Publications by authors named "Hee Chan Kim"

186 Publications

EEG-Based Prediction of the Recovery of Carotid Blood Flow during Cardiopulmonary Resuscitation in a Swine Model.

Sensors (Basel) 2021 May 24;21(11). Epub 2021 May 24.

Department of Biomedical Engineering, Seoul National University College of Medicine, Seoul 03080, Korea.

The recovery of cerebral circulation during cardiopulmonary resuscitation (CPR) is important to improve the neurologic outcomes of cardiac arrest patients. To evaluate the feasibility of an electroencephalogram (EEG)-based prediction model as a CPR feedback indicator of high- or low-CBF carotid blood flow (CBF), the frontal EEG and hemodynamic data including CBF were measured during animal experiments with a ventricular fibrillation (VF) swine model. The most significant 10 EEG parameters in the time, frequency and entropy domains were determined by neighborhood component analysis and Student's -test for discriminating high- or low-CBF recovery with a division criterion of 30%. As a binary CBF classifier, the performances of logistic regression, support vector machine (SVM), k-nearest neighbor, random forest and multilayer perceptron algorithms were compared with eight-fold cross-validation. The three-order polynomial kernel-based SVM model showed the best accuracy of 0.853. The sensitivity, specificity, F1 score and area under the curve of the SVM model were 0.807, 0.906, 0.853 and 0.909, respectively. An automated CBF classifier derived from non-invasive EEG is feasible as a potential indicator of the CBF recovery during CPR in a VF swine model.
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http://dx.doi.org/10.3390/s21113650DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8197348PMC
May 2021

Ultrasonic blood flowmeter with a novel Xero algorithm for a mechanical circulatory support system.

Ultrasonics 2021 Aug 2;115:106457. Epub 2021 May 2.

Department of Information and Communication Engineering, Daegu Gyeongbuk Institute of Science & Technology, Daegu, Republic of Korea. Electronic address:

Mechanical circulatory support systems (MCSSs) are crucial devices for transplants in patients with heart failure. The blood flowing through the MCSS can be recirculated or even stagnated in the event of critical blood flow issues. To avoid emergencies due to abnormal changes in the flow, continuous changes of the flowrate should be measured with high accuracy and robustness. For better flowrate measurements, a more advanced ultrasonic blood flowmeter (UFM), which is a noninvasive measurement tool, is needed. In this paper, we propose a novel UFM sensor module using a novel algorithm (Xero) that can exploit the advantages of both conventional cross-correlation (Xcorr) and zero-crossing (Zero) algorithms, using only the zero-crossing-based algorithm. To ensure the capability of our own developed and optimized ultrasonic sensor module for MCSSs, the accuracy, robustness, and continuous monitoring performance of the proposed algorithm were compared to those of conventional algorithms after application to the developed sensor module. The results show that Xero is superior to other algorithms for flowrate measurements under different environments and offers an error rate of at least 0.92%, higher robustness for changing fluid temperatures than conventional algorithms, and sensitive responses to sudden changes in flowrates. Thus, the proposed UFM system with Xero has a great potential for flowrate measurements in MCSSs.
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http://dx.doi.org/10.1016/j.ultras.2021.106457DOI Listing
August 2021

Suture tie-down forces and cyclic contractile forces after an undersized tricuspid annuloplasty using a 3-dimensional rigid ring in an ovine model.

Eur J Cardiothorac Surg 2021 Mar 31. Epub 2021 Mar 31.

Department of Thoracic and Cardiovascular Surgery, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, Korea.

Objectives: This study was conducted to measure suture tie-down forces and evaluate cyclic contractile forces (CCFs) in beating hearts after undersized 3-dimensional (3D) rigid-ring tricuspid valve annuloplasty (TAP).

Methods: Eight force transducers were attached to the 3D rigid TAP ring. Segments 1 to 8 were attached from the mid-septal to anterior-septal commissural area in a counterclockwise order. Two-sizes-down ring TAPs were performed in 6 sheep. Tie-down forces and CCF were recorded and analysed at the 8 annular segments and at 3 levels of peak right ventricular pressure (RVP: 30, 50 and 70 mmHg).

Results: The overall average tie-down forces and CCF were 4.34 ± 2.26 newtons (N) and 0.23 ± 0.09 N, respectively. The CCF at an RVP of 30 mmHg were higher at 3 commissural areas (segments 3, 5 and 8) than at the other segments. The increases in the CCF following changes in the RVP were statistically significant only at the 3 commissural areas (P = 0.012). However, mean CCFs remained low at all annular positions (ranges of average CCF = 0.06-0.46 N).

Conclusions: The risk of suture dehiscence after down-sized 3D rigid-ring TAP might be minimal because the absolute forces remained low in all annular positions even in the condition of high RVP. However, careful suturing in the septal annular area and commissures is necessary to prevent an annular tear during a down-sized 3D rigid-ring TAP.
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http://dx.doi.org/10.1093/ejcts/ezab131DOI Listing
March 2021

Prediction of cerebral perfusion pressure during CPR using electroencephalogram in a swine model of ventricular fibrillation.

Am J Emerg Med 2021 Feb 25;45:137-143. Epub 2021 Feb 25.

Laboratory of Emergency Medical Services, Biomedical Research Institute, Seoul National University Hospital, Seoul, Republic of Korea.

Background: Measuring the quality of cardiopulmonary resuscitation (CPR) is important for improving outcomes in cardiac arrest. Cerebral perfusion pressure (CePP) could represent cerebral circulation during CPR, but it is difficult to measure non-invasively. In this study, we developed the electroencephalogram (EEG) based brain index (EBRI) derived from EEG signals by machine learning techniques, which could estimate CePP accurately in a porcine cardiac arrest model.

Methods: We conducted a randomised crossover study using nine female pigs. After 1 min of untreated ventricular fibrillation, we performed CPR with 12 different 2-min tilting angle sessions, including two different head-up tilt (HUT) angles (30°, 15°) twice, horizontal angle (0°) four times and two different head-down tilt (HDT) angles (-15°, -30°) twice with the random order. We collected EEG signals using a single channel EEG electrode in real-time during CPR. We derived the EBRI models to predict the CePP classified by the 5 or 10 groups using three different machine learning algorithms, including the support vector machine (SVM), k-nearest neighbour (KNN) and random forest classification (RFC) method. We assessed the accuracy, sensitivity and specificity of each model.

Results: The accuracy of the EBRI model using an SVM algorithm in the 5-group CePP classification was 0.935 with a standard deviation (SD) from 0.923 to 0.946. The accuracy in the 10-group classification was 0.904 (SD: 0.896, 0.913). The accuracy of the EBRI using the KNN method in the 5-group classification was 0.927 (SD: 0.920, 0933) and in the 10-group was 0.894 (SD: 0.880, 0.907). The accuracy of the RFC algorithm was 0.947 (SD: 0.931, 0.963) in the 5-group classification and 0.920 (SD: 0.911, 0.929) in the 10-group classification.

Conclusion: We developed the EBRI model using non-invasive acquisition of EEG signals to predict CePP during CPR. The accuracy the EBRI model was 0.935, 0.927 and 0.947 for each machine learning algorithm, and the EBRI could be used as a surrogate indicator for measuring cerebral perfusion during CPR.
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http://dx.doi.org/10.1016/j.ajem.2021.02.051DOI Listing
February 2021

Quantitative assessment of self-treated canalith repositioning procedures using inertial measurement unit sensors.

J Vestib Res 2021 Feb 20. Epub 2021 Feb 20.

Institute of Medical & Biological Engineering, Medical Research Center, Seoul National University, Seoul, Korea.

Background: Low success and high recurrence of benign paroxysmal positional vertigo (BPPV) after home-based self-treated Epley and Barbeque (BBQ) roll maneuvers is an important issue.

Objective: To quantify the cause of low success rate of self-treated Epley and BBQ roll maneuvers and provide a clinically acceptable criterion to guide self-treatment head rotations.

Methods: Twenty-five participants without active BPPV wore a custom head-mount rotation monitoring device for objective measurements. Self-treatment and specialist-assisted maneuvers were compared for head rotation accuracy. Absolute differences between the head rotation evaluation criteria (American Academy of Otolaryngology guidelines) and measured rotation angles were considered as errors. Self-treatment and specialist-treated errors in maneuvers were compared. Between-trial variations and age effects were evaluated.

Results: A significantly large error and between-trial variation occurred in step 4 of the self-treated Epley maneuver, with a considerable error in the second trial. The cumulative error of all steps of self-treated BBQ roll maneuver was significantly large. Age effect occurred only in the self-treated BBQ roll maneuver. Errors in specialist-treated maneuvers ranged from 10 to 20 degrees.

Conclusions: Real-time feedback of head movements during simultaneous head-body rotations could increase success rates of self-treatments. Specialist-treated maneuvers can be used as permissible rotation margin criteria.
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http://dx.doi.org/10.3233/VES-190747DOI Listing
February 2021

Point-of-care testing of plasma free hemoglobin and hematocrit for mechanical circulatory support.

Sci Rep 2021 Feb 15;11(1):3788. Epub 2021 Feb 15.

Department of Biomedical Engineering, College of Medicine and Institute of Medical and Biological Engineering, Medical Research Center, Seoul National University, Seoul, 03080, Republic of Korea.

Hematological analysis is essential for patients who are supported by a mechanical circulatory support (MCS). The laboratory methods used to analyze blood components are conventional and accurate, but they require a mandatory turn-around-time for laboratory results, and because of toxic substances, can also be hazardous to analysis workers. Here, a simple and rapid point-of-care device is developed for the measurement of plasma free hemoglobin (PFHb) and hematocrit (Hct), based on colorimetry. The device consists of camera module, minimized centrifuge system, and the custom software that includes the motor control algorithm for the centrifuge system, and the image processing algorithm for measuring the color components of blood from the images. We show that our device measured PFHb with a detection limit of 0.75 mg/dL in the range of (0-100) mg/dL, and Hct with a detection limit of 2.14% in the range of (20-50)%. Our device had a high correlation with the measurement method generally used in clinical laboratories (PFHb R = 0.999, Hct R = 0.739), and the quantitative analysis resulted in precision of 1.44 mg/dL for PFHb value of 14.5 mg/dL, 1.36 mg/dL for PFHb value of 53 mg/dL, and 1.24% for Hct 30%. Also, the device can be measured without any pre-processing when compared to the clinical laboratory method, so results can be obtained within 5 min (about an 1 h for the clinical laboratory method). Therefore, we conclude that the device can be used for point-of-care measurement of PFHb and Hct for MCS.
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http://dx.doi.org/10.1038/s41598-021-83327-5DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7884396PMC
February 2021

Clinical outcome prediction from analysis of microelectrode recordings using deep learning in subthalamic deep brain stimulation for Parkinson`s disease.

PLoS One 2021 26;16(1):e0244133. Epub 2021 Jan 26.

Department of Neurosurgery, Seoul National University Hospital, Seoul, Korea.

Background: Deep brain stimulation (DBS) of the subthalamic nucleus (STN) is an effective treatment for improving the motor symptoms of advanced Parkinson's disease (PD). Accurate positioning of the stimulation electrodes is necessary for better clinical outcomes.

Objective: We applied deep learning techniques to microelectrode recording (MER) signals to better predict motor function improvement, represented by the UPDRS part III scores, after bilateral STN DBS in patients with advanced PD. If we find the optimal stimulation point with MER by deep learning, we can improve the clinical outcome of STN DBS even under restrictions such as general anesthesia or non-cooperation of the patients.

Methods: In total, 696 4-second left-side MER segments from 34 patients with advanced PD who underwent bilateral STN DBS surgery under general anesthesia were included. We transformed the original signal into three wavelets of 1-50 Hz, 50-500 Hz, and 500-5,000 Hz. The wavelet-transformed MER was used for input data of the deep learning. The patients were divided into two groups, good response and moderate response groups, according to DBS on to off ratio of UPDRS part III score for the off-medication state, 6 months postoperatively. The ratio were used for output data in deep learning. The Visual Geometry Group (VGG)-16 model with a multitask learning algorithm was used to estimate the bilateral effect of DBS. Different ratios of the loss function in the task-specific layer were applied considering that DBS affects both sides differently.

Results: When we divided the MER signals according to the frequency, the maximal accuracy was higher in the 50-500 Hz group than in the 1-50 Hz and 500-5,000 Hz groups. In addition, when the multitask learning method was applied, the stability of the model was improved in comparison with single task learning. The maximal accuracy (80.21%) occurred when the right-to-left loss ratio was 5:1 or 6:1. The area under the curve (AUC) was 0.88 in the receiver operating characteristic (ROC) curve.

Conclusion: Clinical improvements in PD patients who underwent bilateral STN DBS could be predicted based on a multitask deep learning-based MER analysis.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0244133PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7837468PMC
April 2021

Comparative study of glenoid version and inclination using two-dimensional images from computed tomography and three-dimensional reconstructed bone models.

Clin Shoulder Elb 2020 Sep 1;23(3):119-124. Epub 2020 Sep 1.

Department of Orthopedic Surgery, School of Medicine, Catholic University of Daegu, Daegu, Korea.

Background: This study was performed to compare glenoid version and inclination measured using two-dimensional (2D) images from computed tomography (CT) scans or three-dimensional (3D) reconstructed bone models.

Methods: Thirty patients who had undergone conventional CT scans were included. Two orthopedic surgeons measured glenoid version and inclination three times on 2D images from CT scans (2D measurement), and two other orthopedic surgeons performed the same measurements using 3D reconstructed bone models (3D measurement). The 3D-reconstructed bone models were acquired and measured with Mimics and 3-Matics (Materialise).

Results: Mean glenoid version and inclination in 2D measurements were -1.705º and 9.08º, respectively, while those in 3D measurements were 2.635º and 7.23º. The intra-observer reliability in 2D measurements was 0.605 and 0.698, respectively, while that in 3D measurements was 0.883 and 0.892. The inter-observer reliability in 2D measurements was 0.456 and 0.374, respectively, while that in 3D measurements was 0.853 and 0.845.

Conclusions: The difference between 2D and 3D measurements is not due to differences in image data but to the use of different tools. However, more consistent results were obtained in 3D measurement. Therefore, 3D measurement can be a good alternative for measuring glenoid version and inclination.
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http://dx.doi.org/10.5397/cise.2020.00220DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7714290PMC
September 2020

Effect of age on the gap-prepulse inhibition of the cortical N1-P2 complex in humans as a step towards an objective measure of tinnitus.

PLoS One 2020 5;15(11):e0241136. Epub 2020 Nov 5.

Department of Otorhinolaryngology- Head and Neck Surgery, Seoul National University Hospital, Seoul, Korea.

The gap-prepulse inhibition of the acoustic startle reflex has been widely used as a behavioral method for tinnitus screening in animal studies. The cortical-evoked potential gap-induced inhibition has also been investigated in animals as well as in human subjects. The present study aimed to investigate the effect of age on the cortical N1-P2 complex in the gap-prepulse inhibition paradigm. Fifty-seven subjects, aged 20 to 68 years, without continuous tinnitus, were tested with two effective gap conditions (embedded gap of 50- or 20-ms duration). Retest sessions were performed within one month. A significant gap-induced inhibition of the N1-P2 complex was found in both gap durations. Age differently affected the inhibition, depending on gap duration. With a 50-ms gap, the inhibition decreased significantly with the increase in age. This age-inhibition relationship was not found when using a 20-ms gap. The results were reproducible in the retest session. Our findings suggest that the interaction between age and gap duration should be considered when applying the gap-induced inhibition of the cortical-evoked potential as an objective measure of tinnitus in human subjects. Further studies with tinnitus patients are warranted to identify gap duration that would minimize the effects of age and maximize the difference in the inhibition between those with and without tinnitus.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0241136PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7644010PMC
December 2020

Deep-learning-based enhanced optic-disc photography.

PLoS One 2020 1;15(10):e0239913. Epub 2020 Oct 1.

Department of Ophthalmology, Seoul National University College of Medicine, Seoul, Korea.

Optic-disc photography (ODP) has proven to be very useful for optic nerve evaluation in glaucoma. In real clinical practice, however, limited patient cooperation, small pupils, or media opacities can limit the performance of ODP. The purpose of this study was to propose a deep-learning approach for increased resolution and improved legibility of ODP by contrast, color, and brightness compensation. Each high-resolution original ODP was transformed into two counterparts: (1) down-scaled 'low-resolution ODPs', and (2) 'compensated high-resolution ODPs' produced via enhancement of the visibility of the optic disc margin and surrounding retinal vessels using a customized image post-processing algorithm. Then, the differences between these two counterparts were directly learned through a super-resolution generative adversarial network (SR-GAN). Finally, by inputting the high-resolution ODPs into SR-GAN, 4-times-up-scaled and overall-color-and-brightness-transformed 'enhanced ODPs' could be obtained. General ophthalmologists were instructed (1) to assess each ODP's image quality, and (2) to note any abnormal findings, at 1-month intervals. The image quality score for the enhanced ODPs was significantly higher than that for the original ODP, and the overall optic disc hemorrhage (DH)-detection accuracy was significantly higher with the enhanced ODPs. We expect that this novel deep-learning approach will be applied to various types of ophthalmic images.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0239913PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7529226PMC
November 2020

A machine learning-based diagnostic model associated with knee osteoarthritis severity.

Sci Rep 2020 09 25;10(1):15743. Epub 2020 Sep 25.

Department of Orthopedic Surgery, Seoul National University Hospital, Seoul National University College of Medicine, 101 Daehak-ro, Jongno-gu, Seoul, 110-744, Korea.

Knee osteoarthritis (KOA) is characterized by pain and decreased gait function. We aimed to find KOA-related gait features based on patient reported outcome measures (PROMs) and develop regression models using machine learning algorithms to estimate KOA severity. The study included 375 volunteers with variable KOA grades. The severity of KOA was determined using the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC). WOMAC scores were used to classify disease severity into three groups. A total of 1087 features were extracted from the gait data. An ANOVA and student's t-test were performed and only features that were significant were selected for inclusion in the machine learning algorithm. Three WOMAC subscales (physical function, pain and stiffness) were further divided into three classes. An ANOVA was performed to determine which selected features were significantly related to the subscales. Both linear regression models and a random forest regression was used to estimate patient the WOMAC scores. Forty-three features were selected based on ANOVA and student's t-test results. The following number of features were selected from each joint: 12 from hip, 1 feature from pelvic, 17 features from knee, 9 features from ankle, 1 feature from foot, and 3 features from spatiotemporal parameters. A significance level of < 0.0001 and < 0.00003 was set for the ANOVA and t-test, respectively. The physical function, pain, and stiffness subscales were related to 41, 10, and 16 features, respectively. Linear regression models showed a correlation of 0.723 and the machine learning algorithm showed a correlation of 0.741. The severity of KOA was predicted by gait analysis features, which were incorporated to develop an objective estimation model for KOA severity. The identified features may serve as a tool to guide rehabilitation and progress assessments. In addition, the estimation model presented here suggests an approach for clinical application of gait analysis data for KOA evaluation.
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http://dx.doi.org/10.1038/s41598-020-72941-4DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7519044PMC
September 2020

Dual-input convolutional neural network for glaucoma diagnosis using spectral-domain optical coherence tomography.

Br J Ophthalmol 2020 Sep 12. Epub 2020 Sep 12.

Department of Ophthalmology, Seoul National University College of Medicine, Seoul, South Korea.

Background/aims: To evaluate, with spectral-domain optical coherence tomography (SD-OCT), the glaucoma-diagnostic ability of a deep-learning classifier.

Methods: A total of 777 Cirrus high-definition SD-OCT image sets of the retinal nerve fibre layer (RNFL) and ganglion cell-inner plexiform layer (GCIPL) of 315 normal subjects, 219 patients with early-stage primary open-angle glaucoma (POAG) and 243 patients with moderate-to-severe-stage POAG were aggregated. The image sets were divided into a training data set (252 normal, 174 early POAG and 195 moderate-to-severe POAG) and a test data set (63 normal, 45 early POAG and 48 moderate-to-severe POAG). The visual geometry group (VGG16)-based dual-input convolutional neural network (DICNN) was adopted for the glaucoma diagnoses. Unlike other networks, the DICNN structure takes two images (both RNFL and GCIPL) as inputs. The glaucoma-diagnostic ability was computed according to both accuracy and area under the receiver operating characteristic curve (AUC).

Results: For the test data set, DICNN could distinguish between patients with glaucoma and normal subjects accurately (accuracy=92.793%, AUC=0.957 (95% CI 0.943 to 0.966), sensitivity=0.896 (95% CI 0.896 to 0.917), specificity=0.952 (95% CI 0.921 to 0.952)). For distinguishing between patients with early-stage glaucoma and normal subjects, DICNN's diagnostic ability (accuracy=85.185%, AUC=0.869 (95% CI 0.825 to 0.879), sensitivity=0.921 (95% CI 0.813 to 0.905), specificity=0.756 (95% CI 0.610 to 0.790)]) was higher than convolutional neural network algorithms that trained with RNFL or GCIPL separately.

Conclusion: The deep-learning algorithm using SD-OCT can distinguish normal subjects not only from established patients with glaucoma but also from patients with early-stage glaucoma. The deep-learning model with DICNN, as trained by both RNFL and GCIPL thickness map data, showed a high diagnostic ability for discriminatingpatients with early-stage glaucoma from normal subjects.
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http://dx.doi.org/10.1136/bjophthalmol-2020-316274DOI Listing
September 2020

Estimation and Validation of Arterial Blood Pressure Using Photoplethysmogram Morphology Features in Conjunction With Pulse Arrival Time in Large Open Databases.

IEEE J Biomed Health Inform 2021 Apr 6;25(4):1018-1030. Epub 2021 Apr 6.

Although various predictors and methods for BP estimation have been proposed, differences in study designs have led to difficulties in determining the optimal method. This study presents analyses of BP estimation methods using 2.4 million cardiac cycles of two commonly used non-invasive biosignals, electrocardiogram (ECG) and photoplethysmogram (PPG), from 1376 surgical patients. Feature selection methods were used to determine the best subset of predictors from a total of 42 including PAT, heart rate (HR), and various PPG morphology features, and BP estimation models constructed using linear regression (LR), random forest (RF), artificial neural network (ANN), and recurrent neural network (RNN) were evaluated. 28 features out of 42 were determined as suitable for BP estimation, in particular two PPG morphology features outperformed PAT, which has been conventionally seen as the best non-invasive indicator of BP. By modelling the low frequency component of BP using ANN and the high frequency component using RNN with the selected predictors, mean errors of 0.05 ± 6.92 mmHg for systolic BP, and -0.05 ± 3.99 mmHg for diastolic BP were achieved. External validation of the model using another biosignal database consisting of 334 intensive care unit patients led to similar results, satisfying three standards for accuracy of BP monitors. The results indicate that the proposed method can contribute to the realization of ubiquitous non-invasive continuous BP monitoring.
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http://dx.doi.org/10.1109/JBHI.2020.3009658DOI Listing
April 2021

Changes of acetabular anteversion according to pelvic tilt on sagittal plane under various acetabular inclinations.

J Orthop Res 2021 04 10;39(4):806-812. Epub 2020 Jul 10.

Department of Orthopedics, Daegu Catholic University Medical Center, Daegu, South Korea.

Improper functional orientation of the acetabular cup can result in improper positions when dynamic pelvic positions are not considered. The purpose of this study was to evaluate changes on acetabular anteversion according to pelvic tilt under various acetabular inclinations. Two artificial pelvic models were selected for this study. Acetabular inclinations on the coronal plane were 25°, 32°, 50°, and 60°. Acetabular anteversion of all components were 15°. Changes of anteversion according to pelvic tilt were measured at angles of 0°, 10°, 20°, 30°, and 40°. Computer Navigation, PolyWare 3D pro, CT, and plain radiography were used to measure each angle. The anatomical anteversions against pelvic tilt were calculated using the following formulae: anatomical anteversion (°) = -14.48Χ + 90.18 (inclination angle 25°); anatomical anteversion (°) = -12.26Χ + 80.10 (inclination angle 32°); anatomical anteversion (°) = -7.468Χ + 61.13 (inclination angle 50°); and anatomical anteversion (°) = -5.328Χ + 44.84 (inclination angle 60°) (Χ: pelvic tilt angle). Radiographic anteversion against pelvic tilt were calculated using the following formulae: radiographic anteversion (°) = -9.50Χ + 57.09 (inclination angle 25°); radiographic anteversion (°) = -8.577Χ + 50.89 (inclination angle 32°); radiographic anteversion (°) = -6.794Χ + 45.73 (inclination angle 50°); radiographic anteversion (°) = -5.226Χ + 33.08 (inclination angle 60°). In conclusion, changes in anteversion according to pelvic tilt were lesser at higher degrees of acetabular inclination.
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http://dx.doi.org/10.1002/jor.24790DOI Listing
April 2021

Evaluation of Surgical Skills during Robotic Surgery by Deep Learning-Based Multiple Surgical Instrument Tracking in Training and Actual Operations.

J Clin Med 2020 Jun 23;9(6). Epub 2020 Jun 23.

Institute of Medical & Biological Engineering, Medical Research Center, Seoul National University College of Medicine, 101 Daehak-ro, Jongno-gu, Seoul 03080, Korea.

As the number of robotic surgery procedures has increased, so has the importance of evaluating surgical skills in these techniques. It is difficult, however, to automatically and quantitatively evaluate surgical skills during robotic surgery, as these skills are primarily associated with the movement of surgical instruments. This study proposes a deep learning-based surgical instrument tracking algorithm to evaluate surgeons' skills in performing procedures by robotic surgery. This method overcame two main drawbacks: occlusion and maintenance of the identity of the surgical instruments. In addition, surgical skill prediction models were developed using motion metrics calculated from the motion of the instruments. The tracking method was applied to 54 video segments and evaluated by root mean squared error (RMSE), area under the curve (AUC), and Pearson correlation analysis. The RMSE was 3.52 mm, the AUC of 1 mm, 2 mm, and 5 mm were 0.7, 0.78, and 0.86, respectively, and Pearson's correlation coefficients were 0.9 on the -axis and 0.87 on the -axis. The surgical skill prediction models showed an accuracy of 83% with Objective Structured Assessment of Technical Skill (OSATS) and Global Evaluative Assessment of Robotic Surgery (GEARS). The proposed method was able to track instruments during robotic surgery, suggesting that the current method of surgical skill assessment by surgeons can be replaced by the proposed automatic and quantitative evaluation method.
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http://dx.doi.org/10.3390/jcm9061964DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7355689PMC
June 2020

Reconstruction of 12-Lead Electrocardiogram from a Three-Lead Patch-Type Device Using a LSTM Network.

Sensors (Basel) 2020 Jun 9;20(11). Epub 2020 Jun 9.

Department of Biomedical Engineering, College of Medicine, Seoul National University, Seoul 03080, Korea.

Reconstructing a standard 12-lead electrocardiogram (ECG) from signals received from electrodes packed into a patch-type device is a challenging task in the field of medical instrumentation. All attempts to obtain a clinically valid 12-lead ECG using a patch-type device were not satisfactory. In this study, we designed the hardware for a three-lead patch-type ECG device and employed a long short-term memory (LSTM) network that can overcome the limitations of the linear regression algorithm used for ECG reconstruction. The LSTM network can overcome the issue of reduced horizontal components of the vector in the electric signal obtained from the patch-type device attached to the anterior chest. The reconstructed 12-lead ECG that uses the LSTM network was tested against a standard 12-lead ECG in 30 healthy subjects and ECGs of 30 patients with pathologic findings. The average correlation coefficient of the LSTM network was found to be 0.95. The ability of the reconstructed ECG to detect pathologic abnormalities was identical to that of the standard ECG. In conclusion, the reconstruction of a standard 12-lead ECG using a three-lead patch-type device is feasible, and such an ECG is an equivalent alternative to a standard 12-lead ECG.
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http://dx.doi.org/10.3390/s20113278DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7309162PMC
June 2020

Frontal EEG Changes with the Recovery of Carotid Blood Flow in a Cardiac Arrest Swine Model.

Sensors (Basel) 2020 May 28;20(11). Epub 2020 May 28.

Department of Biomedical Engineering, Seoul National University College of Medicine, Seoul 03080, Korea.

Monitoring cerebral circulation during cardiopulmonary resuscitation (CPR) is essential to improve patients' prognosis and quality of life. We assessed the feasibility of non-invasive electroencephalography (EEG) parameters as predictive factors of cerebral resuscitation in a ventricular fibrillation (VF) swine model. After 1 min untreated VF, four cycles of basic life support were performed and the first defibrillation was administered. Sustained return of spontaneous circulation (ROSC) was confirmed if a palpable pulse persisted for 20 min. Otherwise, one cycle of advanced cardiovascular life support (ACLS) and defibrillation were administered immediately. Successfully defibrillated animals were continuously monitored. If sustained ROSC was not achieved, another cycle of ACLS was administered. Non-ROSC was confirmed when sustained ROSC did not occur after 10 ACLS cycles. EEG and hemodynamic parameters were measured during experiments. Data measured for approximately 3 s right before the defibrillation attempts were analyzed to investigate the relationship between the recovery of carotid blood flow (CBF) and non-invasive EEG parameters, including time- and frequency-domain parameters and entropy indices. We found that time-domain magnitude and entropy measures of EEG correlated with the change of CBF. Further studies are warranted to evaluate these EEG parameters as potential markers of cerebral circulation during CPR.
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http://dx.doi.org/10.3390/s20113052DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7313692PMC
May 2020

Acquisition of coronal alignment according to the degree of varus deformity in total knee arthroplasty using computer-assisted navigation.

J Orthop Surg (Hong Kong) 2020 Jan-Apr;28(2):2309499020926268

Department of Orthopaedic Surgery, College of Medicine, Daegu Catholic University Hospital, Daegu, Korea.

Purpose: We have analyzed the surgical outcomes of primary total knee arthroplasty (TKA) using computer-assisted navigation that were performed by a single surgeon in terms of postoperative coronal alignment depending on preoperative varus deformity.

Methods: We conducted a retrospective study of patients who have undergone navigated primary TKA from January 2016 through December 2019. Two hundred and fifty-six cases with varus deformity of 10° or less were assigned to group 1, and 216 cases with varus deformity of more than 10° were assigned to group 2. The postoperative mechanical hip-knee-ankle (mHKA) angle was measured from scanograms which were taken preoperatively and 3 months after surgery. The postoperative mHKA angle was targeted to be 0°, and the appropriate range of coronal alignment was set as 0 ± 3°.

Results: The Pearson correlation showed a significant correlation with the degree of preoperative varus deformity and with the absolute error of postoperative mHKA ( = 0.01). Among all patients, 64 cases (13.6%) were detected as outliers (mHKA > 0° ± 3°) at 3 months after surgery. Of the 64 cases, 25 cases (9.8%) were affiliated to group 1 and 39 cases (18.1%) were affiliated to group 2. Group 2 showed significantly higher occurrence of outliers than group 1 ( = 0.01). Multiple variables logistic regression analysis, which analyzed the difference in the occurrence rate of outliers (mHKA > 0° ± 3°), showed that the occurrence rate of group 2 was 2.04 times higher than group 1. After adjusting for patient's age, gender, and body mass index, the occurrence rate of outliers in group 2 was 2.01 times higher than group 1.

Conclusion: The benefit of computer-assisted navigation during TKA in obtaining coronal alignment within 0 ± 3° may be lessened when the preoperative varus deformity is severely advanced.
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http://dx.doi.org/10.1177/2309499020926268DOI Listing
February 2021

Vision-based tracking system for augmented reality to localize recurrent laryngeal nerve during robotic thyroid surgery.

Sci Rep 2020 05 21;10(1):8437. Epub 2020 May 21.

Department of Biomedical Engineering, College of Medicine and Institute of Medical and Biological Engineering, Medical Research Center, Seoul National University, Seoul, Korea.

We adopted a vision-based tracking system for augmented reality (AR), and evaluated whether it helped surgeons to localize the recurrent laryngeal nerve (RLN) during robotic thyroid surgery. We constructed an AR image of the trachea, common carotid artery, and RLN using CT images. During surgery, an AR image of the trachea and common carotid artery were overlaid on the physical structures after they were exposed. The vision-based tracking system was activated so that the AR image of the RLN followed the camera movement. After identifying the RLN, the distance between the AR image of the RLN and the actual RLN was measured. Eleven RLNs (9 right, 4 left) were tested. The mean distance between the RLN AR image and the actual RLN was 1.9 ± 1.5 mm (range 0.5 to 3.7). RLN localization using AR and vision-based tracking system was successfully applied during robotic thyroidectomy. There were no cases of RLN palsy. This technique may allow surgeons to identify hidden anatomical structures during robotic surgery.
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http://dx.doi.org/10.1038/s41598-020-65439-6DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7242458PMC
May 2020

Improved Accuracy in Optical Diagnosis of Colorectal Polyps Using Convolutional Neural Networks with Visual Explanations.

Gastroenterology 2020 06 29;158(8):2169-2179.e8. Epub 2020 Feb 29.

Department of Internal Medicine, Healthcare Research Institute, Seoul National University Hospital Healthcare System Gangnam Center, Seoul, Korea; Department of Internal Medicine, Liver Research Institute, Seoul National University College of Medicine, Seoul, Korea. Electronic address:

Background & Aims: Narrow-band imaging (NBI) can be used to determine whether colorectal polyps are adenomatous or hyperplastic. We investigated whether an artificial intelligence (AI) system can increase the accuracy of characterizations of polyps by endoscopists of different skill levels.

Methods: We developed convolutional neural networks (CNNs) for evaluation of diminutive colorectal polyps, based on efficient neural architecture searches via parameter sharing with augmentation using NBIs of diminutive (≤5 mm) polyps, collected from October 2015 through October 2017 at the Seoul National University Hospital, Healthcare System Gangnam Center (training set). We trained the CNN using images from 1100 adenomatous polyps and 1050 hyperplastic polyps from 1379 patients. We then tested the system using 300 images of 180 adenomatous polyps and 120 hyperplastic polyps, obtained from January 2018 to May 2019. We compared the accuracy of 22 endoscopists of different skill levels (7 novices, 4 experts, and 11 NBI-trained experts) vs the CNN in evaluation of images (adenomatous vs hyperplastic) from 180 adenomatous and 120 hyperplastic polyps. The endoscopists then evaluated the polyp images with knowledge of the CNN-processed results. We conducted mixed-effect logistic and linear regression analyses to determine the effects of AI assistance on the accuracy of analysis of diminutive colorectal polyps by endoscopists (primary outcome).

Results: The CNN distinguished adenomatous vs hyperplastic diminutive polyps with 86.7% accuracy, based on histologic analysis as the reference standard. Endoscopists distinguished adenomatous vs hyperplastic diminutive polyps with 82.5% overall accuracy (novices, 73.8% accuracy; experts, 83.8% accuracy; and NBI-trained experts, 87.6% accuracy). With knowledge of the CNN-processed results, the overall accuracy of the endoscopists increased to 88.5% (P < .05). With knowledge of the CNN-processed results, the accuracy of novice endoscopists increased to 85.6% (P < .05). The CNN-processed results significantly reduced endoscopist time of diagnosis (from 3.92 to 3.37 seconds per polyp, P = .042).

Conclusions: We developed a CNN that significantly increases the accuracy of evaluation of diminutive colorectal polyps (as adenomatous vs hyperplastic) and reduces the time of diagnosis by endoscopists. This AI assistance system significantly increased the accuracy of analysis by novice endoscopists, who achieved near-expert levels of accuracy without extra training. The CNN assistance system can reduce the skill-level dependence of endoscopists and costs.
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http://dx.doi.org/10.1053/j.gastro.2020.02.036DOI Listing
June 2020

CT-based deep learning model to differentiate invasive pulmonary adenocarcinomas appearing as subsolid nodules among surgical candidates: comparison of the diagnostic performance with a size-based logistic model and radiologists.

Eur Radiol 2020 Jun 13;30(6):3295-3305. Epub 2020 Feb 13.

Department of Radiology, Seoul National University Hospital, Seoul National University College of Medicine, 101, Daehak-ro, Jongno-gu, Seoul, 03080, South Korea.

Objectives: To evaluate the deep learning models for differentiating invasive pulmonary adenocarcinomas (IACs) among subsolid nodules (SSNs) considered for resection in a retrospective diagnostic cohort in comparison with a size-based logistic model and expert radiologists.

Methods: This study included 525 patients (309 women; median, 62 years) to develop models, and an independent cohort of 101 patients (57 women; median, 66 years) was used for validation. A size-based logistic model and deep learning models using 2.5-dimension (2.5D) and three-dimension (3D) CT images were developed to discriminate IAC from less invasive pathologies. Overall performance, discrimination, and calibration were assessed. Diagnostic performances of the three thoracic radiologists were compared with those of the deep learning model.

Results: The overall performances of the deep learning models (Brier score, 0.122 for the 2.5D DenseNet and 0.121 for the 3D DenseNet) were superior to those of the size-based logistic model (Brier score, 0.198). The area under the receiver operating characteristic curve (AUC) of the 2.5D DenseNet (0.921) was significantly higher than that of the 3D DenseNet (0.835; p = 0.037) and the size-based logistic model (0.836; p = 0.009). At equally high sensitivities of 90%, the 2.5D DenseNet showed significantly higher specificity (88.2%; all p < 0.05) and positive predictive value (97.4%; all p < 0.05) than other models. Model calibration was poor for all models (all p < 0.05). The 2.5D DenseNet had a comparable performance with the radiologists (AUC, 0.848-0.910).

Conclusion: The 2.5D DenseNet model could be used as a highly sensitive and specific diagnostic tool to differentiate IACs among SSNs for surgical candidates.

Key Points: • The deep learning model developed using 2.5D DenseNet showed higher overall performance and discrimination than the size-based logistic model for the differentiation of invasive adenocarcinomas among subsolid nodules for surgical candidates. • The 2.5D DenseNet demonstrated a thoracic radiologist-level diagnostic performance and had higher specificity (88.2%) at equal sensitivities (90%) than the size-based logistic model (specificity, 52.9%). • The 2.5D DenseNet could be used to reduce potential overtreatment for the indolent subsolid nodules or to select candidates for sublobar resection instead of the standard lobectomy.
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http://dx.doi.org/10.1007/s00330-019-06628-4DOI Listing
June 2020

Automated Quantification of Macular Ellipsoid Zone Intensity in Glaucoma Patients: the Method and its Comparison with Manual Quantification.

Sci Rep 2019 12 24;9(1):19771. Epub 2019 Dec 24.

Department of Ophthalmology, Seoul National University College of Medicine, Seoul, Korea.

The macular ellipsoid zone intensity (mEZi) is a known marker of disease severity in a number of diverse ocular diseases. The purpose of this study was to establish an automated method (AM) for mEZi quantification and to compare the method's performance with that of a manual method (MM) for glaucoma patients and healthy controls. Seventy-one (71) mild-to-moderate glaucoma patients, 71 severe-glaucoma patients, and 51 controls were enrolled. Both calibration (n = 160) and validation (n = 33) image sets were compiled. The correlation of AM to MM quantification was assessed by Deming regression for the calibration set, and a compensation formula was generated. Then, for each image in the validation set, the compensated AM quantification was compared with the mean of five repetitive MM quantifications. The AM quantification of the calibration set was found to be linearly correlated with MM in the normal-to-severe-stage glaucoma patients (R = 0.914). The validation set's compensated AM quantification produced R = 0.991, and the relationship between the 2 quantifications was AM = 1.004(MM) + 0.139. In the validation set, the compensated AM quantification fell within MM quantification's 95% confidence interval in 96.9% of the images. An AM for mEZi quantification was calibrated and validated relative to MM quantification for both glaucoma patients and healthy controls.
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http://dx.doi.org/10.1038/s41598-019-56337-7DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6930206PMC
December 2019

Analysis of Pulse Arrival Time as an Indicator of Blood Pressure in a Large Surgical Biosignal Database: Recommendations for Developing Ubiquitous Blood Pressure Monitoring Methods.

J Clin Med 2019 Oct 24;8(11). Epub 2019 Oct 24.

Department of Biomedical Engineering, College of Medicine, Seoul National University, Seoul 03080, Korea.

As non-invasive continuous blood pressure monitoring (NCBPM) has gained wide attraction in the recent decades, many pulse arrival time (PAT) or pulse transit time (PTT) based blood pressure (BP) estimation studies have been conducted. However, most of the studies have used small homogeneous subject pools to generate models of BP based on particular interventions for induced hemodynamic change. In this study, a large open biosignal database from a diverse group of 2309 surgical patients was analyzed to assess the efficacy of PAT, PTT, and confounding factors on the estimation of BP. After pre-processing the dataset, a total of 6,777,308 data pairs of BP and temporal features between electrocardiogram (ECG) and photoplethysmogram (PPG) were extracted and analyzed. Correlation analysis revealed that PAT or PTT extracted from the intersecting-tangent (IT) point of PPG showed the highest mean correlation to BP. The mean correlation between PAT and systolic blood pressure (SBP) was -0.37 and the mean correlation between PAT and diastolic blood pressure (DBP) was -0.30, outperforming the correlation between BP and PTT at -0.12 for SBP and -0.11 for DBP. A linear model of BP with a simple calibration method using PAT as a predictor was developed which satisfied international standards for automatic oscillometric BP monitors in the case of DBP, however, SBP could not be predicted to a satisfactory level due to higher errors. Furthermore, multivariate regression analyses showed that many confounding factors considered in previous studies had inconsistent effects on the degree of correlation between PAT and BP.
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http://dx.doi.org/10.3390/jcm8111773DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6912522PMC
October 2019

Dynamics of driftless preconcentration using ion concentration polarization leveraged by convection and diffusion.

Lab Chip 2019 10 2;19(19):3190-3199. Epub 2019 Sep 2.

Department of Electrical and Computer Engineering, Seoul National University, Seoul, 08826, Republic of Korea. and Nano Systems Institute, Seoul National University, Seoul, 08826, South Korea and Inter-University Semiconductor Research Center, Seoul National University, Seoul, 08826, South Korea.

Over the past several decades, separation and preconcentration methods of (bio)molecules have been actively developed for various biomedical and chemical processes such as disease diagnostics, point of care test and environmental monitoring. Among the great developments of the electrokinetic method in a micro/nanofluidic platform is the ion concentration polarization (ICP) phenomenon, in which a target molecule is accumulated near a permselective nanoporous membrane under an applied electric field. ICP method has been actively studied due to its easy implementation and high preconcentration/separation efficiency. However, the dynamic behavior of preconcentrated analytes has not yet been fully studied, especially driftless migration, where the applied electric field is orthogonal to the direction of the drift migration. Here, we demonstrate anomalous shapes of preconcentrated analytes (either plug or dumbbell shape) and the morphologies were analytically modeled by the leverage of convection and diffusion migration. This model was experimentally verified with various lengths of DNA and the limiting cases (convection-free environment in paper-based microfluidic device and extremely low diffusivity of red blood cells) were also shown to confirm the model. Thus, this study not only provides an insight into the fundamental electrokinetic dynamics of molecules in an ICP platform but also plays a guiding role for the design of a nanofluidic preconcentrator for a lab on a chip application.
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http://dx.doi.org/10.1039/c9lc00508kDOI Listing
October 2019

"Weighing Cam": A New Mobile Application for Weight Estimation in Pediatric Resuscitation.

Prehosp Emerg Care 2020 May-Jun;24(3):441-450. Epub 2019 Aug 29.

We evaluated the validity of a newly developed mobile application (i.e. the Weighing Cam) for pediatric weight estimation compared with that of the Broselow tape. We developed an application that estimates the weight of pediatric patients using a smartphone camera and displays the drug dosage, device size, and defibrillation energy on the screen of the smartphone. We enrolled a convenience sample of pediatric patients aged <16 years who presented at two pediatric emergency departments of two tertiary academic hospitals in South Korea. The pediatric patients' heights and weights were measured; then, one researcher estimated the weights using the application. Using the measured height, we determined the weight estimated by the Broselow tape. We compared the estimated measurements by determining the mean percentage error (MPE), mean absolute percentage error, root mean square percentage error, and percentages predicted within 10% and 20% of the actual. In total, 480 patients were enrolled in 16 age categories, each with 15 males and 15 females of different ages. The Weighing Cam demonstrated a lower bias (mean difference: -1.98% [95% confidence interval -2.91% to -1.05%] for MPE) and a higher proportion of estimated weights within 10% of the actual weights than the Broselow tape (mean difference: 9.1% [95% confidence interval 3.0% to 15.1%]). The Weighing Cam showed better performance in terms of accuracy and precision than the Broselow tape in all subgroups stratified by age or body mass index percentile. The Weighing Cam may estimate pediatric patients' weights more accurately than the Broselow tape. The Weighing Cam may be useful for pediatric resuscitation in both prehospital and hospital settings.
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http://dx.doi.org/10.1080/10903127.2019.1651432DOI Listing
August 2019

Estimating Maximal Oxygen Uptake From Daily Activity Data Measured by a Watch-Type Fitness Tracker: Cross-Sectional Study.

JMIR Mhealth Uhealth 2019 06 13;7(6):e13327. Epub 2019 Jun 13.

Interdisciplinary Program in Bioengineering, Seoul National University, Seoul, Republic of Korea.

Background: Cardiorespiratory fitness (CRF), an important index of physical fitness, is the ability to inhale and provide oxygen to the exercising muscle. However, despite its importance, the current gold standard for measuring CRF is impractical, requiring maximal exercise from the participants.

Objective: This study aimed to develop a convenient and practical estimation model for CRF using data collected from daily life with a wristwatch-type device.

Methods: A total of 191 subjects, aged 20 to 65 years, participated in this study. Maximal oxygen uptake (VO max), a standard measure of CRF, was measured with a maximal exercise test. Heart rate (HR) and physical activity data were collected using a commercial wristwatch-type fitness tracker (Fitbit; Fitbit Charge; Fitbit) for 3 consecutive days. Maximal activity energy expenditure (aEEmax) and slope between HR and physical activity were calculated using a linear regression. A VO max estimation model was built using multiple linear regression with data on age, sex, height, percent body fat, aEEmax, and the slope. The result was validated with 2 different cross-validation methods.

Results: aEEmax showed a moderate correlation with VO max (r=0.50). The correlation coefficient for the multiple linear regression model was 0.81, and the SE of estimate (SEE) was 3.518 mL/kg/min. The regression model was cross-validated through the predicted residual error sum of square (PRESS). The PRESS correlation coefficient was 0.79, and the PRESS SEE was 3.667 mL/kg/min. The model was further validated by dividing it into different subgroups and calculating the constant error (CE) where a low CE showed that the model does not significantly overestimate or underestimate VO max.

Conclusions: This study proposes a CRF estimation method using data collected by a wristwatch-type fitness tracker without any specific protocol for a wide range of the population.
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http://dx.doi.org/10.2196/13327DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6592480PMC
June 2019

A Novel Wearable EEG and ECG Recording System for Stress Assessment.

Sensors (Basel) 2019 Apr 28;19(9). Epub 2019 Apr 28.

Interdisciplinary Program in Bioengineering, Graduate School, Seoul National University, Seoul 03080, Korea.

Suffering from continuous stress can lead to serious psychological and even physical disorders. Objective stress assessment methods using noninvasive physiological responses such as heart rate variability (HRV) and electroencephalograms (EEG) have therefore been proposed for effective stress management. In this study, a novel wearable device that can measure electrocardiograms (ECG) and EEG simultaneously was designed to enable continuous stress monitoring in daily life. The developed system is easily worn by hanging from both ears, is lightweight (i.e., 42.5 g), and exhibits an excellent noise performance of 0.12 μVrms. Significant time and frequency features of HRV and EEG were found in two different stressors, namely the Stroop color word and mental arithmetic tests, using 14 young subjects. Stressor situations were classified using various HRV and EEG feature selections and a support vector machine technique. The five-fold cross-validation results obtained when using both EEG and HRV features showed the best performance with an accuracy of 87.5%, which demonstrated the requirement for simultaneous HRV and EEG measurements.
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http://dx.doi.org/10.3390/s19091991DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6539530PMC
April 2019

Wirelessly Controlled Implantable System for On-demand and Pulsatile Insulin Administration.

Sci Rep 2019 03 21;9(1):5009. Epub 2019 Mar 21.

Institute of Medical and Biological Engineering, Medical Research Center, Seoul National University, Seoul, 03080, Republic of Korea.

We propose a wirelessly controlled implantable system for on-demand and pulsatile insulin delivery with a more convenient and safer strategy than currently available strategies. The system is a combined entity of a magnetically driven pump (i.e., an MDP), external control device (i.e., an ECD) and mobile app. The MDP for implantation consists of a plunger, barrel and drug reservoir, where an accurate amount of insulin can be infused in a pulsatile manner only at the time when a magnetic force is applied to actuate the plunger in the barrel. The ECD at the outside body can modulate the MDP actuation with an electromagnet and its control circuit, and this modulation can be wirelessly controlled by the mobile app. As a safety feature, the mobile app is programmed to pre-set the restrictions for the insulin dose and administration schedule to avoid overdose. The system is shown to infuse insulin in a highly reproducible manner, but it does not allow for insulin infusion when the pre-set restrictions are violated. When tested with diabetic rats, the profiles of insulin plasma concentration and blood glucose level are similar to those of animals treated with a subcutaneous injection of the same dose of insulin.
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http://dx.doi.org/10.1038/s41598-019-41430-8DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6428930PMC
March 2019

Acoustic Trapping Technique for Studying Calcium Response of a Suspended Breast Cancer Cell: Determination of Its Invasion Potentials.

IEEE Trans Ultrason Ferroelectr Freq Control 2019 04 24;66(4):737-746. Epub 2019 Jan 24.

A noncontact single-beam acoustic trapping technique has proven to be a promising tool for cell manipulation and characterization that provide essential knowledge for a variety of biomedical applications. Here, we investigated cell characteristics as to whether the calcium responses of suspended breast cancer cells to different acoustic trapping forces are related to their invasiveness. For this, we combined a single-beam acoustic trapping system with a 30-MHz press-focused lithium niobate ultrasound transducer and an epifluorescence microscope. Using the system, intracellular calcium changes of suspended MDA-MB-231 (highly invasive) and MCF-7 (weakly invasive) cells were monitored while trapping the cells at different acoustic pressures. The results showed that a single suspended breast cancer cell isolated by the acoustic microbeam behaved differently on the calcium elevation in response to changes in acoustic trapping force, depending on its invasiveness. In particular, the MDA-MB-231 cells exhibited higher calcium elevation than MCF-7 cells when each cell was trapped at low acoustic pressure. Based on these results, we believe that the single-beam acoustic trapping technique has high potential as an alternative tool for determining the degree of invasiveness of suspended breast cancer cells.
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http://dx.doi.org/10.1109/TUFFC.2019.2894662DOI Listing
April 2019

Application of a Perception Neuron System in Simulation-Based Surgical Training.

J Clin Med 2019 Jan 21;8(1). Epub 2019 Jan 21.

Department of Biomedical Engineering, Seoul National University College of Medicine, 101 Daehak-ro, Jongno-gu, Seoul 03080, Korea.

While multiple studies show that simulation methods help in educating surgical trainees, few studies have focused on developing systems that help trainees to adopt the most effective body motions. This is the first study to use a Perception Neuron system to evaluate the relationship between body motions and simulation scores. Ten medical students participated in this study. All completed two standard tasks with da Vinci Skills Simulator (dVSS) and five standard tasks with thyroidectomy training model. This was repeated. Thyroidectomy training was conducted while participants wore a perception neuron. Motion capture (MC) score that indicated how long the tasks took to complete and each participant's economy-of-motion that was used was calculated. Correlations between the three scores were assessed by Pearson's correlation analyses. The 20 trials were categorized as low, moderate, and high overall-proficiency by summing the training model, dVSS, and MC scores. The difference between the low and high overall-proficiency trials in terms of economy-of-motion of the left or right hand was assessed by two-tailed -test. Relative to cycle 1, the training model, dVSS, and MC scores all increased significantly in cycle 2. Three scores correlated significantly with each other. Six, eight, and six trials were classified as low, moderate, and high overall-proficiency, respectively. Low- and high-scoring trials differed significantly in terms of right (dominant) hand economy-of-motion (675.2 mm and 369.4 mm, respectively) ( = 0.043). Perception Neuron system can be applied to simulation-based training of surgical trainees. The motion analysis score is related to the traditional scoring system.
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http://dx.doi.org/10.3390/jcm8010124DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6352185PMC
January 2019