against the face. Limited sizes of nCPAP mask contribute to mal-fitting related complications and adverse outcomes in this fragile population. We hypothesized that custom-fit nCPAP masks will improve the fit with less skin pressure and strap tension improving efficacy and reducing complications associated with nCPAP therapy in neonates. METHODS: After IRB approval and informed consent, we evaluated several methods to develop 3D facial models to test custom 3D nCPAP masks. These methods included camera-based photogrammetry, laser scanning and structured light scanning using a Bellus3D Face Camera Pro and iPhone X running either Bellus3D FaceApp for iPhone, or Heges application. This data was used to provide accurate 3D neonatal facial models. Using CAD software nCPAP inserts were designed to be placed between proprietary nCPAP mask and the model infant's face. The resulted 3D designed nCPAP mask was form fitted to the model face. Subsequently, nCPAP masks were connected to a ventilator to provide CPAP and calibrated pressure sensors and co-linear tension sensors were placed to measures skin pressure and nCPAP mask strap tension. RESULTS: Photogrammetry and laser scanning were not suited to the neonatal face. However, structured light scanning techniques produced accurate 3D neonatal facial models. Individualized nCPAP mask inserts manufactured using 3D printed molds and silicon injection were effective at decreasing surface pressure and mask strap pressure in some cases by more than 50% compared to CPAP masks without inserts. CONCLUSIONS: We found that readily available structured light scanning devices such as the iPhone X are a low cost, safe, rapid, and accurate tool to develop accurate models of preterm infant facial topography. Structured light scanning developed 3D nCPAP inserts applied to commercially available CPAP masks significantly reduced skin pressure and strap tension at clinically relevant CPAP pressures when utilized on model neonatal faces. This workflow maybe useful at producing individualized nCPAP masks for neonates reducing complications due to misfit.

Prospective evaluation of medical student accuracy conducting direct ophthalmoscopy with an unmodified iPhone X.

PURPOSE: To evaluate fundus examination accuracy of medical students when using an unmodified iPhone X or a direct ophthalmoscope in comparison to a staff ophthalmologist's retinal examination. METHODS: In this prospective comparative analysis, patients underwent dilated fundus examination by novice medical trainees using either an unmodified iPhone X or standard direct ophthalmoscope. The primary outcome was the mean difference and degree of agreement in cup-to-disc ratio between student examination and the staff ophthalmologist's cup-to-disc observation. RESULTS: A total of 18 medical students conducted 230 retinal examinations, 117 with the iPhone X and 113 with the direct ophthalmoscope. A greater proportion of students were unable to report cup-to-disc ratio using the iPhone X (81.2%) vs direct ophthalmoscope (30.1%). Student examination of cup-to-disc ratio led to a systematic bias (95% limits of agreement) of + 0.16 (-0.22 to + 0.54) and + 0.10 (-0.36 to + 0.56) with the iPhone X and direct ophthalmoscope, respectively. iPhone X and direct ophthalmoscope student observation concordance for optic disc colour (88.7 and 82.4%, respectively) and contour (68.3 and 74.2%, respectively) demonstrated low agreement with staff ophthalmologist findings. Student iPhone X observations demonstrated lower agreement with staff findings compared to direct ophthalmoscope observations for spontaneous venous pulsations (Cohen's Kappa = -0.044 vs 0.099). CONCLUSION: Amongst medical trainees, optic disc visualization using an unmodified iPhone X was inferior to the direct ophthalmoscope. When able to visualize the optic nerve head, there was no significant difference in reported cup-to-disc ratio between modalities. However, both modalities demonstrated poor reliability in comparison to staff ophthalmologist findings.