Showing 1–12 of 26 results
A novel neural interfacing electrode array for electrical stimulation and simultaneous recording of EEG/EMG/ENG$15.00
Abstract: Neural interface is man-made information pathway through which biological nerve system could communicate directly with electromechanical devices including computer, robot and even cyborg. This paper introduces a novel neural interfacing electrode array capable of bidirectional information transmission and multi-signals recording. The novel flexible electrode array with 32 channels enables close-looped control and feedback neural interfacing researches with the capability of both electrical stimulation and simultaneous recording of electroencephalogram (EEG), electromyogram (EMG), electroneurogram (ENG) signals. The electrochemical impedance spectroscopy (EIS) measurement of the electrode array was carried out to evaluate the electrode array electrochemical performance in the electrophysiology frequency range. Electrical stimulation to peripheral nerve was performed with various stimulation configuration of ENG electrode site pairs to produce distinct activation patterns. Muscle action potentials of the gastrocnemius of the hind limb indicated different configuration of electrode site pairs could generate distinct stimulating effect. In addition, three groups of in vivo experiments were conducted to demonstrate the recording ability of the electrode array for nerve signals. The data from 32 channels verified the effectiveness of this flexible electrode array in simultaneous recording of EEG/EMG/ENG in vivo.
Construction of a focused ultrasound neuromodulation system for the treatment of epileptic seizure$15.00
Abstract: Thus far, Ultrasound has been proved to be useful for noninvasively stimulating brain activity and has hope to play a positive role in the treatment of neurological diseases. Epilepsy is a neurological disorder in which brain activity becomes abnormal, causing seizures or periods of unusual behavior, and sometimes loss of awareness. In this paper, we established a focused ultrasound (FUS) neuromodulation system for the treatment of epilepsy. We used the chemically-induced rat epilepsy model to explore the effect of pulsed focused ultrasound on epilepsy, and obtained preliminary experimental results. We have proved the feasibility of this system through experiments, which can be used in the treatment of epilepsy by ultrasound neuromodulation.
Image Segmentation-Based Face Tracking on Thermal Images for Automatic Estimation of Psychophysiological States Using Facial Skin Temperature Distribution$15.00
Abstract: In human-machine system, human and machine need to recognize each other’s state with continuously, quantitatively and real-time property. Facial skin temperature could be measured with these properties by infrared thermography. The non-contact property is a great advantage in bioinstrumentation. Previous studies have been reported the availability of facial skin temperature for evaluation of psychophysiological states of a human such as stress, drowsiness and emotion. On the other hand, the development of the face detection and tracking techniques on thermal images are necessary for the automatic evaluation of psychophysiological states of a human based on facial skin temperature, measured by infrared thermography. The objective of this study is to establish the technique for face detection and tracking on thermal images. In this study, the algorithm consisting of three phases: (A) human detection based on inter-frame difference, (B) face detection based on image segmentation, and (C) face tracking based on temporal analysis, is proposed. As a result, the face region on thermal images could be detected and tracked with high precision. However, a part with low temperature such as the back of nasal and cheek was classified as a region other than a face.
Keywords: Thermal image; face tracking; image segmentation
Effect of Shoes on Lower Extremity Pain and Low Back during Prolonged$15.00
Abstract: Media with 16o slope is an effective solution to reduce low back pain risk caused by prolonged standing. In this study, we examine the effect of shoes on lower back pain caused by prolonged standing for 2 hours on sloping medium. However, prolonged standing has another major risk: lower extremity pain. Many studies have shown that this risk can be affected by shoes type or characteristic. Hence, lower extremity pain risk is the main concern in this research. Two types of shoes observed in this study are Safety Shoes and Slip-On Shoes, as these are the most widely used in the manufacturing industry. Using the Surface Electromyography (S-EMG) method, the difference in Medial Gastrocnemius muscle response was measured against both types of shoes. The study showed that both types of shoes have different muscle activation values and the Safety Shoes showed greater activation. This result proves that, type of shoes may affect the amount of lower extremity pain caused while standing for 2 hours on sloping medium and Safety Shoes poses a greater lower extremity risk. Both Visual Analog Scale (VAS) and Foot Pain Questionnaire methods supported the finding. While the results of VAS method found standing for 2 hours on sloping medium has a greater lower extremity pain than low back pain risk. Foot Pain Questionnaire method indicated that the activity of standing for 2 hours over sloping medium causes a high pain on thumb toe and the back of foot. Based on this study, it can be concluded that it is necessary to design a special shoe for prolonged standing occupation on a sloping medium that can reduce the lower extremity pain risk, besides low back pain risk
Keywords: Biomechanics, ergonomics, lower extremity pain, low back pain, prolonged standing, shoes, surface-electromyography.
Calibration of Surgical Knife-Tip Position with Marker-Based Optical Tracking Camera and Precise Evaluation of Its Measurement Accuracy$15.00
Abstract: We have been developing a liver surgery support system in collaboration with Kansai Medical University Hospital. Our surgical support system issues a warning when the surgical knife approaches a vital nerve or large blood vessel that should not be cut. It is also able to navigate the knife-tip to appropriately resect a tumor. Our system estimates the position and orientation of the surgical knife and the target organ using two distance cameras during surgery. The distance between the knife-tip and the blood vessels inside the organ is measured in real-time. In this paper, we present the details of our liver surgery support system and report the accuracy of the knife-tip positioning. The experimental results show that the position estimation error of the knife-tip is 0.3 mm and the standard deviation is 0.3 mm. The error of the distance between the estimated knife-tip positions on the neighboring grid points was 0.1 mm. This result satisfies the doctor’s surgical requirement.
Keywords: Surgical knife positioning; Calibration; Liver; Accuracy;
An Implementation of Medical Image Mosaicing System Based on Oriented FAST and Rotated BRIEF Approach$15.00
Abstract: Image stitching is a technique that combines two or more images that are taken from different view of the same scene to obtain a panoramic image. Image stitching is used in medical applications for stitching of X-ray images. As the traditional system of X-ray machine cannot capture the whole body structure in a single image. So, images stitching solves this problem by combining two or more x-ray images into a large view one. This paper proposes an algorithm which automatically stitches the x-ray images with overlapped region. The stitching method is based on ORB features (Oriented FAST and Rotated BRIEF features). The proposed system is designed with five stages, preprocessing, features extraction, features matching, Homography estimation and images stitching. In feature detection stage, Oriented FAST approach is used. In feature description stage, Rotated BRIEF approach is applied. The two primary parameters for measuring the stitching performance are the quality of the resultant image and the processing time. Therefore, the main objective of this paper is to produce a high quality image stitching system with low processing time. First, we compare many different features detectors. We test SIFT method, SURF method, Harris corner detector and ORB approach to measure the correct detection rate of the feature points and computation time. Second, we measure the quality of result images that produced by stitching system of different feature detection methods. From experimental results, we conclude that ORB approach is the fastest, more accurate, and higher performance.
Keywords: Biomedical images; Feature based approach ; Image stitching; ORB features ; Panorama
Optogenetics-based Neuromodulation for the Alleviation of hemi-Parkinsonian Motor Asymmetry in Rat$15.00
Abstract: The development of more effective deep brain stimulation (DBS) paradigms for Parkinson’s disease is limited by the non-specific nature of electrical stimulation. Optogenetics, with its spatial and cell-type specificity, is a potential alternative therapeutic approach. In 6-hydroxydopamine-induced hemi-Parkinsonian rats, we investigated the therapeutic values of optogenetic modulation of the subthalamic nucleus (STN) and the motor cortex. Here we report optogenetic inhibition of principal neurons in the STN significantly improved hemi-Parkinsonian motor asymmetry, measured by amphetamine-induced rotations. We also show preliminary results that revealed therapeutic improvement in motor asymmetry by single-site optogenetic excitation of the motor cortex. Although improvement from optogenetic modulations did not exceed the effects of DBS in the STN, our findings suggest that spatially patterned optogenetic stimulation of the cortex, i.e., more precise manipulation of cortical activity over larger area, should be investigated as a therapeutic approach for Parkinson’s disease.
The Role of Neuroimaging in Diagnosis of Neurodegenerative Disease$15.00
Abstract: Imaging the human body is one of the most important aspects of medical science in clinics and research. Due to the increasing spread of diseases related to the nervous system, neuroimaging has grown substantially in the last two decades. In this study, neuroimaging techniques that are used to diagnose neurodegenerative diseases have been expressed. Clinical applications of each neuroimaging method have also been reviewed. Some imaging techniques create structural and anatomical images, and some provide physiological and functional images. Recent advances in neuroimaging have led to the creation of hybrid techniques. In these multimodality methods, structural and functional images are combined. This feature leads to increased accuracy in the diagnosis of neurodegenerative diseases.
Controlling 3D Object made of CT data in Medical Training System Using Leap Motion$15.00
Abstract: This paper describes a user interface of 3D (three-dimensional) object converted from 2D (two-dimensional) CT data in DICOM format using Leap Motion device that can be used as a medical training system for medical students and interns. The resultant data can be controlled in a 3D development environment of Unity software. The system consists of desktop computer, the displaying software environment and Leap Motion device. The experimental results show that we can have a desirable control over the rendered object in 360 degrees, and that we can check the details of the object using zooming feature in the system.
Multi-label classification of brain tumor mass spectrometry data. In pursuit of tumor boundary detection method.$15.00
Abstract: The mass-spectrometry is the promising tool for the fast characterization of brain biopsy samples as a part of the intraoperative identification of tumor boundary. The spray-from-tissue ambient ionization method is a new instrument for mass-spectrometry analysis of soft tissues without sample preparation. In this contribution, we analyze the performance of multi-label classification techniques in detection of the tumor and necrosis fragments within the sample.
Decision Making Using Fuzzy Cognitive Maps in Post-Triage of Non-Critical Elderly Patients$15.00
Abstract: For patients arriving in the Emergency Departments (EDs) of hospitals a key aspect is to classify patients and identify high-risk patients since they have the potential for rapid deterioration during the waiting time. Triage is a widely applied and well-known process of evaluating and categorizing patients’ condition, in EDs. On the other hand, EDs are frequently overcrowded, which makes triage an extremely challenging and demanding process in order to ensure that patients stepping into the ED are given the appropriate medical attention in time. This paper discusses the introduction of a general decision making procedure based on Fuzzy Cognitive Maps so that to create a Medical Decision Support System for Post-Triage decisions. The case of non-emergent and non-urgent elderly patients is examined and the corresponding model is developed.
Supervised Learning-based Nuclei Segmentation on Cytology Pleural Effusion Images with Artificial Neural Network$15.00
Abstract: Automated segmentation of cell nuclei is the crucial step towards computer-aided diagnosis system because the morphological features of the cell nuclei are highly associated with the cell abnormality and disease. This paper contributes four main stages required for automatic segmentation of the cell nuclei on cytology pleural effusion images. Initially, the image is preprocessed to enhance the image quality by applying contrast limited adaptive histogram equalization (CLAHE). The segmentation process is relied on a supervised Artificial Neural network (ANN) based pixel classification. Then, the boundaries of the extracted cell nuclei regions are refined by utilizing the morphological operation. Finally, the overlapped or touched nuclei are identified and split by using the marker-controlled watershed method. The proposed method is evaluated with the local dataset containing 35 cytology pleural effusion images. It achieves the performance of 0.95%, 0.86 %, 0.90% and 92% in precision, recall, F-measure and Dice Similarity Coefficient respectively. The average computational time for the entire algorithm took 15 mins per image. To our knowledge, this is the first attempt that utilizes ANN as the segmentation on cytology pleural effusion images.