Camera System Research Articles

Determination of the internal loads experienced by proximal phalanx fracture fixations during rehabilitation exercises.

Phalangeal fractures are common, particularly in younger patients, leading to a large economic burden due to higher incident rates among patients of working age. In traumatic cases where the fracture may be unstable, plate fixation has grown in popularity due to its greater construct rigidity. However, these metal plates have increased reoperation rates due to inflammation of the surrounding soft tissue. To overcome these challenges, a novel osteosynthesis platform, AdhFix, has been developed. This method uses a light-curable polymer that can be shaped in situ around traditional metal screws to create a plate-like structure that has been shown to not induce soft tissue adhesions. However, to effectively evaluate any novel osteosynthesis device, the biomechanical environment must first be understood. In this study, the internal loads in a phalangeal plate osteosynthesis were measured under simulated rehabilitation exercises. In a human hand cadaver study, a plastic plate with known biomechanical properties was used to fix a 3mm osteotomy and each finger was fully flexed to mimic traditional rehabilitation exercises. The displacements of the bone fragments were tracked with a stereographic camera system and coupled with specimen specific finite element (FE) models to calculate the internal loads in the osteosynthesis. Following this, AdhFix patches were created and monotonically tested under similar conditions to determine survival of the novel technique. The internal bending moment in the osteosynthesis was 6.78 ± 1.62Nmm and none of the AdhFix patches failed under the monotonic rehabilitation exercises. This study demonstrates a method to calculate the internal loads on an osteosynthesis device during non-load bearing exercises and that the novel AdhFix solution did not fail under traditional rehabilitation protocols in this controlled setting. Further studies are required prior to clinical application.

Wavelets for Self-Calibration of Aerial Metric Camera Systems

In this paper, wavelets are applied to develop new models for the self-calibration of aerial metric camera systems. It is well known and mathematically proven that additional parameters (APs) can compensate image distortions and remaining error sources by a rigorous photogrammetric bundle-block adjustment. Thus, kernel functions based on orthogonal wavelets (e. g., asymmetric Daubechies wave- lets, least asymmetric Daubechies wavelets, Battle-Lemarié wavelets, Meyer wavelets) are used to build the wavelets-based family of APs for self-calibrating digital frame cameras. These new APs are called wavelet APs. Its applications in rigorous tests are accomplished by using aerial images taken by an airborne digital mapping camera in situ and practical calibrations. The test results demonstrate that these orthogonal wavelet APs are applicable and largely avoid the risk of over-parameterization. Their external accuracy is evaluated using reliable and high precision check points in the calibration field.

Ground experimental study of the electron density of plasma sheath reduced by pulsed discharge

Abstract A plasma sheath will be generated around the hypersonic vehicle during reentry, where a large number of electrons will significantly affect the propagation of EM waves, resulting in the phenomenon of communication blackout. This paper proposes a method of reducing the electron density of reentry vehicle plasma sheath by pulsed discharge. Experiments were conducted in a high-speed plasma wind tunnel to study the effects and scope of pulsed discharge on the plasma sheath electron density using an ultrahigh-speed camera and microwave diagnostic system. The experimental results show that the application of pulsed discharge resulted in the formation of a light intensity attenuation region measuring 14 × 19 × 4 cm around the discharge area, with an attenuation degree ranging from 30% to 58%. The microwave diagnostic results indicate that after the actuator discharge, the electron density of the plasma sheath within a 4 cm height above the vehicle wall is significantly reduced compared to before the actuator discharge, with a maximum reduction of approximately 86%. These results demonstrate that this method has significant effects on reducing plasma sheath electron density. Furthermore, the low power consumption, load, and space requirements suggest that it has potential for practical applications.

Dynamics of automated body condition scores in grazing Holstein cows in a year-round calving system

This observational study aimed to characterize the seasonal dynamics of automated body condition scores (BCS) through the lactation of Holstein cows in a pasture-based system with year-round calvings. Examining the association between nadir BCS (nBCS; defined as the lowest daily BCS after calving) and peak milk yield within each calving period (calendar seasons equally divided in early and late) was a secondary objective of this research. Retrospective data included 2,164 lactations in 539 primiparous (PRI) and 1,625 multiparous (MLT) Holstein cows that calved from July 2021 to June 2023 in a commercial dairy farm located in Southern Chile. Individual BCS were generated in every milking by an automated BCS camera system. Body condition score at calving (BCSc), nBCS, and the change in BCS from calving to nadir (ΔBCS) were considered for the analysis. Peak milk yield (greatest daily milk yield) values were retrieved from on-farm software and lactations were categorized considering quartiles (Q1 = 25% lowest peak milk yield; Q4 = 25% greatest peak milk yield). Data were examined in PRI and MLT cows separately using multivariable linear models that considered calving period and peak milk yield as the main explanatory variables of interest, while BCSc and health status were included as covariables when appropriate. The differences in BCSc among calving periods were more evident in primiparous cows that had the lowest BCSc in early spring (3.13 ± 0.03) and the greatest BCSc in late fall (3.51 ± 0.03). In MLT cows, the lowest and greatest BCSc were recognized in late fall (3.07 ± 0.04) and early summer (3.23 ± 0.03), respectively. Only MLT cows had differences in nBCS and ΔBCS across calving periods: The lowest nBCS were identified in late spring (2.71 ± 0.02), early summer (2.71 ± 0.02), and in late summer (2.71 ± 0.02). The greatest losses in BCS also occurred in early summer (−0.41 ± 0.02) and in late spring (−0.41 ± 0.02). Time from calving to nBCS varied among calving periods and depended on parity category. Primiparous cows reached nBCS earlier in late summer (65 ± 8 DIM) and late spring (68 ± 7 DIM), while MLT had the shortest times to nBCS in late and early fall (67 ± 5 DIM; 68 ± 5 DIM). Greater values at milk peak were associated with lower nBCS only in multiparous cows during the late spring period. We concluded that the dynamics of BCS were associated with calving period in both parity groups. This data could help guide decisions on nutrition and breeding strategies in farms facing comparable conditions.

A practical and affordable surgical light-integrated camera system for dermatologic surgery video recordings

A practical and affordable surgical light-integrated camera system for dermatologic surgery video recordings

Consecutive diagnosis of nanosecond pulsed discharge in a coaxial electrode configuration using a quadruple emICCD camera system

Abstract Understanding the rapid dynamics of the primary streamer is crucial for comprehending the nanosecond pulsed discharge process. To reveal the fast primary streamer process, this study introduces a newly developed quadruple emICCD camera system capable of capturing a sequence of four discharge images in single pulse, coupled with self-customized software for data analysis. A nanosecond pulse power with its FWHM of 10.5 ns was applied to a coaxial reactor, focusing on the dynamics of the primary streamer. Our research clarifies the spatiotemporal variations of the primary streamer’s properties and examines their relation with inner electrode diameter (i.d. 0.2–2.0 mm). Results showed that in a pulse-powered coaxial electrode, there are three stages in the primary streamer process and that i.d. serves as an important factor influencing the formation and propagation of streamers. Interestingly, we found that streamer head velocity, streamer width, and streamer area for individual streamers remain constant prior to streamer channels reaching the outer electrode. Furthermore, we also observed an initial increase followed by a decrease in both streamer head velocity and streamer width with increasing i.d values. This study sheds light on the fundamental properties of the primary streamer during nanosecond pulsed discharge, contributing valuable insights for future plasma applications.

Augmented Reality-Based Chronic Wound Healing Assessment Using 3D Stereoscopic Imaging and Self-Organizing Maps

Background: Chronic wounds (CW) present significant public health challenges, impacting individuals' well-being and daily activities. Traditional wound measurement methods, such as the ruler technique, are time-consuming, imprecise, and pose infection risks. Advances in wound care technology, including artificial intelligence (AI) and augmented reality (AR), have improved wound healing (WH) assessment accuracy and enhanced clinician-patient communication. Methods: This study developed a novel CW evaluation device combining AR and a stereoscopic camera system. The device captures images using two Leopard Imaging LI-OV580 stereo cameras and a pico-projector to create a 3D wound model. The system calculates the wound area by processing stereoscopic images, utilizing structured-from-motion techniques and convolutional neural networks (CNNs). Additionally, the device measures epipolar and projection errors (PE) during AR-based wound evaluation. A Self-Organizing Map (SOM) was employed to refine the 3D reconstruction of the wound. Results: The AR-PE analysis demonstrated the device's accuracy, with the lowest PE recorded at 20 cm from the wound area. The projection error increased as the measurement distance moved toward the edges of the wound. The average epipolar error (EE) was 0.46 pixels, indicating high precision in stereoscopic measurements. Conclusion: The study introduced a non-invasive CW evaluation device that improves wound assessment accuracy and clinician-patient interaction. By utilizing 3D wound modeling and AR, the system enables more effective communication and progress tracking during WH. The results suggest this technology could enhance CW management, offering a reliable alternative to traditional methods.

Efficacy of a Combination Treatment of Ablative Fractional Carbon Dioxide Laser Therapy and Recombinant Human Epidermal Growth Factor for Atrophic Acne Scars.

Atrophic acne scars (AAS) are disfiguring and permanent changes caused by inflammatory acne. Fractional carbon dioxide is a common ablative device used to treat this condition. However, issues such as unclear effectiveness, frequent treatments, and potential side effects exist. In recent years, recombinant human epidermal growth factor (rhEGF) has also been frequently reported for its application in the treatment of acne scars. To explore the potential synergistic effect of fractional carbon dioxide laser combined with rhEGF in AAS treatment. We enrolled 15 patients with AAS. They received fractional carbon dioxide laser treatment and were then randomly assigned to receive either rhEGF or a placebo on one side of the face. The procedure was repeated three times, and the results were evaluated using the échelle d'évaluation clinique des cicatrices d'acné (ECCA) score and analyzed using the CBS camera system, 3D analysis (3DMD). Reflectance confocal microscopy (RCM) examination was also conducted. Both sides exhibited significant improvement in the appearance of the acne scars after treatment, as confirmed by the ECCA score, 3DMD data, and CBS texture score. On the rhEGF-treated side, the pore number and epidermal pigment area significantly improved as compared to the control side, whereas no significant differences were observed in the other data. Under RCM, a significant increase in epidermal thickness and appearance of reticular collagen fibers in the dermal layer after treatment was observed. Compared to the sole use of laser, the combination of fractional carbon dioxide laser and rhEGF does not significantly enhance scar therapeutic effects. However, it does shorten the recovery period after laser treatment and improves the pore appearance.

Delivery of luminescent particles to plants for information encoding and storage

In the era of smart agriculture, the precise labeling and recording of growth information in plants pose challenges for modern agricultural production. This study introduces strontium aluminate particles coated with H3PO4 as luminescent labels capable of spatial embedding within plants for information encoding and storage during growth. The encapsulation with H3PO4 imparts stability and enhanced luminescence to SrAl2O4:Eu2+,Dy3+ (SAO). Using SAO@H3PO4 as a low-damage luminescent label, we implement its delivery into plants through microneedles (MNs) patches. The embedded SAO@H3PO4 within plants exhibits sustained and unaltered high signal-to-noise afterglow emission, with luminous intensity remaining at approximately 78% of the original for 27 days. To cater to diverse information recording needs, MNs of various geometric shapes are designed for loading SAO@H3PO4, and the luminescent signals in different shapes can be accurately identified through a designed program, the corresponding information can be conveniently viewed on a computer. Additionally, inspired by binary information concepts, MNs patches with specific arrangements of luminescent and non-luminescent points are created, resulting in varied luminescent MNs arrays on leaves. An advanced camera system with a tailored program accurately identifies and maps the labels to the corresponding recorded information. These findings showcase the potential of low-damage luminescent labels within plants, paving the way for convenient and widespread storage of plant growth information.

AI-Based Integrated Smart Process Sensor for Emulsion Control in Industrial Application

In industry, reliable process supervision is essential to ensure efficient, safe, and high-quality production. The droplet size distribution represents a critical quality attribute for emulsification processes and should be monitored. For emulsion characterization, image-based analysis methods are well-known but are often performed offline, leading to a time-delayed and error-prone process evaluation. The use of an integrated smart process sensor to characterize the emulsification process over time enables the real-time evaluation of the entire system. The presented integrated smart process sensor consists of an optical measurement flow cell built into a camera system. The overall system is placed in a bypass system of a production plant for emulsification processes. AI-based image evaluation is used in combination with a feature extraction method (You Only Look Once version 4 (YOLOv4) and Hough circle (HC)) to characterize the process over time. The sensor system is installed in the plant and tested with different cosmetic products. Various iteration, prototyping, and test steps for the final sensor design are performed prior to this in a laboratory test setup. The results indicate robust and accurate detection and determination of the droplet size in real time to improve product control and save time. For benchmarking the integrated smart process sensor, the results are compared with common analysis methods using offline samples.

Unveiling Users' Security and Privacy Concerns Regarding Smart Home IoT Products from Online Reviews

The Internet of Things (IoT) has revolutionized the global market with lifestyle products such as fitness trackers (FT), smart home speakers (SHS), and surveillance and security camera systems (SSCS). While offering convenience, these products also introduce potential security and privacy (S&P) risks to buyers, often going unnoticed. Consumers’ incomplete mental models of the risks involved and the information asymmetry between buyers and sellers only add to the problem. Understanding consumer concerns in online product reviews can play a crucial role in bridging the gap of such information asymmetry. By establishing a balanced flow of information between buyers and sellers, manufacturers can leverage genuine concerns expressed in reviews to enhance product features while educating users about misinformation in reviews. In this study, we collected FT, SHS, and SSCS product reviews from three Amazon domains: the US, the UK, and India. Using a keyword-based search method focused on S&P concerns, we discovered a considerable number of reviews expressing notable concerns regarding security and privacy. Our qualitative analysis revealed that data security is a common concern across all product types. Further, our quantitative analysis exposed significant geographic variations, with the concern ratio being higher in the US than in the UK for all device types and higher than in the Indian domain for security cameras. These findings highlight the need for tailored security measures and user awareness campaigns in different parts of the world to address the identified concerns effectively.

On the Travel of State Crimes by Algorithm: Chinese Camera Systems in Israel

On the Travel of State Crimes by Algorithm: Chinese Camera Systems in Israel

Kinematics of mandibular advancement devices (MADs): Why do some MADs move the lower jaw backward during mouth opening?

Mandibular advancement devices (MADs) are widely used treatments for obstructive sleep apnea. MADs function by advancing the lower jaw to open the upper airway. To increase patient comfort, most patients allow the mouth to be opened. However, not all systems maintain the lower jaw in a forward position during mouth opening, which results in the production of a retrusion that favors the collapse of the upper airway. Furthermore, the kinematic behavior of the mechanism formed by the mandible-device assembly depends on jaw morphology. This means that, during mouth opening, some devices cause lower jaw protrusion in some patients, but cause its retraction in others. In this study, we report the behavior of well-known devices currently on the market. To do so, we developed a kinematic model of the lower jaw device assembly. This model was validated for all devices analyzed using a high-resolution camera system. Our results show that some of the devices analyzed here did not produce the correct behavior during patient mouth opening.Graphic abstract

Changing Australia's trading language has enhanced the implementation of objective carcase measurement technologies

In 2016 an Australian project, the Advanced Livestock Measurement Technologies project (ALMTech), was initiated to accelerate the development and implementation of technologies that measure lean meat yield and eating quality. This led to the commercial testing, and implementation of a range of new technologies in the lamb, beef, and pork industries. For measuring lean meat yield %, these technologies included dual energy X-ray absorptiometry, hand-held microwave systems, and 3-D imaging systems. For measuring beef rib-eye traits and intramuscular fat %, both pre- and post-chilling technologies were developed. Post-chilling, a range of camera systems and near infrared spectrophotometers were developed. While pre-chilling, technologies included insertable needle probes, nuclear magnetic resonance, and X-ray systems. Initially these technologies were trained to predict the pre-existing traits already traded upon within industry. However, this approach was limiting because the technologies could measure attributes that were either non-existent in the trading language, were superior as calibrating standards, or more accurately reflected value than the pre-existing trait. Therefore, we introduced IMF% into the trading language for both beef and sheep meat, and carcase lean%, fat%, and bone% for sheep meat. These new technologies and the traits that they predict have delivered multiple benefits. Technology provider-companies are instilled with the confidence to commercialise due to the provision of achievable accreditation standards. Processors have the confidence to invest in these technologies and establish payment grids based upon their measurements. And lastly, it has enhanced data flow into genetic databases, industry data systems (MSA), and as feedback to producers.

A novel 3D reconstruction method of blast furnace burden surface based on virtual camera array

Accurate three-dimensional (3D) blast furnace burden surface topography is crucial for optimizing material distribution and furnace operation. However, harsh conditions within the furnace pose challenges to this 3D reconstruction, such as difficulties in matching feature points and sparse 3D point clouds. To overcome these challenges, we propose a 3D reconstruction method for the blast furnace burden surface using virtual camera array. Firstly, an ORB feature extraction and matching method based on bidirectional optical flow tracking is proposed to solve the impact of illumination changes and noise. Then, the virtual camera array is constructed to generate a sparse 3D point cloud from an image sequence. Finally, dense surface reconstruction of the burden surface is achieved based on the improved PMVS and the Poisson surface reconstruction method. Experimental results demonstrate that the proposed method can extract accurate feature points and reconstruct the accurate 3D topography of the burden surface.

In situ observations of zooplankton show changes in abundance and swimming speed in response to hypoxia and acidification

AbstractZooplankton exhibit diverse swimming behaviors to reposition themselves in the water column, feed, find mates, and avoid predation. Environmental stressors that modify behavior can have cascading effects on population distributions and predator–prey interactions. Understanding zooplankton population dynamics is challenging, largely because traditional methods for quantifying zooplankton distributions are costly, limited in scope, and require extended analysis by trained analysts. We developed a novel methodology that combined remotely deployed camera systems, machine learning‐based identification of zooplankton, and video‐based tracking technology to quantify copepod and amphipod in situ swimming behavior in Hood Canal, WA, USA, a seasonally hypoxic and acidified fjord. Behavioral analysis showed copepods of all sizes swam on average 24% slower in stressful (hypoxic and acidified) waters relative to non‐stressful waters. Copepods exhibited less frequent escape responses in stressful waters, with a 68% decrease in the amount of time spent “jumping” for copepods 1–2 mm in length. Interestingly, abundances of small copepods increased in stressful waters, with 56% more 1–2 mm long copepods in stressful vs. non‐stressful conditions. In contrast, amphipods' average “darting” speeds did not differ between environmental conditions, but the abundance of amphipods significantly decreased in stressful waters relative to non‐stressful waters, suggesting avoidance of stressful conditions. Changes in swimming behavior are informative metrics in understanding ecosystem impacts of environmental stress because swimming speed has individual, population, and community‐level implications. Our results suggest that, among copepods, in situ behaviors may be useful proxies in monitoring the impacts of climate change on coastal ecosystems.

HabitSense: A Privacy-Aware, AI-Enhanced Multimodal Wearable Platform for mHealth Applications

Wearable cameras provide an objective method to visually confirm and automate the detection of health-risk behaviors such as smoking and overeating, which is critical for developing and testing adaptive treatment interventions. Despite the potential of wearable camera systems, adoption is hindered by inadequate clinician input in the design, user privacy concerns, and user burden. To address these barriers, we introduced HabitSense, an open-source1, multi-modal neck-worn platform developed with input from focus groups with clinicians (N=36) and user feedback from in-wild studies involving 105 participants over 35 days. Optimized for monitoring health-risk behaviors, the platform utilizes RGB, thermal, and inertial measurement unit sensors to detect eating and smoking events in real time. In a 7-day study involving 15 participants, HabitSense recorded 768 hours of footage, capturing 420.91 minutes of hand-to-mouth gestures associated with eating and smoking data crucial for training machine learning models, achieving a 92% F1-score in gesture recognition. To address privacy concerns, the platform records only during likely health-risk behavior events using SECURE, a smart activation algorithm. Additionally, HabitSense employs on-device obfuscation algorithms that selectively obfuscate the background during recording, maintaining individual privacy while leaving gestures related to health-risk behaviors unobfuscated. Our implementation of SECURE has resulted in a 48% reduction in storage needs and a 30% increase in battery life. This paper highlights the critical roles of clinician feedback, extensive field testing, and privacy-enhancing algorithms in developing an unobtrusive, lightweight, and reproducible wearable system that is both feasible and acceptable for monitoring health-risk behaviors in real-world settings.

3D mode shapes characterization under hammer impact using 3D-DIC and phase-based motion magnification

Modal analysis constitutes a fundamental aspect of structural investigation within diverse engineering domains, encompassing sectors such as automotive, wind energy, and aerospace. The prominence of high-frequency excitation loads, exemplified by the combustion phenomena in liquid rocket engines, necessitates an in-depth examination of the high-frequency vibrational response within structural components. However, the complexity of evaluating high-frequency vibrations arises from the negligible displacement associated with these responses. When using an optical full-field measurement system based on a high-speed camera for vibration measurement, it is usually severely affected by noise. Direct analysis of raw data using an optical measurement system (3D-DIC) is not feasible. In this paper, we combine phase-based motion magnification and digital image correlation methods to obtain the high-frequency vibration modes of the structure. 3D-DIC(3D Digital Image Correlation)analysis is performed on the magnified images to quantify the out-of-plane vibration modes of the structure. Using the cantilever beam as an example, the first five out-of-plane vibration mode shapes were separated from the response video under a single hammer excitation. Especially the 5th order natural frequency is as high as 3503 Hz, and the corresponding structural response was below the noise floor of the camera system. The vibration mode results obtained by this method are highly consistent with the vibration modes obtained by the 3D-SLDV(3D Scanning Laser Doppler Vibrometer) method. Finally, this method was applied to identify the out-of-plane vibration modes of real engine pipe. The combination of motion magnification techniques and DIC can enhance the capability of traditional 3D-DIC, which is beneficial for high-frequency structural identification. Future research could concentrate on optimizing motion amplification factors for different structures and loads, and creating automated algorithms for analyzing and visualizing amplified motion data in real time.

Vision-based autonomous robots calibration for large-size workspace using ArUco map and single camera systems

The low positioning accuracy of industrial robots limits their application in industry. Vision-based kinematic calibration, known for its rapid processing and economic efficiency, is an effective solution to enhance this accuracy. However, most of these methods are constrained by the camera's field of view, limiting their effectiveness in large workspaces. This paper proposes a novel calibration framework composed of monocular vision and computer vision techniques using ArUco markers. Firstly, a robot positioning error model was established by considering the kinematic error based on the Modified Denavit-Hartenberg model. Subsequently, a calibrated camera was used to create an ArUco map as an alternative to traditional single calibration targets. The map was constructed by stitching images of ArUco markers with unique identifiers, and its accuracy was enhanced through closed-loop detection and global optimization that minimizes reprojection errors. Then, initial hand-eye parameters were determined, followed by acquiring the robot's end-effector pose through the ArUco map. The Levenberg-Marquardt algorithm was employed for calibration, involving iterative refinement of hand-eye and kinematic parameters. Finally, experimental validation was conducted on the KUKA kr500 industrial robot, with laser tracker measurements as the reference standard. Compared to the traditional checkerboard method, this new approach not only expands the calibration space but also significantly reduces the robot's absolute positioning error, from 1.359 mm to 0.472 mm.

A Single-Pixel Event Photoactive Device for Real-Time, In-Sensor Spatiotemporal Optical Information Processing.

The increasing demand for energy-efficient, sophisticated optical sensing technologies in various applications, from machine vision to optical communication, highlights the necessity for innovations in spatiotemporal information sensing and processing at a nearly single-pixel scale. Traditional methods, including multi-pixel photodetector arrays and event-based camera systems, often fail to provide rapid, real-time detection and processing of dynamic events within the sensor. This shortcoming is particularly notable in handling high-dimensional spatiotemporal data, where the dependency on sequential data input and external processing tools leads to latency, reduced throughput, and heightened energy consumption, thereby impeding real-time parallel data processing capabilities. Here, a carrier-selective, single-pixel, position-sensitive planar photoactive device that integrates spatiotemporal event sensing with inherent short-term memory capabilities is introduced. The proof-of-concept single-pixel event photoactive device enables in-sensor spatiotemporal parallel optical information processing, efficiently managing multibit (>4 bit) data simultaneously and facilitating ultrafast (≈0.4µs) recognition of input patterns with low energy consumption (25 femtojoules). Additionally, by adjusting the operating speed from continuous to pulsed light illumination, the sensor array can detect trajectories and absolute position of events, offering in-sensor optical flow detection. This single-pixel event photodetector marks significant advancement toward developing compact, energy-efficient, ultrafast sensors suitable for a wide range of in sensor-based photonic applications.