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Technology and Health Care is intended to serve as a forum for the presentation of original articles and technical notes, observing rigorous scientific standards. Furthermore, upon invitation, reviews, tutorials, discussion papers and minisymposia are featured.
The following types of contributions and areas are considered:
1. Original articles:
Technology development in medicine: New concepts, procedures and devices associated with the use of technology in medical research and clinical practice are presented to a readership with a widespread background in engineering and/or medicine.
Significance of medical technology and informatics for healthcare: The appropriateness, efficacy and usefulness deriving from the application of engineering methods, devices and informatics in medicine and with respect to public health are discussed.
2. Technical notes:
Short communications on novel technical developments with relevance for clinical medicine.
3. Reviews and tutorials (upon invitation only):
Tutorial and educational articles for persons with a primarily medical background on principles of engineering with particular significance for biomedical applications and vice versa are presented.
4. Minisymposia (upon invitation only):
Under the leadership of a Special Editor, controversial issues relating to healthcare are highlighted and discussed by various authors.
Abstract: In these days, wearable devices have been developed for effectively measuring biological data. However, these devices have tissue allege and noise problem. To solve these problems, biometric measurement based on a non-contact method, such as face image sequencing is developed. This makes it possible to measure biometric data without any operation and side effects. However, it is impossible for a remote center to identify the person whose data are measured by the novel methods. In this paper, we propose the novel non-contact heart rate and blood pressure imaging system, Deep Health Eye. This system has authentication process at the same…time as measuring bio signals, through non-contact method. In the future, this system can be convenient home bio signal monitoring system by combined with smart mirror.
Keywords: Partial pressure suit, counter pressure, circulatory physiology, numerical model
Abstract: BACKGROUND: To improving the nursing level of diabetics, it is necessary to develop noninvasive blood glucose method. OBJECTIVE: In order to reduce the number of the near-infrared signal, consider the nonlinear relationship between the blood glucose concentration and near-infrared signal, and correct the individual difference and physiological glucose dynamic, 2 artificial neural networks (2ANN) combined with particle swarm optimization (PSO), named as PSO-2ANN, is proposed. METHOD: Two artificial neural networks (ANNs) are employed as the basic structure of the PSO-ANN model, and the weight coefficients of the two ANNs which represent the difference of…individual and daily physiological rule are optimized by particle swarm optimization (PSO). RESULTS: Clarke error grid shows the blood glucose predictions are distributed in regions A and B, Bland-Altman analysis show that the predictions and measurements are in good agreement. CONCLUSIONS: The PSO-2ANN model is a nonlinear calibration strategy with accuracy and robustness using 1550-nm spectroscopy, which can correct the individual difference and physiological glucose dynamics.
Keywords: Near-infrared technique, noninvasive, blood glucose detection, the PSO-2ANN model
Abstract: Myocardium characteristics differ markedly among individuals and play an important role in defibrillation threshold. The accuracy of simulation models used in most published studies are still have room to be improved and most of them only discussed the effect of myocardial anisotropy on defibrillation threshold. In our manuscript, a rabbit ventricular finite-element (FE) volume conductor model with high precision was constructed. Ventricular myocardium characteristics include cardiomyocyte coupling and the degree of myocardial anisotropy, which are represented as the value and the ratio of anisotropic conductivity, respectively. Quantitative analysis was performed simultaneously in terms of cardiomyocyte coupling and the degree of…myocardial anisotropy. Based on this, the combined effects of these two factors were further discussed. The electric field distributions of shocks and the defibrillation thresholds under different myocardial characteristics were simulated on this model. The simulation results revealed that as the degree of myocardial anisotropy increases, defibrillation threshold increases, and cardiomyocyte decoupling (decrease in electrical conductivity) can considerably increase the defibrillation threshold.
Abstract: BACKGROUND: Deaf people use sign or finger languages for communication, but these methods of communication are very specialized. For this reason, the deaf can suffer from social inequalities and financial losses due to their communication restrictions. OBJECTIVE: In this study, we developed a finger language recognition algorithm based on an ensemble artificial neural network (E-ANN) using an armband system with 8-channel electromyography (EMG) sensors. METHODS: The developed algorithm was composed of signal acquisition, filtering, segmentation, feature extraction and an E-ANN based classifier that was evaluated with the Korean finger language (14 consonants, 17 vowels and…7 numbers) in 17 subjects. E-ANN was categorized according to the number of classifiers (1 to 10) and size of training data (50 to 1500). The accuracy of the E-ANN-based classifier was obtained by 5-fold cross validation and compared with an artificial neural network (ANN)-based classifier. RESULTS AND CONCLUSIONS: As the number of classifiers (1 to 8) and size of training data (50 to 300) increased, the average accuracy of the E-ANN-based classifier increased and the standard deviation decreased. The optimal E-ANN was composed with eight classifiers and 300 size of training data, and the accuracy of the E-ANN was significantly higher than that of the general ANN.
Keywords: Finger language recognition, armband sensor, surface electromyography (EMG)
Abstract: The body-weight support (BWS) function, which helps to decrease load stresses on a user, is an effective tool for gait and balance rehabilitation training for elderly people with weakened lower-extremity muscular strength, hemiplegic patients, etc. This study conducts structural analysis to secure user safety in order to develop a rail-type gait and balance rehabilitation training system (RRTS). The RRTS comprises a rail, trolley, and brain-machine interface. The rail (platform) is connected to the ceiling structure, bearing the loads of the RRTS and of the user and allowing locomobility. The trolley consists of a smart drive unit (SDU) that assists the…user with forward and backward mobility and a body-weight support (BWS) unit that helps the user to control his/her body-weight load, depending on the severity of his/her hemiplegia. The brain-machine interface estimates and measures on a real-time basis the body-weight (load) of the user and the intended direction of his/her movement. Considering the weight of the system and the user, the mechanical safety performance of the system frame under an applied 250-kg static load is verified through structural analysis using ABAQUS (6.14-3) software. The maximum stresses applied on the rail and trolley under the given gravity load of 250 kg, respectively, are 18.52 MPa and 48.44 MPa. The respective safety factors are computed to be 7.83 and 5.26, confirming the RRTS’s mechanical safety. An RRTS with verified structural safety could be utilized for gait movement and balance rehabilitation and training for patients with hemiplegia.
Keywords: The body-weight support, rehabilitation, training system, gait movement
Abstract: Pressure Injuries are chronic wounds that are formed due to the constriction of the soft tissues against bone prominences. In order to assess these injuries, the medical personnel carry out the evaluation and diagnosis using visual methods and manual measurements, which can be inaccurate and may generate discomfort in the patients. By using segmentation techniques, the Pressure Injuries can be extracted from an image and accurately parameterized, leading to a correct diagnosis. In general, these techniques are based on the solution of differential equations and the involved numerical methods are demanding in terms of computational resources. In previous work, we…proposed a technique developed using toroidal parametric equations for image decomposition and segmentation without solving differential equations. In this paper, we present the development of a mobile application useful for the non-contact assessment of Pressure Injuries based on the toroidal decomposition from images. The usage of this technique allows us to achieve an accurate segmentation almost 8 times faster than Active Contours without Edges (ACWE) and Dynamic Contours methods. We describe the techniques and the implementation for Android devices using Python and Kivy. This application allows for the segmentation and parameterization of injuries, obtain relevant information for the diagnosis and tracking the evolution of patient’s injuries.
Keywords: Pressure ulcer, image segmentation, mobile application, Python, Kivy, Android
Abstract: BACKGROUND: The conventional methods of speech enhancement, noise reduction, and voice activity detection are based on the suppression of noise or non-speech components of the target air-conduction signals. However, air-conduced speech is hard to differentiate from babble or white noise signals. OBJECTIVE: To overcome this problem, the proposed algorithm uses the bone-conduction speech signals and soft thresholding based on the Shannon entropy principle and cross-correlation of air- and bone-conduction signals. METHODS: A new algorithm for speech detection and noise reduction is proposed, which makes use of the Shannon entropy principle and cross-correlation with…the bone-conduction speech signals to threshold the wavelet packet coefficients of the noisy speech. RESULTS: The proposed method can be get efficient result by objective quality measure that are PESQ, RMSE, Correlation, SNR. CONCLUSION: Each threshold is generated by the entropy and cross-correlation approaches in the decomposed bands using the wavelet packet decomposition. As a result, the noise is reduced by the proposed method using the MATLAB simulation. To verify the method feasibility, we compared the air- and bone-conduction speech signals and their spectra by the proposed method. As a result, high performance of the proposed method is confirmed, which makes it quite instrumental to future applications in communication devices, noisy environment, construction, and military operations.
Keywords: Noise reduction, bone conduction, Shannon entropy, speech
Abstract: This study was conducted according to the method presented in the Republic of Korea Pharmacopoeia 11th Revision, aseptic test method to evaluate the suitability of sterilization for a sterile needle (4 Pin Multi-needle). In this study, four tests were conducted: sterility test, cytotoxicity test, acute toxicity test, skin sensitization test. First, in the aseptic test, the microorganism was not proliferated in the aseptic test of the medium. As a result of the performance test of the medium, it was confirmed that the microorganism developed within 3 days and the fungus was evident within 5 days. Based on this, it was…confirmed that the medium was suitable, and as a result of the aseptic test, the development of microorganisms was not observed during the total culture period. Based on these results, tests were conducted which were confirmed to be suitable for aseptic testing because the development of bacteria on the provided samples was not recognized. For cytotoxicity tests ISO10993-5; 2009 (Biological Evaluation of Medical Devices, Part 5: Test for in vitro Cytotoxicity). As a result, the MEM eluate of the test substance caused very slight cytotoxicity to the fibroblasts of the mouse and was judged to be Grade 1 (Slightly cytotoxic) according to the judgment standard of ISO 10993-5. On the other hand, solvent control, negative control and positive control showed the expected results on the test. Acute Toxicity Test Results: It was judged that there was no systemic toxicity change when ICR mice were treated with 50 mL/kg B.W. of the eluate of sterile injectable needle for 72 hours. Skin sensitization test result: The Hartley guinea pig was evaluated as a substance which is evaluated as a substance which does not induce any skin reaction when skin sensitization is applied to the dissected material of the sterile injectable needle and is weak in skin sensitivity. Based on the above tests, we will study the stability and efficacy of more reliable medical devices based on the verification and performance of medical devices.
Keywords: Meso-therapy, multi-Needle, medical device, safety evaluation
Abstract: BACKGROUND: Dermoscopy imaging has been a routine examination approach for skin lesion diagnosis. Accurate segmentation is the first step for automatic dermoscopy image assessment. OBJECTIVE: The main challenges for skin lesion segmentation are numerous variations in viewpoint and scale of skin lesion region. METHODS: To handle these challenges, we propose a novel skin lesion segmentation network via a very deep dense deconvolution network based on dermoscopic images. Specifically, the deep dense layer and generic multi-path Deep RefineNet are combined to improve the segmentation performance. The deep representation of all available layers is aggregated…to form the global feature maps using skip connection. Also, the dense deconvolution layer is leveraged to capture diverse appearance features via the contextual information. Finally, we apply the dense deconvolution layer to smooth segmentation maps and obtain final high-resolution output. RESULTS: Our proposed method shows the superiority over the state-of-the-art approaches based on the public available 2016 and 2017 skin lesion challenge dataset and achieves the accuracy of 96.0% and 93.9%, which obtained a 6.0% and 1.2% increase over the traditional method, respectively. CONCLUSIONS: By utilizing Dense Deconvolution Net, the average time for processing one testing images with our proposed framework was 0.253 s.
Abstract: BACKGROUND: Soft tissue modeling plays an important role in the development of surgical training simulators as well as in robot-assisted minimally invasive surgeries. It has been known that while the traditional Finite Element Method (FEM) promises the accurate modeling of soft tissue deformation, it still suffers from a slow computational process. OBJECTIVE: This paper presents a Kalman filter finite element method to model soft tissue deformation in real time without sacrificing the traditional FEM accuracy. METHODS: The proposed method employs the FEM equilibrium equation and formulates it as a filtering process to estimate…soft tissue behavior using real-time measurement data. The model is temporally discretized using the Newmark method and further formulated as the system state equation. RESULTS: Simulation results demonstrate that the computational time of KF-FEM is approximately 10 times shorter than the traditional FEM and it is still as accurate as the traditional FEM. The normalized root-mean-square error of the proposed KF-FEM in reference to the traditional FEM is computed as 0.0116. CONCLUSIONS: It is concluded that the proposed method significantly improves the computational performance of the traditional FEM without sacrificing FEM accuracy. The proposed method also filters noises involved in system state and measurement data.