• Journal of Biomedical Engineering Research
• /
• v.40 no.5
• /
• pp.206-214
• /
• 2019

Surgical methods and associated precision systems have been developed, but surgical procedures that require precise location and fine manipulation of the lesion remain a limitation. The combination of precision robot manipulation technology and 3D medical image navigation technology overcomes the limitations of minimally invasive surgery (MIS) and enables a more stable and successful operation. Surgical robots are surgical robots such as da Vince, and surgical robots using industrial robotic arms. There are various developments and researches of medical robots. In recent medical robot development, a new type of surgical robot based on an industrial robot arm capable of easily replacing the end effector according to the user's needs is being actively developed at home and abroad. Therefore, in this study, we developed safety and performance evaluation guideline for micro - surgical robots based on open robot platform using general purpose robot arm to help quality control of the medical device.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2009.10a
• /
• pp.355-358
• /
• 2009

Due to growth of electronics and control devices, automation and situational awareness systems have been applied by automobile. Vision systems with the introduction of unmanned system being actively developed, but are still high price and visual information is passed through the cable, because of cars are difficult to install. In this paper, can be installed inside the car at low-cost, simple image processing device through a wireless communication know the obstacles and the alarm system based on Zigbee wireless communication, infrared and ultrasonic sensors to monitor the situation through with easy parking cars outside the system design was implemented.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2009.10a
• /
• pp.273-275
• /
• 2009

In recent years, many home machines have been developed in order to design and control comfortable interior inside houses. For such task, important factors are temperature, natural and interior lights, and space and control of relative factors each other. This paper presents novel sensor module inside houses, which is designed based on these factors through the PMV (Predicted Mean Vote) standard using information about home state. Moreover, LonWorks based power line communication technique is utilized for control interior lights and air-conditioners by means of wireless remote controllers. This mechanism is systemically operated via intelligent control framework.

• Journal of Biomedical Engineering Research
• /
• v.42 no.6
• /
• pp.287-294
• /
• 2021

Cardiotoxicity assessment of all drugs has been performed according to the ICH guidelines since 2005. Non-clinical evaluation S7B has focused on the hERG assay, which has a low specificity problem. The comprehensive in vitro proarrhythmia assay (CiPA) project was initiated to correct this problem, which presented a model for classifying the Torsade de pointes (TdP)-induced risk of drugs as biomarkers calculated through an in silico ventricular model. In this study, we propose a TdP-induced risk group classifier of artificial neural network (ANN)-based. The model was trained with 12 drugs and tested with 16 drugs. The ANN model was performed according to nine features, seven features, five features as an individual ANN model input, and the model with the highest performance was selected and compared with the classification performance of the qNet input logistic regression model. When the five features model was used, the results were AUC 0.93 in the high-risk group, AUC 0.73 in the intermediate-risk group, and 0.92 in the low-risk group. The model's performance using qNet was lower than the ANN model in the high-risk group by 17.6% and in the low-risk group by 29.5%. This study was able to express performance in the three risk groups, and it is a model that solved the problem of low specificity, which is the problem of hERG assay.

• Journal of Biomedical Engineering Research
• /
• v.44 no.1
• /
• pp.85-91
• /
• 2023

Stress urinary incontinence (SUI) occurs when abdominal pressure increases, such as sneezing, exercising, and laughing. Surgical and non-surgical treatments are the common methods of SUI treatment; however, the conventional treatments still require continuous and invasive treatment. Laser have been used to treat SUI, but excessive temperature increase often causes thermal burn on urethra tissue. Therefore, the optimal conditions must be considered to minimize the thermal damage for the laser treatment. The current study investigated the feasibility of the laser irradiation condition for SUI treatment using non-ablative 980 nm laser from a safety perspective through numerical simulations. COMSOL Multiphysics was used to analyze the numerical simulation model. The Pennes bioheat equation with the Beer's law was used to confirm spatio-temporal temperature distributions, and Arrhenius equation defined the thermal damage caused by the laser-induced heat. Ex vivo porcine urethral tissue was tested to validate the extent of both temperature distribution and thermal damage. The temperature distribution was symmetrical and uniformly observed in the urethra tissue. A muscle layer had a higher temperature (28.3 ℃) than mucosal (23.4 ℃) and submucosal layers (25.5 ℃). MT staining revealed no heat-induced collagen and muscle damage. Both control and treated groups showed the equivalent thickness and area of the urethral mucosal layer. Therefore, the proposed numerical simulation can predict the appropriate irradiation condition (20 W for 15 s) for the SUI treatment with minimal temperature-induced tissue.

• Journal of Biomedical Engineering Research
• /
• v.44 no.1
• /
• pp.92-98
• /
• 2023

Purpose: To propose a new infusion rate monitoring technique based on the 2D image marker tacking to improve patient safety by preventing syringe pump-related medication accidents due to decreased infusion rate control accuracy. Materials and Methods: The infusion rate of the syringe pump and drug residue in the pump-equipped syringe were monitored in real time by tracking the movement of the 2D image markers attached to the syringe pump. Results: The error rate between the set and the estimated infusion rates was 1.03, 0.66, 1.95, 0.23, and 1.05% when the infusion rate setting was 10, 20, 30, 40, and 50 mL/H, respectively. In addition, the error rate between the actual and the estimated drug residues was 1.04, 0.47, 0.60, 3.66, and 0.00% when the infusion rate setting was 10, 20, 30, 40, and 50 mL/H, respectively. Conclusion: Experimental results demonstrated that the proposed technique can increase the efficiency of the safety management system for seriously ill inpatients by decreasing a possibility of syringe pump-related medication accidents in hospitals.

• Journal of Biomedical Engineering Research
• /
• v.43 no.4
• /
• pp.280-289
• /
• 2022

In this paper, we present a QRS-complex detection algorithm to calculate an accurate heartbeat and clearly recognize irregular rhythm from ECG signals. The conventional Pan-Tompkins algorithm brings false QRS detection in the derivative when QRS and noise signals have similar instant variation. The proposed algorithm uses amplitude differences in 7 adjacent samples to detect QRS-complex which has the highest amplitude variation. The calculated amplitude is cubed to dominate QRS-complex and the moving average method is applied to diminish the noise signal's amplitude. Finally, a decision rule with a threshold value is applied to detect accurate QRS-complex. The calculated signals with Pan-Tompkins and proposed algorithms were compared by signal-to-noise ratio to evaluate the noise reduction degree. QRS-complex detection performance was confirmed by sensitivity and the positive predictive value(PPV). Normal ECG, muscle noise ECG, PVC, and atrial fibrillation signals were achieved which were measured from an ECG simulator. The signal-to-noise ratio difference between Pan-Tompkins and the proposed algorithm were 8.1, 8.5, 9.6, and 4.7, respectively. All ratio of the proposed algorithm is higher than the Pan-Tompkins values. It indicates that the proposed algorithm is more robust to noise than the Pan-Tompkins algorithm. The Pan-Tompkins algorithm and the proposed algorithm showed similar sensitivity and PPV at most waveforms. However, with a noisy atrial fibrillation signal, the PPV for QRS-complex has different values, 42% for the Pan-Tompkins algorithm and 100% for the proposed algorithm. It means that the proposed algorithm has superiority for QRS-complex detection in a noisy environment.

• Journal of the Korea Society of Computer and Information
• /
• v.14 no.12
• /
• pp.25-32
• /
• 2009

This paper proposes the construction of intelligent home network system using Power Line Communication(PLC) technique, which allows for UPnP bridge remote control and monitoring based on TCP/IP. Also, the communication for control module inside intelligent home network systems is designed with Simple Control Protocol (SCP) in which each device is connected to be controlled independently. When new UPnP device is additionally installed in intelligent home network systems, it is monitored through UPnP bridges based on its registered UPnP device information. The device control based on PLC and implementation of each UPnP device are effectively managed by using TCP/IP remote control and it's provided fundamental functions to monitor various device information in the home network.

• Journal of Biomedical Engineering Research
• /
• v.45 no.2
• /
• pp.101-107
• /
• 2024

Steady-state visual evoked potential-based brain-computer interface (SSVEP-BCI) is one of the promising systems that can serve as an alternative input device due to its stable and fast performance. However, one of the major bottlenecks is that some individuals exhibit no or very low SSVEP responses to flickering stimulation, known as SSVEP illiteracy, resulting in low performance on SSVEP-BCIs. However, a lengthy duration is required to enhance multiple SSVEP responses using traditional single-frequency transcranial alternating current stimulation (tACS). This research proposes a novel approach using dual-frequency tACS (df-tACS) to potentially enhance SSVEP by targeting the two frequencies with the lowest signal-to-noise ratio (SNR) for each participant. Seven participants (five males, average age: 24.42) were exposed to flickering checkerboard stimuli at six frequencies to determine the weakest SNR frequencies. These frequencies were then simultaneously stimulated using df-tACS for 20 minutes, and the experiment was repeated to evaluate changes in SSVEP responses. The results showed that df-tACS effectively enhances the SNR at each targeted frequency, suggesting it can selectively improve target frequency responses. The study supports df-tACS as a more efficient solution for SSVEP illiteracy, proposing further exploration into multi-frequency tACS that could stimulate more than two frequencies, thereby expanding the potential of SSVEP-BCIs.

• Journal of Biomedical Engineering Research
• /
• v.45 no.3
• /
• pp.128-137
• /
• 2024

It is necessary to develop a pulsatile Extracorporeal Membrane Oxygenator (p-ECMO) with counter-pulsation control(CPC), which ejects blood during the diastolic phase of the heart rather than the systolic phase, due to the known issues with conventional ECMO causing fatal complications such as ventricular dilation and pulmonary edema. A promising method to simultaneously detect the pulsations of the heart and p-ECMO is to analyze blood pressure waveforms using deep neural network technology(DNN). However, the accurate detection of cardiac rhythms by DNNs is challenging due to various noises such as pulsations from p-ECMO, reflected waves in the vessels, and other dynamic noises. This study aims to evaluate the accuracy of DNNs developed for CPC in p-ECMO, using human-like blood pressure waveforms reproduced in an in-vitro experiment. Especially, an experimental setup that reproduces reflected waves commonly observed in actual patients was developed, and the impact of these waves on DNN judgments was assessed using a multiple DNN (m-DNN) that provides accurate determinations along with a separate index for heartbeat recognition ability. In the experimental setup inducing reflected waves, it was observed that the shape of the blood pressure waveform became increasingly complex, which coincided with an increase in harmonic components, as evident from the Fast Fourier Transform results of the blood pressure wave. It was observed that the recognition score (RS) of DNNs decreased in blood pressure waveforms with significant harmonic components, separate from the frequency components caused by the heart and p-ECMO. This study demonstrated that each DNN trained on blood pressure waveforms without reflected waves showed low RS when faced with waveforms containing reflected waves. However, the accuracy of the final results from the m-DNN remained high even in the presence of reflected waves.