Search Results (10)

Eye movement detection technology holds significant potential across medicine, psychology, and human–computer interaction. However, traditional methods, which primarily rely on tracking the pupil and cornea during the open-eye state, are ineffective when the eye is closed. To address this limitation, we developed a novel system capable of real-time eye movement detection even in the closed-eye state. Utilizing a micro-camera based on the OV9734 image sensor, our system captures image data to construct a dataset of eyelid images during ocular movements. We performed extensive experiments with multiple versions of the YOLO algorithm, including v5s, v8s, v9s, and v10s, in addition to testing different sizes of the YOLO v11 model (n < s < m < l < x), to achieve optimal performance. Ultimately, we selected YOLO11m as the optimal model based on its highest AP0.5 score of 0.838. Our tracker achieved a mean distance error of 0.77 mm, with 90% of predicted eye position distances having an error of less than 1.67 mm, enabling real-time tracking at 30 frames per second. This study introduces an innovative method for the real-time detection of eye movements during eye closure, enhancing and diversifying the applications of eye-tracking technology. Full article

In this paper, we present the design and fabrication of a novel chip-on-tip catheter, which uses a microcamera and optical fibres to capture in vivo images in a beating porcine heart thanks to a saline flush to clear the blood field. Here, we demonstrate the medical utility and mechanical robustness of this catheter platform system, which could be used for other optical diagnostic techniques, surgical guidance, and clinical navigation. We also discuss some of the challenges and system requirements associated with developing a miniature prototype for such a study and present assembly instructions. Methods of clearing the blood field are discussed, including an integrated flush channel at the distal end. This permits the capture of images of the endocardial walls. The device was navigated under fluoroscopic guiding, through a guiding catheter to various locations of the heart, where images were successfully acquired. Images were captured at the intra-atrial septum, in the left atrium after a trans-septal cross procedure, and in the left ventricle, which are, to the best of our knowledge, the first images captured in an in vivo beating heart using endoscopic techniques. Full article

In vivo tissue imaging is an essential tool for medical diagnosis, surgical guidance, and treatment. However, specular reflections caused by glossy tissue surfaces can significantly degrade image quality and hinder the accuracy of imaging systems. In this work, we further the miniaturisation of specular reflection reduction techniques using micro cameras, which have the potential to act as intra-operative supportive tools for clinicians. In order to remove these specular reflections, two small form factor camera probes, handheld at 10 mm footprint and miniaturisable to 2.3 mm, are developed using different modalities, with line-of-sight to further miniaturisation. (1) The sample is illuminated via multi-flash technique from four different positions, causing a shift in reflections which are then filtered out in a post-processing image reconstruction step. (2) The cross-polarisation technique integrates orthogonal polarisers onto the tip of the illumination fibres and camera, respectively, to filter out the polarisation maintaining reflections. These form part of a portable imaging system that is capable of rapid image acquisition using different illumination wavelengths, and employs techniques that lend themselves well to further footprint reduction. We demonstrate the efficacy of the proposed system with validating experiments on tissue-mimicking phantoms with high surface reflection, as well as on excised human breast tissue. We show that both methods can provide clear and detailed images of tissue structures along with the effective removal of distortion or artefacts caused by specular reflections. Our results suggest that the proposed system can improve the image quality of miniature in vivo tissue imaging systems and reveal underlying feature information at depth, for both human and machine observers, leading to better diagnosis and treatment outcomes. Full article

Human–machine interaction (HMI) refers to systems enabling communication between machines and humans. Systems for human–machine interfaces have advanced significantly in terms of materials, device design, and production methods. Energy supply units, logic circuits, sensors, and data storage units must be flexible, stretchable, undetectable, biocompatible, and self-healing to act as human–machine interfaces. This paper discusses the technologies for providing different haptic feedback of different natures. Notably, the physiological mechanisms behind touch perception are reported, along with a classification of the main haptic interfaces. Afterward, a comprehensive overview of wearable haptic interfaces is presented, comparing them in terms of cost, the number of integrated actuators and sensors, their main haptic feedback typology, and their future application. Additionally, a review of sensing systems that use haptic feedback technologies—specifically, smart gloves—is given by going through their fundamental technological specifications and key design requirements. Furthermore, useful insights related to the design of the next-generation HMI devices are reported. Lastly, a novel smart glove based on thin and conformable AlN (aluminum nitride) piezoelectric sensors is demonstrated. Specifically, the device acquires and processes the signal from the piezo sensors to classify performed gestures through an onboard machine learning (ML) algorithm. Then, the design and testing of the electronic conditioning section of AlN-based sensors integrated into the smart glove are shown. Finally, the architecture of a wearable visual-tactile recognition system is presented, combining visual data acquired by a micro-camera mounted on the user’s glass with the haptic ones provided by the piezoelectric sensors. Full article

Freshness is one of the most important parameters for assessing the quality of avian eggs. Available techniques to estimate the degradation of albumen and enlargement of the air cell are either destructive or not suitable for high-throughput applications. The aim of this research was to introduce a new approach to evaluate the air cell of quail eggs for freshness assessment as a fast, noninvasive, and nondestructive method. A new methodology was proposed by using a thermal microcamera and deep learning object detection algorithms. To evaluate the new method, we stored 174 quail eggs and collected thermal images 30, 50, and 60 days after the labeled expiration date. These data, 522 in total, were expanded to 3610 by image augmentation techniques and then split into training and validation samples to produce models of the deep learning algorithms, referred to as “You Only Look Once” version 4 and 5 (YOLOv4 and YOLOv5) and EfficientDet. We tested the models in a new dataset composed of 60 eggs that were kept for 15 days after the labeled expiration label date. The validation of our methodology was performed by measuring the air cell area highlighted in the thermal images at the pixel level; thus, we compared the difference in the weight of eggs between the first day of storage and after 10 days under accelerated aging conditions. The statistical significance showed that the two variables (air cell and weight) were negatively correlated (R² = 0.676). The deep learning models could predict freshness with F1 scores of 0.69, 0.89, and 0.86 for the YOLOv4, YOLOv5, and EfficientDet models, respectively. The new methodology for freshness assessment demonstrated that the best model reclassified 48.33% of our testing dataset. Therefore, those expired eggs could have their expiration date extended for another 2 weeks from the original label date. Full article

The use of stem cells for regenerative applications and immunomodulatory effect is increasing. Amniotic epithelial cells (AECs) possess embryonic-like proliferation ability and multipotent differentiation potential. Despite the simple isolation procedure, inter-individual variability and different isolation steps can cause differences in isolation yield and cell proliferation ability, compromising reproducibility observations among centers and further applications. We investigated the use of a new technology as a diagnostic tool for quality control on stem cell isolation. The instrument label-free separates cells based on their physical characteristics and, thanks to a micro-camera, generates a live fractogram, the fingerprint of the sample. Eight amniotic membranes were processed by trypsin enzymatic treatment and immediately analysed. Two types of profile were generated: a monomodal and a bimodal curve. The first one represented the unsuccessful isolation with all recovered cell not attaching to the plate; while for the second type, the isolation process was successful, but we discovered that only cells in the second peak were alive and resulted adherent. We optimized a Quality Control (QC) method to define the success of AEC isolation using the fractogram generated. This predictive outcome is an interesting tool for laboratories and cell banks that isolate and cryopreserve fetal annex stem cells for research and future clinical applications. Full article

The present work proposed a low-cost portable device as an enabling technology for agriculture using multispectral imaging and machine learning in soil texture. Clay is an important factor for the verification and monitoring of soil use due to its fast reaction to chemical and surface changes. The system developed uses the analysis of reflectance in wavebands for clay prediction. The selection of each wavelength is performed through an LED lamp panel. A NoIR microcamera controlled by a Raspberry Pi device is employed to acquire the image and unfold it in RGB histograms. Results showed a good prediction performance with R² of 0.96, RMSEC of 3.66% and RMSECV of 16.87%. The high portability allows the equipment to be used in a field providing strategic information related to soil sciences. Full article

Existing laparoscopic surgery systems use a single laparoscope to visualize the surgical area with a limited field of view (FoV), necessitating maneuvering the laparoscope to search a target region. In some cases, the laparoscope needs to be moved from one surgical port to another one to detect target organs. These maneuvers would cause longer surgical time and degrade the efficiency of operation. We hypothesize that if an array of cameras can be deployed to provide a stitched video with an expanded FoV and small blind spots, the time required to perform multiple tasks at different sites can be significantly reduced. We developed a micro-camera array that can enlarge the FoV and reduce blind spots between the cameras by optimizing the angle of cameras. The video stream of this micro-camera array was designed to be processed in real-time to provide a stitched video with the expanded FoV. We mounted this micro-camera array to a Fundamentals of Laparoscopic Surgery (FLS) laparoscopic trainer box and designed an experiment to validate the hypothesis above. Surgeons, residents, and a medical student were recruited to perform a modified bean drop task, and the completion time was compared against that measured using a traditional single-camera laparoscope. It was observed that utilizing the micro-camera array, the completion time of the modified bean drop task was $203\pm 55$ s while using the laparoscope, the completion time was $245\pm 114$ s, with a p-value of 0.00097. It is also observed that the benefit of using an FoV-expanded camera array does not diminish for subjects who are more experienced. This test provides convincing evidence and validates the hypothesis that expanded FoV with small blind spots can reduce the operation time for laparoscopic surgical tasks. Full article

This paper proposes a magnetic actuator using multiple vibration components to perform locomotion in a complex pipe with a 25 mm inner diameter. Due to the desire to increase the turning moment in a T-junction pipe, two vibration components were attached off-center to an acrylic plate with an eccentricity of 2 mm. The experimental results show that the magnetic actuator was able to move at 40.6 mm/s while pulling a load mass of 20 g in a pipe with an inner diameter of 25 mm. In addition, this magnetic actuator was able to move stably in U-junction and T-junction pipes. If a micro-camera is implemented in the future, the inspection of small complex pipes can be enabled. The possibility of inspection in pipes with a 25 mm inner diameter was shown by equipping the pipe with a micro-camera. Full article

Pulse transit time (PTT) is an important physiological parameter that directly correlates with the elasticity and compliance of vascular walls and variations in blood pressure. This paper presents a PTT estimation method based on photoplethysmographic imaging (PPGi). The method utilizes two opposing cameras for simultaneous acquisition of PPGi waveform signals from the index fingertip and the forehead temple. An algorithm for the detection of maxima and minima in PPGi signals was developed, which includes technology for interpolation of the real positions of these points. We compared our PTT measurements with those obtained from the current methodological standards. Statistical results indicate that the PTT measured by our proposed method exhibits a good correlation with the established method. The proposed method is especially suitable for implementation in dual-camera-smartphones, which could facilitate PTT measurement among populations affected by cardiac complications. Full article