Hemodynamic effects of support modes of LVADs on the aortic valve Abstract As the alternative treatment for heart failure, left ventricular assist devices (LVADs) have been widely applied to clinical practice. However, the effects of the support modes of LVADs on the biomechanical states of the aortic valve are still poorly understood. Hence, the present study investigates such effects and proposes a novel fluid–structure interaction (FSI) approach that combines the lattice Boltzmann method (LBM) and finite element (FE) method. Two support modes of LVADs, namely constant speed mode and constant flow mode, which have been widely applied to clinical practice, are also designed. Results demonstrate that the support modes of LVADs could significantly affect the biomechanical states of the aortic valve and the blood flow pattern of the ascending aorta. Compared with those in the constant flow mode, the leaflets in the constant speed mode could achieve better dynamic performance and lower stress during the systolic phase. The max radial displacement of the leaflets in the constant speed mode is at 8 mm, whereas that in the constant flow mode is at 0.8 mm. Furthermore, the outflow of LVADs directly impacts the aortic surfaces of the leaflets during the diastolic phase by increasing the level of wall shear stress of the leaflets. The leaflets in the constant speed mode receive less impact than those in the constant flow mode. The condition with such minimal impact is conducive to maintaining the normal structure of leaflets and benefits the reduction of the risk of valvular diseases. In sum, the support modes of LVADs exert a crucial effect on the biomechanical environment of the aortic valve. The constant speed mode is better than the constant flow mode in terms of providing a good hemodynamic environment for the aortic valve.

Regularized logistic regression for obstructive sleep apnea screening during wakefulness using daytime tracheal breathing sounds and anthropometric information Abstract Obstructive sleep apnea (OSA) is a prevalent health problem. Developing a technology for quick OSA screening is momentous. In this study, we used regularized logistic regression to predict the OSA severity level of 199 individuals (116 males) with apnea/hypopnea index (AHI) ≥ 15 (moderate/severe OSA) and AHI < 5 (non-OSA) using their tracheal breathing sounds (TBS) recorded during daytime, while they were awake. The participants were guided to breathe through their nose, and then through their mouth at their deep breathing rate. The least absolute shrinkage and selection operator (LASSO) feature selection approach was used to select the discriminative features from the power spectra of the TBS and the anthropometric information. Using a five-fold cross-validation procedure, five different training sets and their corresponding blind-testing sets were formed. The average blind-testing classification accuracy over the five different folds was found to be 79.3% ± 6.1 with the sensitivity (specificity) of 82.2% ± 7.2% (75.8% ± 9.9%). The accuracy for the entire dataset was found to be 81.1% with sensitivity (specificity) of 84.4% (77.0%). The feature selection and classification procedures were intelligible and fast. The selected features were physiologically meaningful. Overall, the results show that TBS analysis can be used as a quick and reliable prediction of the presence and severity of OSA during wakefulness without a sleep study. Graphical abstract Wakefulness screening of obstructive sleep apnea using tracheal breathing sounds and anthropometric information by means of regularized logistic regression with the least absolute shrinkage and selection operator approach for feature selection and classification.

Detection of inflammation from finger temperature profile in rheumatoid arthritis Abstract Rheumatoid arthritis (RA) is a chronic inflammatory tissue disease that leads to cartilage, bone, and periarticular tissue damage. This study aimed to investigate whether the use of infrared thermography and measurement of temperature profiles along the hand fingers could detect the inflammation and improve the diagnostic accuracy of the cold provocation test (0 °C for 5 s) and rewarming test (23 °C for180 s) in RA patients. Thirty RA patients (mean age = 49.5 years, standard deviation = 13.0 years) and 22 controls (mean age = 49.8 years, standard deviation = 7.5 years) were studied. Outcomes were the minimal and maximal: baseline temperature (T1), the temperature post-cooling (T2), the temperature post-rewarming (T3), and the Tmax-Tmin along the axis of each finger. The statistical significance was observed for the thumb, index finger, middle finger, and ring finger post-cooling and post-rewarming. Receiver operating characteristics (ROC) analysis to distinguish between the two groups revealed that for the thumb, index finger, middle finger, and ring finger, the area under the ROC curve was statistically significantly (p < 0.05) post-cooling. The cold provocation test used in this study discriminates between RA patients and controls and detects an inflammation in RA patients by the measurement of temperature profiles along the fingers using an infrared camera. Graphical abstract

Badminton players show a lower coactivation and higher beta band intermuscular interactions of ankle antagonist muscles during isokinetic exercise Abstract Previous studies have suggested that skilled athletes may show a specific muscle activation pattern with a lower antagonist coactivation level. Based on the point, we hypothesize that the coupling of antagonistic muscles may be different between badminton players and non-skilled individuals during exercises. The current work was designed to verify the hypothesis. Ten male college students and eight male badminton players performed three maximal voluntary isometric contractions (MVC) and a set of three maximal concentric ankle dorsiflexion and plantar flexions at an angular velocity of 30°, 60°, 120°, and 180°/s. Surface electromyography (EMG) was recorded from the tibialis anterior (TA) and lateral gastrocnemius (LG) muscles during the test. Normalized average EMG amplitude and phase synchronization index (PSI) between surface EMG of TA and LG were calculated. Antagonist muscle coactivation was significantly lower (from 22.1% ± 9.4 and 10.7% ± 3.7 at 30°/s to 22.4% ± 9.7 and 10.6% ± 2.5 at 180°/s for non-players and badminton players group, respectively), and PSI in beta frequency band was significantly higher (from 0.42 ± 0.06 and 0.47 ± 0.15 at 30°/s to 0.35 ± 0.12 and 0.49 ± 0.14 at 180°/s) in the badminton player group compared with the non-player group during isokinetic ankle dorsiflexion contraction. No significant difference was found in antagonist muscle coactivation and PSI between two group subjects during ankle plantar flexion. The decrease of antagonist coactivation may indicate an optimal motor control style to increase the contraction efficiency, while the increase coupling of antagonistic muscles may help to ensure joint stability to compensate for the decrease of antagonist coactivation. Graphical abstract Significant difference of observed indexes between non-players and badminton players.

Design a prototype for automated patient diagnosis in wireless sensor networks Abstract It is indeed necessary to design of an elderly support mobile healthcare and monitoring system on wireless sensor network (WSN) for dynamic monitoring. It comes from the need for maintenance of healthcare among patients and elderly people that leads to the demand on change in traditional monitoring approaches among chronic disease patients and alert on acute events. In this paper, we propose a new automated patient diagnosis called automated patient diagnosis (AUPA) using ATmega microcontrollers over environmental sensors. AUPA monitors and aggregates data from patients through network connected over web server and mobile network. The scheme supports variable data management and route establishment. Data transfer is established using adaptive route discovery and management approaches. AUPA supports minimizing packet loss and delay, handling erroneous data, and providing optimized decision-making for healthcare support. The performance of AUPA’s QoS approach is tested using a set of health-related sensors which gather the patient’s data over variable period of time and send from a source to destination AUPA node. Experimental results show that AUPA outperforms the existing schemes, namely SPIN and LEACH, with minimal signal loss rate and a better neighborhood node selection and link selection. It diminishes the jitter compared to the related algorithms. Graphical abstract Stack architecture of AUPA

Advanced computing solutions for analysis of laryngeal disorders Abstract Clinical diagnosis of voice pathologies is performed by analyzing audio, color, shape, and vibration patterns of the laryngeal recordings which are taken with medical imaging devices such as video-laryngostroboscope, direct laryngoscopy, and high-speed videoendoscopes. This paper examines state-of-the-art methods and reveals open issues and problems of computing solutions for analysis and identification of laryngeal disorders. We propose a categorical representation of the most significant applications published so far in terms of their scopes, used methodologies, and achieved results. Laryngeal image/video analysis is discussed in four main categories: segmentation of vocal folds, classification of vocal fold disorders, vocal fold vibration analysis, and vocal fold image stitching. By this study, we reveal new opportunities and potentials of vision-based computerized solutions for evaluation, early diagnosis, and prevention of laryngeal disorders. Graphical abstract

Real-time epileptic seizure prediction based on online monitoring of pre-ictal features Abstract Reliable prediction of epileptic seizures is of prime importance as it can drastically change the quality of life for patients. This study aims to propose a real-time low computational approach for the prediction of epileptic seizures and to present an efficient hardware implementation of this approach for portable prediction systems. Three levels of feature extraction are performed to characterize the pre-ictal activities of the EEG signal. In the first-level, the line length algorithm is applied to the pre-ictal region. The features obtained in the first-level are mathematically integrated to extract the second-level features and then the line lengths of the second-level features are calculated to obtain our third-level feature. The third-level information is compared with predefined threshold levels to make a decision on whether the extracted characteristics are relevant to a seizure occurrence or not. The validity of this algorithm was tested by EEG recordings in the CHB-MIT database (97 seizures, 834.224 h) for 19 epileptic patients. The results showed that the average sensitivity was 90.62%, the specificity was 88.34%, the accuracy was 88.76% with the average false prediction rate as low as 0.0046 h−1, and the average prediction time was 23.3 min. The low computational complexity is the superiority of the proposed approach, which provides a technologically simple but accurate way of predicting epileptic seizures and enables hardware implantable devices. Graphical abstract Proposed seizure prediction algorithm and its features

Robust control of heart rate for cycle ergometer exercise Abstract The objective was to assess the performance and robustness of a novel strategy for automatic control of heart rate (HR) during cycle ergometry. Control design used a linear plant model and direct shaping of the closed-loop input-sensitivity function to achieve an appropriate response to disturbances attributable to broad-spectrum heart rate variability (HRV). The controller was evaluated in 73 feedback control experiments involving 49 participants. Performance and stability robustness were analysed using a separately identified family of 73 plant models. The controller gave highly accurate and stable HR tracking performance with mean root-mean-square tracking error between 2.5 beats/min (bpm) and 3.1 bpm, and with low average control signal power. Although plant parameters varied over a very wide range, key closed-loop transfer functions remained invariant to plant uncertainty in important frequency bands, while infinite gain margins and large phase margins (> 62∘) were preserved across the whole plant model family. Highly accurate, stable and robust HR control can be achieved using LTI controllers of remarkably simple structure. The results highlight that HR control design must focus on disturbances caused by HRV. The input-sensitivity approach evaluated in this work provides a transparent method of addressing this challenge. Graphical Abstract Heart rate control using a cycle ergometer

The synergetic effect of pelvic rotation and X-ray offset on radiographic angles of the acetabular cup Abstract The objective of this study is to investigate the synergetic effect of the pelvic rotation and X-ray offset on the radiographic anteversion/inclination (RA/RI) angles of the acetabular cup using a mathematical model. A cone model for establishing the spatial relationship between a three-dimensional (3D) circle and its two-dimensional (2D) elliptical projection is utilized to quantify the relationship between the 3D RA/RI angles of the cup and their 2D counterparts with different types of pelvic rotations in pelvic/hip anteroposterior radiographs. The results reveal that the effect of inlet/outlet views on the 2D RA angle is similar to that of iliac/obturator views. The permissible ranges of pelvic rotation for the 2D RA angle with an acceptable bias are the 3D space formed by the limits of triple axial rotations. For a specified acceptable bias of the 2D RA angle, these ranges are almost equal between pelvic and hip radiographs. The combined inlet/obturator or outlet/iliac views can maintain the 2D RA angle of a pelvic radiograph within the same range of acceptable bias as that of a hip radiograph. For a 2D RA angle with an acceptable bias, the permissible range of pelvic rotation needs to be evaluated with equal attention in both radiographs. Graphical abstract The traditional methods for calculating the radiographic angles of the acetabular cup are based on the ellipse projection of the opening circle of the cup on radiographs. However, with varying locations of the X-ray source and pelvis rotations about different axes, the outline of this ellipse projection will change, and accordingly, the traditional method and calculating results will be inaccurate. In this study, a cone model for three-dimensional circle-to-two-dimensional ellipse projection is utilized to incorporate the effect of X-ray offset and quantify the relationships of the radiographic angles of the cup with the true orientation of the cup and pelvic rotations in either pelvic or hip anteroposterior radiographic situation.

Medical image encryption using fractional discrete cosine transform with chaotic function Abstract In this advanced era, where we have high-speed connectivity, it is very imperative to insulate medical data from forgery and fraud. With the regular increment in the number of internet users, it is challenging to transmit the beefy medical data. This (medical data) is always reused for different diagnosis purposes, so the information of the medical images need to be protected. This paper introduces a new scheme to ensure the safety of the medical data, which includes the use of a chaotic map on the fractional discrete cosine transform (FrDCT) coefficients of the medical data/images. The imperative FrDCT provides a high degree of freedom for the encryption of the medical images. The algorithm consists of two significant steps, i.e., application of FrDCT on an image and after that chaotic map on FrDCT coefficients. The proposed algorithm discusses the benefits of FrDCT over fractional Fourier transform (FRFT) concerning fractional order α. The key sensitivity and space of the proposed algorithm for different medical images inspire us to make a platform for other researchers to work in this area. Experiments are conducted to study different parameters and challenges. The proposed method has been compared with state-of-the-art techniques. The results suggest that our technique outperforms many other state-of-the-art techniques. Graphical Abstract Overview of the proposed algorithm