• Korean Journal of Applied Biomechanics
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• v.21 no.4
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• pp.495-501
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• 2011

The purpose of this study was to develop the inertial sensor module system to detect gait event using single angular rate sensor(gyroscope), and evaluate the accuracy of this system. This sensor module is attached at the heel and gait events such as heel strike, foot flat, heel off, toe off are detected by using proposed automatic event detection algorithm. The developed algorithm detect characteristics of pitch data of the gyroscope to find gait event. To evaluate the accuracy of system, 3D motion capture system was used and synchronized with sensor module system for comparison of gait event timings. In experiment, 6 subjects performed 5 trials level walking with 3 different conditions such as slow, preferred and fast. Results showed that gait event timings by sensor module system are similar to that by kinematic data, because maximum absolute errors were under 37.4msec regardless of gait velocity. Therefore, this system can be used to detect gait events. Although this system has advantages of small, light weight, long-term monitoring and high accuracy, it is necessary to improve the system to get other gait information such as gait velocity, stride length, step width and joint angles.

• Proceedings of the KOSOMBE Conference
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• v.1998 no.11
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• pp.187-188
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• 1998

A low cost, low power, portable cardiac event recorder as a tether-free biological signal processor was developed. Dual channel ECG signals are sampled at 128Hz in 12 bits resolution. Sampled data are continuously recorded in a circular buffer. If event button is pressed, 2 minutes data before and after the event are recorded in 512 Kbyte SRAM. Total 11 events can be recorded. Data can be transferred to PC through RS-232 protocol. It operates for two months by a half AA size 3.6V Lithium battery. The system size is $55\times55\times13[mm^3]$.

• Journal of Biomedical Engineering Research
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• v.29 no.6
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• pp.443-450
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• 2008

The purpose of this study is to measure both ECG and BCG(Ballistocariograph) signal of a subject on moving or resting wheelchair and detect the heart rate and respiratory rate and transmit an event message to remote server on emergent situation. To acquire ECG and BCG data, amplifier circuits were composed to be suitable for their characteristics. The output signals were converted to digital data and stored in bio-signal archiving media(SD card). CDMA module was used to transmit the event data on ECG electrode detachment and the received data was monitored by the developed C# application program. 5 volunteers participated in the experiment to evaluate the validity of the developed device. When the event occurs in each subject, 48 Kbyte data, stored for 32 seconds from that point, was transmitted to remote server through CDMA cellular phone network correctly. The received data of ECG, BCG, and 3-axial acceleration could be archived in server and the heart rate and respiratory rate could be measured and analyzed. The developed device in this study could acquire the ECG and BCG data of subjects on wheelchair simultaneously and measure their heart rate and respiratory rate. In addition, event data was verified to be transmitted to remote server without any errors.

• Journal of the Korean Society for Library and Information Science
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• v.51 no.4
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• pp.77-97
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• 2017

A recent sharp increase of the biomedical literature causes researchers to struggle to grasp the current research trends and conduct creative studies based on the previous results. In order to alleviate their difficulties in keeping up with the latest scholarly trends, numerous attempts have been made to develop specialized analytic services that can provide direct, intuitive and formalized scholarly information by using various text mining technologies such as information extraction and event detection. This paper introduces and evaluates total 8 Convolutional Neural Network (CNN) models for extracting biomedical events from academic abstracts by applying various feature utilization approaches. Also, this paper conducts performance comparison evaluation for the proposed models. As a result of the comparison, we confirmed that the Entity-Type-Fully-Connected model, one of the introduced models in the paper, showed the most promising performance (72.09% in F-score) in the event classification task while it achieved a relatively low but comparable result (21.81%) in the entire event extraction process due to the imbalance problem of the training collections and event identify model's low performance.

• Proceedings of the Korean Society of Medical Physics Conference
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• 2006.08a
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• pp.45-45
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• 2006

• Proceedings of the KSMRM Conference
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• 2003.10a
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• pp.81-81
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• 2003

This event-related fMRI study was to further our understanding about how different brain regions could contribute to effective access of specific information related to cognitive process and shows the different response of brain regions involved in recognition of familiar faces compared to unfamiliar faces and repetition effect.

• Journal of Biomedical Engineering Research
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• v.30 no.4
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• pp.306-310
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• 2009

The purpose of this study is to observe the change in gamma-band cortical activities (GBAs) due to task difficulty. Event-related potential and gamma-band activity were investigated using electroencephalograms recorded during auditory oddball tasks with two difficulty levels. For more difficult task, the amplitude of P300 decreased and the peak latency of P300 was delayed significantly compared to easier task. The induced GBA decreased considerably during the P300 latency period and the peak latency of the induced GBA was delayed for more difficult task. The results imply that the difficulty-related change in cortical information processing may be implemented as a change in the strength of local neuronal association.

• Journal of Electrical Engineering and Technology
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• v.7 no.3
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• pp.451-458
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• 2012

The voluntary EMG (vEMG) signal from electrically stimulated muscle is very useful for feedback control in functional electrical stimulation. However, the recorded EMG signal from surface electrodes has unwanted stimulation artifact and M-wave as well as vEMG. Here, we propose an event-synchronous adaptive digital filter for the suppression of stimulation artifact and M-wave in this application. The proposed method requires a simple experimental setup that does not require extra hardware connections to obtain the reference signals of adaptive digital filter. For evaluating the efficiency of this proposed method, the filter was tested and compared with a least square (LS) algorithm using previously measured data. We conclude that the cancellation of both primary and residual stimulation artifacts is enhanced with an event-synchronous adaptive digital filter and shows promise for clinical application to rehabilitate paretic limbs. Moreover because this algorithm is far simpler than the LS algorithm, it is portable and ready for real-time application.

• Korean Journal of Applied Biomechanics
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• v.19 no.1
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• pp.159-166
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• 2009

The purpose of this study was to develop and automatic gait event detection algorithm using single accelerometer which is attached at the top of the shoe. The sinal vector magnitude and anterior-posterior(x-axis) directional component of accelerometer were used to detect heel strike(HS) and toe off(TO), respectively. To evaluate proposed algorithm, gait event timing was compared with that by force plate and kinematic data. In experiment, 7 subjects performed 10 trials level walking with 3 different walking conditions such as fast, preferred & slow walking. An accelerometer, force plate and 3D motion capture system were used during experiment. Gait event by force plate was used as reference timing. Results showed that gait event by accelerometer is similar to that by force plate. The distribution of differences were spread about $22.33{\pm}17.45m$ for HS and $26.82{\pm}14.78m$ for To and most error was existed consistently prior to 20ms. The difference between gait event by kinematic data and developed algorithm was small. Thus it can be concluded that developed algorithm can be used during outdoor walking experiment. Further study is necessary to extract gait spatial variables by removing gravity factor.

• Journal of Biomedical Engineering Research
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• v.29 no.4
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• pp.295-301
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• 2008

A wireless 3 channel ECG monitoring system was developed so that it could monitor the health and movement state during subject's daily life. The developed system consists of a wireless biomedical signal acquisition device, a personal healthcare server, and a remote medical server. Three experiments were performed to evaluate the accuracy, reliability and operability, applicability during daily life of the developed device. First, ECG signals were measured using the developed device and commercial reference device during sitting and marking time and compared to verify the accuracy of R-R intervals. Second, the reliable data transmission to remote server was verified on two types of simulated emergency event using patient simulator. Third, during five types of motion in daily life, the accuracy of data transmission to remote server using CDMA network was verified on two types of event occurring. By acquiring and comparing subject's biomedical signal and motion signal, the accuracy, reliability and operability, applicability during daily life of the developed device were verified. In addition, PDA-phone based wireless system enabled subject to be monitored without any constraints. Therefore, the developed system is expected to be applicable for monitoring the aged and chronic diseased people and giving first-aid in emergency.