Manipulating the Cathodic Modification Effect on Corrosion Resistance of High Corrosion-Resistant Titanium Alloy.

Further improving the corrosion resistance of the ASTM Grade 13 (Gr13) titanium alloy was achieved by manipulating the cathodic modification effect. The cathodic modification of Gr13 was mainly related to the Ti2Ni precipitate, where minor Ru was contained and controlled the precipitate in terms of size and distribution, which could manipulate the cathodic modification effect. Parameters such as temperature and cooling rate during the recrystallization process were designed to control precipitation behavior, where the temperature at 850 °C was selected to allow the full dissolution of the Ti2Ni precipitate. The cooling rate, as high as 160.9 °C/min, was still enough for precipitation to occur during the cooling stage, leading to the formation of the Ti2Ni precipitate along with a grain boundary. The cooling rate of water quenching was too fast to cause the diffusion process, resulting in a large amount of the ß-Ti phase without the precipitate, which was pre-formed while heated at 850 °C. Aging at 600 °C caused the re-precipitation of Ti2Ni, and, at that moment, the precipitate was refined and separated, as a good aspect of the catalyst for HER. Therefore, the aged sample after water quenching showed the lowest onset potential for HER with the highest corrosion potential, indicating that its passivation ability was improved by the strengthened cathodic modification effect. This improvement was confirmed by the OCP results, where passivation survival was observed for the aged sample due to the highest cathodic modification effect. Therefore, the aged sample, which had refined and separate precipitates, showed the lowest corrosion rate.

Blood pressure estimation and its recalibration assessment using wrist cuff blood pressure monitor.

The rapid evolution of wearable technology in healthcare sectors has created the opportunity for people to measure their blood pressure (BP) using a smartwatch at any time during their daily activities. Several commercially-available wearable devices have recently been equipped with a BP monitoring feature. However, concerns about recalibration remain. Pulse transit time (PTT)-based estimation is required for initial calibration, followed by periodic recalibration. Recalibration using arm-cuff BP monitors is not practical during everyday activities. In this study, we investigated recalibration using PTT-based BP monitoring aided by a deep neural network (DNN) and validated the performance achieved with more practical wrist-cuff BP monitors. The PTT-based prediction produced a mean absolute error (MAE) of 4.746 ± 1.529 mmHg for systolic blood pressure (SBP) and 3.448 ± 0.608 mmHg for diastolic blood pressure (DBP) when tested with an arm-cuff monitor employing recalibration. Recalibration clearly improved the performance of both DNN and conventional linear regression approaches. We established that the periodic recalibration performed by a wrist-worn BP monitor could be as accurate as that obtained with an arm-worn monitor, confirming the suitability of wrist-worn devices for everyday use. This is the first study to establish the potential of wrist-cuff BP monitors as a means to calibrate BP monitoring devices that can reliably substitute for arm-cuff BP monitors. With the use of wrist-cuff BP monitoring devices, continuous BP estimation, as well as frequent calibrations to ensure accurate BP monitoring, are now feasible.

Effect of Iron Content on Corrosion Properties of Pure Titanium as Grain Refiner.

Microstructures and corrosion properties of pure titanium were characterized when iron was used as a grain refiner. The added Fe element acted as a strong grain refiner for pure titanium by forming ß Ti phase at grain boundaries, and 0.15 wt% Fe was revealed to be a sufficient amount to make the grain size of pure titanium below 20 µm, which was the requirement for the desired titanium cathode. However, corrosion resistance was decreased with the Fe amount added. From the open circuit potential (OCP) results, it was obvious that the TiO2 stability against the reducing acid environment was deteriorated with the Fe amount, which seemed to be the main reason for the decreased corrosion resistance. Electrochemical impedance spectroscopy (EIS) results showed that both the decrease in the compact oxide film's resistance (Rb) and the appearance of the outer porous film occurred as a result of the dissolution of the TiO2 layer, whose phenomena became more apparent as more Fe was added.

Beat-to-Beat Continuous Blood Pressure Estimation Using Bidirectional Long Short-Term Memory Network.

Continuous blood pressure (BP) monitoring is important for patients with hypertension. However, BP measurement with a cuff may be cumbersome for the patient. To overcome this limitation, various studies have suggested cuffless BP estimation models using deep learning algorithms. A generalized model should be considered to decrease the training time, and the model reproducibility should be taken into account in multi-day scenarios. In this study, a BP estimation model with a bidirectional long short-term memory network is proposed. The features are extracted from the electrocardiogram, photoplethysmogram, and ballistocardiogram. The leave-one-subject-out (LOSO) method is incorporated to generalize the model and fine-tuning is applied. The model was evaluated using one-day and multi-day tests. The proposed model achieved a mean absolute error (MAE) of 2.56 and 2.05 mmHg for the systolic and diastolic BP (SBP and DBP), respectively, in the one-day test. Moreover, the results demonstrated that the LOSO method with fine-tuning was more compatible in the multi-day test. The MAE values of the model were 5.82 and 5.24 mmHg for the SBP and DBP, respectively.

Incidence of intussusception before and after the introduction of rotavirus vaccine in Korea.

BACKGROUND: Recent studies have reported that after the introduction of rotavirus vaccine the incidence of intussusception did not change among infants, or slightly increased at the age immediately after the first dose. The rotavirus vaccines were introduced in Korea for private market use in 2007-2008. We investigated the incidence of intussusception before (2002-2006) and after (2009-2015) the vaccine introduction in Korea. METHODS: We conducted an interrupted time series study that used data from the Korean National Health Insurance database to identify infants (<12 months of age) who were diagnosed with intussusception and underwent non-invasive or invasive reduction from 2002 to 2015. According to the recommended ages for immunization, the annual intussusception incidence and the incidence rate ratios were calculated among three age groups, 6-14, 15-24, and 25-34 weeks. RESULTS: The annual incidences in infants have decreased over time from 241.7 per 100,000 infants (pre-vaccine period) to 160.1-205.2 per 100,000 infants (post-vaccine period). The incidence rate ratio during the post-vaccine period ranged from 0.66 to 0.85. The incidences of intussusception in all three infant age groups have decreased in post-vaccine period compared to pre-vaccine period (incidence rate ratio range: 0.31-0.65, 0.47-0.75, and 0.68-0.94 in 6-14, 15-24, and 25-34 weeks, respectively). CONCLUSIONS: The incidence of intussusception in infants did not increase after the rotavirus vaccine introduction in Korea, but rather decreased over the past decades. Since the incidence of intussusception varies according to country or region, continuous monitoring the incidence of intussusception in infants is necessary in each county or region.

End-to-End Deep Learning Architecture for Continuous Blood Pressure Estimation Using Attention Mechanism.

Blood pressure (BP) is a vital sign that provides fundamental health information regarding patients. Continuous BP monitoring is important for patients with hypertension. Various studies have proposed cuff-less BP monitoring methods using pulse transit time. We propose an end-to-end deep learning architecture using only raw signals without the process of extracting features to improve the BP estimation performance using the attention mechanism. The proposed model consisted of a convolutional neural network, a bidirectional gated recurrent unit, and an attention mechanism. The model was trained by a calibration-based method, using the data of each subject. The performance of the model was compared to the model that used each combination of the three signals, and the model with the attention mechanism showed better performance than other state-of-the-art methods, including conventional linear regression method using pulse transit time (PTT). A total of 15 subjects were recruited, and electrocardiogram, ballistocardiogram, and photoplethysmogram levels were measured. The 95% confidence interval of the reference BP was [86.34, 143.74] and [51.28, 88.74] for systolic BP (SBP) and diastolic BP (DBP), respectively. The R 2 values were 0.52 and 0.49, and the mean-absolute-error values were 4.06 ± 4.04 and 3.33 ± 3.42 for SBP and DBP, respectively. In addition, the results complied with global standards. The results show the applicability of the proposed model as an analytical metric for BP estimation.

Optimal Lead Position in Patch-Type Monitoring Sensors for Reconstructing 12-Lead ECG Signals with Universal Transformation Coefficient.

The aim of this study was to reconstruct a 12-lead electrocardiograph (ECG) with a universal transformation coefficient and find the appropriate electrode position and shape for designing a patch-type ECG sensor. A 35-channel ECG monitoring system was developed, and 14 subjects were recruited for the experiment. A feedforward neural network with one hidden layer was applied to train the transformation coefficient. Three electrode shapes (5 cm × 5 cm square, 10 cm × 10 cm square, and right-angled triangle) were considered for the patch-type ECG sensor. The mean correlation coefficient (CC) and minimum CC methods were applied to evaluate the reconstruction performance. The average CCs between the standard 12-lead ECG and reconstructed 12-lead ECG were 0.860, 0.893, and 0.893 for a 5 cm × 5 cm square, 10 cm × 10 cm square, and right-angled triangle shape. The right-angled triangle showed the highest performance among the considered shapes. The results also suggested that the bottom of the central area of the chest was the most suitable position for attaching the patch-type ECG sensor.

An Instant Donning Multi-Channel EEG Headset (with Comb-Shaped Dry Electrodes) and BCI Applications.

We developed a new type of electroencephalogram (EEG) headset system with comb-shaped electrodes that enables the wearer to quickly don and utilize it in daily life. Two models that can measure EEG signals using up to eight channels have been implemented. The electrodes implemented in the headsets are similar to a comb and are placed quickly by wiping the hair (as done with a comb) using the headset. To verify this headset system, donning time was measured and three brain computer interface (BCI) application experiments were conducted. Alpha rhythm-based, steady-state visual evoked potential (SSVEP)-based, and auditory steady state response (ASSR)-based BCI systems were adopted for the validation experiments. Four subjects participated and ten trials were repeated in the donning experiment. The results of the validation experiments show that reliable EEG signal measurement is possible immediately after donning the headsets without any preparation. It took approximately 10 s for healthy subjects to don the headsets, including an earclip with reference and ground electrodes. The results of alpha rhythm-based BCI showed 100% accuracy. Furthermore, the results of SSVEP-based and ASSR-based BCI experiments indicate that performance is sufficient for BCI applications; 95.7% and 76.0% accuracies were obtained, respectively. The results of BCI paradigm experiments indicate that the new headset type is feasible for various BCI applications.

Effects of Intermetallic Compound Formation in Al/Cu Clad Material Fabricated by Differential Speed Rolling.

In this study, the microstructure and mechanical property of Al/Cu clad material fabricated by differential speed rolling at room temperature were evaluated. Al and Cu plates were prepared and mechanically cladded at a differential speed ratio of 2:1 between the upper and lower rolls. Post- heat-treatment was carried out after the mechanical cladding at 400 °C for 60 min to induce the formation of intermetallic compound layers at the bonded interface of Al/Cu. As a result, differential speed rolling afforded a soundly cladded interface without any defects such as voids and cracks. In addition, intermetallic compound layers such as Al4Cu9 and Al2Cu were formed at the mechanically bonded interface during post-heat-treatment for 60 min, which led to an increase in Vickers microhardness value more than 30% relative to the base material. Therefore, we systematically explained the relationship between formation of intermetallic compounds and mechanical property of Al/Cu clad materials in this study.

Effect of Intermetallic Compound Formation in Friction Welded Al Alloy Rods.

This study was carried out to evaluate the development of microstructures and mechanical properties on friction welded dissimilar materials with a light weight. For this work, Al6063 and Duralumin alloys with a shape of rod were selected as experimental materials, and friction welding was performed under conditions with a rotation speed of 2,000 RPM, a friction load of 12 kgf/cm2 and an upset force of 25 kgf/cm2, respectively. After welding, the microstructural analysis such as the grain boundary characteristic distributions and the formation of intermetallic compounds was analyzed by electron back-scattering diffraction method and transmission electron microscopy, respectively. In addition, the evaluation of mechanical properties on welded materials was conducted by Vickers microhardness and tensile test. As a result, applying the friction welding led to the significant grain refinement from 50 µm in base material to 2 µm in welded zone, respectively. In case of mechanical properties, Vickers micro-hardness and tensile strength of the welded material occupied 81% and 96% in fraction relative to the base material, respectively, which was attributable to the formation and growth of intermetallic compounds during the welding.

Sinabro: A Smartphone-Integrated Opportunistic Electrocardiogram Monitoring System.

In our preliminary study, we proposed a smartphone-integrated, unobtrusive electrocardiogram (ECG) monitoring system, Sinabro, which monitors a user's ECG opportunistically during daily smartphone use without explicit user intervention. The proposed system also monitors ECG-derived features, such as heart rate (HR) and heart rate variability (HRV), to support the pervasive healthcare apps for smartphones based on the user's high-level contexts, such as stress and affective state levels. In this study, we have extended the Sinabro system by: (1) upgrading the sensor device; (2) improving the feature extraction process; and (3) evaluating extensions of the system. We evaluated these extensions with a good set of algorithm parameters that were suggested based on empirical analyses. The results showed that the system could capture ECG reliably and extract highly accurate ECG-derived features with a reasonable rate of data drop during the user's daily smartphone use.

ROI analysis for remote photoplethysmography on facial video.

As wide spreading of camera-equipped devices to the daily living environment, there are enormous opportunities to utilize the camera-based remote photoplethysmography (PPG) for daily physiological monitoring. In the camera-based remote PPG (rPPG) monitoring, the region of interest (ROI) is related to the signal quality and the computational load for the signal extraction processing. Designating the best ROI on the body while minimizing its size is essential for computationally efficient rPPG extraction. In this study, we densely analyzed the face region to find the computationally efficient ROI for facial rPPG extraction. We divided the face into seven regions and evaluated the quality of the signal of each region using the area ratio of high-SNR and high-correlation, and mean and standard deviation (SD) of SNR and correlation coefficient. The results show that a forehead and both cheeks especially have a potential to be a good candidates for computationally efficient ROI. On the other hand, the signal quality from a mouth and a chin was relatively low. A nasion and a nose have a limitation to be efficient ROI.

Estimation of sleep posture using a patch-type accelerometer based device.

In this study, we developed a sleep posture estimation algorithm using 3-axis accelerometer signals measured from a patch-type sensor. Firstly, we inspected the characteristics of accelerometer signals for different sleep postures. Based on the results, we established decision rules to estimate 5 postures containing supine, left, right lateral, prone postures, and non-sleep postures such as sitting and standing. The algorithm was tested by the data from thirteen subjects during night time PSG. As a result, the algorithm estimated sleep postures with an average agreement of 99.16%, and cohen's kappa of 0.98 compared with reference sleep postures determined by position sensor and video recording. The proposed method with the device could be used as supportive purpose in routine PSG study and out-of-hospital environment.

Ballistocardiography and seismocardiography: a review of recent advances.

In the past decade, there has been a resurgence in the field of unobtrusive cardiomechanical assessment, through advancing methods for measuring and interpreting ballistocardiogram (BCG) and seismocardiogram (SCG) signals. Novel instrumentation solutions have enabled BCG and SCG measurement outside of clinical settings, in the home, in the field, and even in microgravity. Customized signal processing algorithms have led to reduced measurement noise, clinically relevant feature extraction, and signal modeling. Finally, human subjects physiology studies have been conducted using these novel instruments and signal processing tools with promising results. This paper reviews the recent advances in these areas of modern BCG and SCG research.

Gender and measuring-position differences in the radial pulse of healthy individuals.

In this research, radial pulse differences according to gender and measuring positions in healthy individuals were investigated in an objective manner. A total of 372 healthy volunteers (189 males and 183 females) participated in this study. The radial pulse was measured at six different measuring positions using a multistep tonometry system. The pulse data were compared between males and females and between different measuring positions. Compared to the pulses in females, those in males were deeper and slower, with a longer diastolic proportion and a shorter systolic proportion. Amplitude of the radial pulse increased as it went distal. The pulse was deepest at the Cheock position and shallowest at the Gwan position. Compared to the right pulse, the radial augmentation index was higher and the main peak angle was larger in case of the left pulse. The results of this research show that the radial pulses in healthy individuals differ significantly according to gender and measuring positions.

CardioGuard: a brassiere-based reliable ECG monitoring sensor system for supporting daily smartphone healthcare applications.

We propose CardioGuard, a brassiere-based reliable electrocardiogram (ECG) monitoring sensor system, for supporting daily smartphone healthcare applications. It is designed to satisfy two key requirements for user-unobtrusive daily ECG monitoring: reliability of ECG sensing and usability of the sensor. The system is validated through extensive evaluations. The evaluation results showed that the CardioGuard sensor reliably measure the ECG during 12 representative daily activities including diverse movement levels; 89.53% of QRS peaks were detected on average. The questionnaire-based user study with 15 participants showed that the CardioGuard sensor was comfortable and unobtrusive. Additionally, the signal-to-noise ratio test and the washing durability test were conducted to show the high-quality sensing of the proposed sensor and its physical durability in practical use, respectively.

Highly wearable galvanic skin response sensor using flexible and conductive polymer foam.

Owing to advancements in daily physiological monitoring technology, diverse healthcare applications have emerged recently. The monitoring of skin conductance responses has extensive feasibility to support healthcare applications such as detecting emotion changes. In this study, we proposed a highly wearable and reliable galvanic skin response (GSR) sensor that measures the signals from the back of the user. To enhance its wearability and usability, we employed flexible conductive foam as the sensing material and designed it to be easily attachable to (and detachable from) a wide variety of clothes. We evaluated the sensing reliability of the proposed sensor by comparing its signal with a reference GSR. The average correlation between the two signals was 0.768; this is sufficiently high to validate the feasibility of the proposed sensor for reliable GSR sensing on the back.

Unobtrusive monitoring of ECG-derived features during daily smartphone use.

Heart rate variability (HRV) is known to be one of the representative ECG-derived features that are useful for diverse pervasive healthcare applications. The advancement in daily physiological monitoring technology is enabling monitoring of HRV in people's everyday lives. In this study, we evaluate the feasibility of measuring ECG-derived features such as HRV, only using the smartphone-integrated ECG sensors system named Sinabro. We conducted the evaluation with 13 subjects in five predetermined smartphone use cases. The result shows the potential that the smartphone-based sensing system can support daily monitoring of ECG-derived features; The average errors of HRV over all participants ranged from 1.65% to 5.83% (SD: 2.54~10.87) for five use cases. Also, all of individual HRV parameters showed less than 5% of average errors for the three reliable cases.