No abstract available.
Photoacoustic Techniques ; Multimodal Imaging ; Spectrum Analysis

Electrochemical skin conductance (ESC) has been suggested as a noninvasive diabetic screening tool. We examined the relevance of ESC method for screening type 2 diabetes. A meal tolerance test (MTT) was conducted for 40 diabetic and 42 control subjects stratifi ed by age, sex and body mass index (BMI). The glucose levels and ESC were measured before the MTT and every 30 min after meal intake up to 120 min. There was no correlation between the blood glucose level and ESC (r = 0.249) or ESC variability (ESCV) (r = −0.173). ESC (ESCV) was higher (lower) in diabetic patients than in normal control (p = 0.02 for ESC and p = 0.06 for ESCV). Receiver operating characteristic analysis showed that the area under the curve (AUC) values of the ESC and ESCV were 0.654 and 0.691, respectively. The novel variable, ESCV, showed 5.7% higher AUC than ESC. Contrary to some previous reports, ESC values in diabetic patients was higher than in age, sex and BMI matched control group. In our study, ESC or ESCV showed a marginal accuracy to be used as a screening tool for diabetes mellitus.
Area Under Curve ; Blood Glucose ; Body Mass Index ; Diabetes Mellitus ; Glucose ; Glucose Tolerance Test ; Humans ; Mass Screening ; Meals ; Methods ; ROC Curve ; Skin

Recent studies have developed simple techniques for monitoring and assessing sleep. However, several issues remain to be solved for example high-cost sensor and algorithm as a home-use device. In this study, we aimed to develop an inexpensive and simple sleep monitoring system using a camera and video processing. Polysomnography (PSG) recordings were performed in six subjects for four consecutive nights. Subjects' body movements were simultaneously recorded by the web camera. Body movement was extracted by video processing from the video data and fi ve parameters were calculated for machine learning. Four sleep stages (WAKE, LIGHT, DEEP and REM) were estimated by applying these fi ve parameters to a support vector machine. The overall estimation accuracy was 70.3 ± 11.3% with the highest accuracy for DEEP (82.8 ± 4.7%) and the lowest for LIGHT (53.0 ± 4.0%) compared with correct sleep stages manually scored on PSG data by a sleep technician. Estimation accuracy for REM sleep was 68.0 ± 6.8%. The kappa was 0.19 ± 0.04 for all subjects. The present non-contact sleep monitoring system showed suffi cient accuracy in sleep stage estimation with REM sleep detection being accomplished. Low-cost computing power of this system can be advantageous for mobile application and modularization into home-device.
Machine Learning ; Methods ; Mobile Applications ; Polysomnography ; Sleep Stages ; Sleep, REM ; Support Vector Machine

In this study, we developed an aluminum-load-cell-based wireless Ringer's solution monitoring and alarm (WRMA) system. The Al load cell was designed with a rectangular shape, and the load was concentrated in the lower beam part of the load cell because of the anisotropic thickness. From the static analysis, we identifi ed the appropriate location for a Wheatstone bridge circuit consisting of four strain gauges. In addition, the modal and harmonic analyses showed that the vibrational frequencies of the hospital environment do not seriously interfere with the output voltage of the Al load cell. However, random vibrations generated by the movement of the WRMA system on various surfaces severely increase the standard deviation of the measured solution weight by ± 10 g or more. Such vibrational error is too large because the average weight of Ringer's solution is 30–40 g at the time of replacing Ringer's solution. Thus, this error could be confusing for nurses and result in mistakes in the timely replacement of the Ringer's solution. However, the standard deviation of the measured weight was dramatically reduced to ± 3 g or less by using the vibration correction algorithm developed in the present study.
Vibration

Since the Compton camera was fi rst introduced, various types of conical Radon transforms have been examined. Here, we derive the inversion formula for the conical Radon transform, where the cone of integration moves along a curve in three-dimensional space such as a helix. Along this three-dimensional curve, a detailed inversion formula for helical movement will be treated for Compton imaging in this paper. The inversion formula includes Hilbert transform and Radon transform. For the inversion of Compton imaging with helical movement, it is necessary to invert Hilbert transform with respect to the inner product between the vertex and the central axis of the cone of the Compton camera. However, the inner product function is not monotone. Thus, we should replace the Hilbert transform by the Riemann–Stieltjes integral over a certain monotone function related with the inner product function. We represent the Riemann–Stieltjes integral as a conventional Riemann integral over a countable union of disjoint intervals, whose end points can be computed using the Newton method. For the inversion of Radon transform, three dimensional fi ltered backprojection is used. For the numerical implementation, we analytically compute the Hilbert transform and Radon transform of the characteristic function of fi nite balls. Numerical test is given, when the density function is given by a characteristic function of a ball or three overlapping balls.
Methods ; Radon

Brain disorder recognition has becoming a promising area of study. In reality, some disorders share similar features and signs, making the task of diagnosis and treatment challenging. This paper presents a rigorous and robust computer aided diagnosis system for the detection of multiple brain abnormalities which can assist physicians in the diagnosis and treatment of brain diseases. In this system, we used energy of wavelet sub bands, textural features of gray level co-occurrence matrix and intensity feature of MR brain images. These features are ranked using Wilcoxon test. The composite features are classifi ed using back propagation neural network. Bayesian regulation is adopted to fi nd the optimal weights of neural network. The experimentation is carried out on datasets DS-90 and DS-310 of Harvard Medical School. To enhance the generalization capability of the network, fi vefold stratifi ed cross validation technique is used. The proposed system yields multi class disease classifi cation accuracy of 100% in diff erentiating 90 MR brain images into 18 classes and 97.81% in diff erentiating 310 MR brain images into 6 classes. The experimental results reveal that the composite features along with BPNN classifi er create a competent and reliable system for the identifi cation of multiple brain disorders which can be used in clinical applications. The Wilcoxon test outcome demonstrates that standard deviation feature along with energies of approximate and vertical sub bands of level 7 contribute the most in achieving enhanced multi class classifi cation performance results.
Brain Diseases ; Brain ; Dataset ; Diagnosis ; Generalization (Psychology) ; Magnetic Resonance Imaging ; Schools, Medical ; Weights and Measures

The aim of this study was to examine the feasibility of the Smart dynamometer as a rehabilitation exercise device in a daily care by comparing with the existing medical devices. We used and analyzed clinical and measurement data of breast cancer survivors who have used Smart dynamometer during their rehabilitation after breast cancer surgery. The Smart dynamometer was compared with the two existing devices of Takei dynamometer and surface electromyography (sEMG) that were used in routine care, respectively. Three key components of the rehabilitation exercise devices were analyzed to validate the feasibility of the Smart dynamometer: grip strength, reaction time, and grip endurance time. Pearson's correlation analysis was performed to compare the statistical significance between the devices. The data of 12 and 15 female breast cancer patients were analyzed for comparing the Smart dynamometer with Takei dynamometer and sEMG, respectively. There was a very weak correlation between the maximum values from the Takei and the Smart dynamometers in the affected and non-affected arms of breast cancer patients (r = 0.5321, 0.4733). Comparisons of 3 features between the Smart dynamometer and sEMG showed that there were strong positive correlations for both reaction time and endurance time in the affected and non-affected arms (r > 0.9). The feasibility of the Smart dynamometer for the possible use in a daily rehabilitation exercise was partially verified. Moreover, since the Smart dynamometer was highly correlated with time-related variables, it was important and significant to measure both grip strength and time-related information.
Arm ; Breast Neoplasms ; Breast ; Electromyography ; Feasibility Studies ; Female ; Hand Strength ; Humans ; Reaction Time ; Rehabilitation ; Self Care ; Survivors

Keratoplasty, which is cornea transplant surgery, is one of the treatment methods for patients with turbidity or keratitis. Recently, keratoplasty using a surgical robot was studied to increase precision. In this study, the effect of surgical factors on the deformation and curvature of the cornea were analyzed in order to improve the accuracy of keratoplasty and derive the optimal surgical factors using finite element method (FEM). Suturing tension and depth were selected as surgical factors. An FEM model, a constitutive equation, and boundary conditions were determined using experiments and reference data. Suturing tension significantly impacted deformation and curvature change, and suturing depth affected the position of the thread-cornea contact point. Both factors have a significant impact on a focal point in the retina and the patient's visual acuity after keratoplasty.
Cornea ; Corneal Transplantation ; Finite Element Analysis ; Humans ; Keratitis ; Methods ; Retina ; Visual Acuity

Biomechanical properties of human gallbladder (GB) wall in passive state can be valuable to diagnosis of GB diseases. In the article, an approach for identifying damage effect in GB walls during uniaxial tensile test was proposed and a strain energy function with the damage effect was devised as a constitutive law phenomenologically. Scalar damage variables were introduced respectively into the matrix and two families of fibres to assess the damage degree in GB walls. The parameters in the constitutive law with the damage effect were determined with a custom MATLAB code based on two sets of existing uniaxial tensile test data on human and porcine GB walls in passive state. It turned out that the uniaxial tensile test data for GB walls could not be fitted properly by using the existing strain energy function without the damage effect, but could be done by means of the proposed strain energy function with the damage effect involved. The stresses and Young moduli developed in two families of fibres were more than thousands higher than the stresses and Young's moduli in the matrix. According to the damage variables estimated, the damage effect occurred in two families of fibres only. Once the damage occurs, the value of the strain energy function will decrease. The proposed constitutive laws are meaningful for finite element analysis on human GB walls.
Diagnosis ; Finite Element Analysis ; Gallbladder ; Humans ; Jurisprudence

Gaze or eye movements are used as a communication interface in daily life. Herein, we developed a simple method for gaze estimations based on planar approximations of voltage ratios calculated from multiple electro-oculogram signals not affected by drift phenomena, which decrease accuracy. Subsequently, we conducted simulations using an eyeball battery model and investigated the effects of adjusting electrode arrangements, determination coefficients for planar approximations of voltage ratios, and threshold values for angles between simultaneous linear equations, to improve the estimation accuracy and decreased the number of required electrodes. Numerical experiments were used to identify arrangements of six electrodes with errors that were approximately 5° less than those of nine-electrode L-shaped arrangements, indicating improved estimation accuracy with fewer electrodes.
Electrodes ; Eye Movements ; Methods