Medical and Biological Engineering

Robot Navigation Using a Brain Computer Interface Based on Motor Imagery Abstract An interface between a human brain and a computer (or any external device) can be implemented for interchanging orders using a brain–computer interface (BCI) system. Motor imagery (MI), which represents human intention to execute actions or movements, can be captured and analyzed using brain signals such as electroencephalograms (EEGs). The present study focuses on a synchronous control system with a BCI based on MI for robot navigation. We employ a new feature extraction technique using common spatial pattern (CSP) filtering combined with band power to form feature vectors. Linear discriminant analysis (LDA) is employed to classify two types of MI tasks (right hand and left hand). In addition, we have developed posture-dependent control architecture that translates the obtained MI into four robot motion commands: going forward, turning left, turning right, and stopping. The EEGs of eight healthy volunteer male subjects were recorded and employed to navigate a simulated robot to a goal in a virtual environment. On a predefined task, the developed BCI robot control system achieved its task in170 s with a collision number of 0.65, distance of 23.92 m, and successful command rate of 80%. Although the performance of the complete system varied from one subject to another, the robot always reached its final position successfully. The developed BCI robot control system yields promising results compared to manual controls.

Gender-Specific Kinematics for Rotational Coordination Between Hips and Lumbar Spine During Downswing Abstract The purpose of this study was to compare and evaluate the inter-joint coordination between the hips and lumbar spine in both male and female skilled golfers during the downswing phase. Six infrared MCAM2 cameras were used for capturing each participant's swing motion. In order to evaluate the inter-joint coordination, kinematic data and continuous relative phase (CRP) were obtained during downswing phase. The lead hip-lumbar spine CRP in male golfers showed a typical parabola pattern with a minimum value at around 60% of the downswing phase. On the other hand, the CRP between the lead hip and lumbar spine of female golfers barely changed from the initial to middle downswing stages, and increased at the later stage. Male golfers typically used their lead hip more than their lumbar spine during the early downswing, while the rotational contribution of the lumbar spine and lead hip in female golfers were comparable until the middle of the downswing phase. These findings result from the opposite rotation of the lumbar spine for even the early downswing phase due to the muscular and articular flexibility of female golfers. This study has the potential to help develop gender-specific coaching materials for the improvement of swing skills.

Complexity-Based Analysis of the Difference Between Normal Subjects and Subjects with Stuttering in Speech Evoked Auditory Brainstem Response Abstract Deficits in auditory processing are an assumed underlying mechanism in stuttering. Previous studies have demonstrated that speech evoked auditory brainstem response (s-ABR) is a reliable method to evaluate brainstem timing in clinical populations with persistent developmental stuttering (PDS). The examination of s-ABR signals to quantify differential complexities between PDS and normal subjects using linear analysis is unreliable. This prompted us to evaluate non-linear methods, which are more effective for conveying complex dynamics. The aim of the current study is to apply fractal dimension and the Hurst exponent to s-ABR signals in order to identify complexity differences between PDS and normal subjects who were stimulated with the synthetic/da/stimulus. Analysis of scaling exponents showed a statistically significant difference between the two groups. The s-ABR signal in subjects with stuttering becomes more complex due to stimulation. These findings are discussed in terms of dysfunctional sub-cortical activation in PDS populations.

A Modular Data Glove System for Finger and Hand Motion Capture Based on Inertial Sensors Abstract This study proposes a modular data glove system to accurately and reliably capture hand kinematics. This data glove system's modular design enhances its flexibility. It can provide the hand's angular velocities, accelerations, and joint angles to physicians for adjusting rehabilitation treatments. Three validations—raw data verification, static angle verification, and dynamic angle verification—were conducted to verify the reliability and accuracy of the data glove. Furthermore, to ensure the wearability of the data glove, 15 healthy participants and 15 participants with stroke were recruited to test the data glove and fill out a questionnaire. The errors of the finger ROMs obtained from the fusion algorithm were less than 2°, proving that the fusion algorithm can measure the wearer's range of motion accurately. The result of the questionnaire shows the participants' high satisfaction with the data glove. Moreover, a comparison between the proposed data glove and related research shows that the proposed data glove is superior to other data glove systems.

Mammographic Image Classification System via Active Learning Abstract Training an accurate prediction model for mammographic image classification is usually necessary to require a large number of labeled images. However, the manually acquiring rich and reliable annotations is known to be tedious and time-consuming process, especially for medical image. The advances in machine learning yielded a branch of technique, termed active learning (AL), which has been proposed for solving the problem of the limited training samples and expensive labeling cost, and has resulted in highly successful applications in many pattern recognition tasks such as image processing and speech recognition. In this article, a comparison is provided among the mammographic image classification systems, relying on traditional supervised learning, un-supervised learning and AL, aiming to obtain a system with low labeling cost. The experiments based on digital database for screening mammography demonstrate that the AL is able to minimize the labeling cost of mammographic image without sacrificing the accuracy of final classification system. In addition, some specific characteristics of mammographic image: file information and spatial feature, which are not available to the traditional AL methods, have been found to further decrease the labeling cost. In conclusion, we suggest that the AL is a reasonable alternative to supervised learning for the researchers in the field of medical image classification with limited experimental conditions.

Implementation of an Environmental Quality and Harmful Gases Monitoring System in Cloud Abstract The improvement of environmental quality is aligned with the betterment of life quality. Poor air quality has a greatest impact on people health, it links to cancer, long-term harm to cardiovascular and respiratory systems. Conversely, safe air quality free of harmful gases such as formaldehyde, volatile organic compounds and carbon monoxide helps to prevent disease and other health problems. The application of information technology can greatly enhance the effectiveness of ensuring good air quality. Therefore, the implementation of environmental quality and harmful gases monitoring system is beneficial to manage indoor air quality. In this work, we built an environment quality monitoring system, which can adjust the indoor air quality and monitor the concentration of formaldehyde, volatile organic compounds and carbon monoxide. If the environment comfort value is out of the standard, the system will give notification if the concentration of harmful gases exceeds the standard, and activates air ventilation and purification devices. With these real-time data, the proposed system can help people make right and timely decisions, and act in time to maintain a healthy environment in the monitored area.

The Ion Delivery Manner Influences the Antimicrobial Efficacy of Silver Oligodynamic Iontophoresis Abstract Introduction Electrical activation of silver ions, known as oligodynamic iontophoresis, has shown broad-spectrum antimicrobial activities against bacteria, fungi, and viruses. However, it is not clear how the ion delivery manner, which is controlled by the electrical activation, influences the iontophoresis process. This paper focuses on this knowledge gap, aiming to characterize the interactive effects of electric current intensity and activation duration on the antimicrobial efficacy of a silver-based iontophoresis prototype against Gram-positive (S. aureus) and Gram-negative (E. coli) strains respectively. Materials and Methods The modified Kirby–Bauer disc diffusion method was adopted to quantify the antimicrobial efficacy. A linear regression model was established and validated by empirical data. Conclusion This study revealed that the antimicrobial activities of the device was more sensitive to current duration than current intensity, and the marginal antimicrobial efficacy of the device decreased as the current intensity increased. In addition, a sustained release of Ag + had superior antimicrobial efficacy compared to a fast release. These findings will contribute to the performance optimization of silver oligodynamic iontophoresis devices for antimicrobial applications.

The Effects of Implant Orientations and Implant–Bone Interfacial Conditions on Potential Causes of Failure of Tibial Component Due to Total Ankle Replacement Abstract Aseptic loosening of implant components is a major issue of failure for total ankle replacement (TAR). One of the causes of implant loosening is a result of excessive bone density loss. This study is aimed at determining the effects of implant orientations and implant–bone interface conditions on the potential causes of failure of the tibial component. Three-dimensional finite element (FE) models of intact and implanted ankles were developed using computed tomography data sets. To understand the effect of implant orientations, four other FE models of the implanted ankle were developed separately, which consist of a variation of varus and valgus angles of 5° and 10°, respectively. Dorsiflexion and neutral and plantar flexion positions were considered as applied loading conditions. Orientations of the implant caused a decrease in strain energy density (SED) of the tibia bone away from the implant vicinity, where around 10–50 and 10–60% reduction in SED was found owing to the orientation of the 5° and 10° varus and valgus angles. Decreases in SED were found to be greater in the case of debonded implant–bone interface conditions compared to bonded interface conditions. This study indicates that proper bonding between implant and bone and implant orientation are important for long-term survival of the tibial component owing to TAR.

An Anonymity, Availability and Security-Ensured Authentication Model of the IoT Control System for Reliable and Anonymous eHealth Services Abstract eHealth is supported by electronic processes and communication. The Internet of Things (IoT) is utilized to realize smart healthcare, backup terminal devices are required for reliable eHealth services, and the IoT control system is essential for the security of IoT applications. In 2013, Yang et al. first added backup terminal devices, a status monitor device and an alarm module to the IoT control system and proposed an authentication mechanism for availability and security. In 2016, Chang et al. found that Yang et al.'s authentication model suffers from some drawbacks. In this paper, we adjust the operation and requirements of the IoT control system and take user anonymity into consideration to propose an authentication model for the IoT control system for reliable and anonymous eHealth services. To ensure anonymity of the user and the accessed service, the real identifiers will not be transmitted for untraceability. The proposed authentication model complies with six essential requirements. Via the proposed authentication model, the IoT control system can ensure reliable and anonymous eHealth services with anonymity, availability and security.

Experimental Research on the Impact of Alveolar Morphology on Deposition of Inhalable Particles in the Human Pulmonary Acinar Area Abstract Studying the deposition pattern of inhalable particles in the pulmonary acinus has significance in clarifying the predisposing cause, progression, clinical treatment and prevention of common respiratory system diseases such as emphysema. In this study, we established an in vitro experimental model capable of simulating pulmonary acinar morphological lesions, such as emphysema and pulmonary atrophy. In addition, the deposition efficiencies of inhalable particles with various diameters in the pulmonary acinus were investigated under an unsteady state respiratory mode. The changes in pulmonary acinar morphology significantly affected the deposition rates of particles. Moreover, alveolar atrophy increased the deposition rate of particles, while pulmonary alveolar dilatation decreased the deposition rate. The results of this study may provide experimental evidence for the development of a disease course by pulmonary acinus morphologic changes. The established model also provides a feasible in vitro experimental model for studying the deposition pattern of inhalable particles in the pulmonary acinus.

Alexandros Sfakianakis
Anapafseos 5 . Agios Nikolaos
Crete.Greece.72100
2841026182

6948891480

alsfakia@gmail.com