• Journal of Biomedical Engineering Research
• /
• v.15 no.4
• /
• pp.465-474
• /
• 1994

This study is concerned with a method which helps human to generate EMG signals accurately and consistently to make reliable design samples of function discriminator for prosthetic arm control. We intend to ensure a signal accuracy and consistency by training human as a signal generation source. For the purposes, we construct a human training system using a digital computer, which generates visual graphes to compare real target motion trajectory with the desired one, to observe EMG signals and their features. To evaluate the effect which affects a feature variance and a feature separability between motion classes by the human training system, we select 4 features such as integral absolute value, zero crossing counts, AR coefficients and LPC cepstrum coefficients. We perform a experiment four times during 2 months. The experimental results show that the hu- man training system is effective for accurate and consistent EMG signal generation and reduction of a feature variance, but is not correlated for a feature separability, The cepstrum coefficient is the most preferable among the used features for reduction of variance, class separability and robustness to a time varing property of EMG signals.

• Proceedings of the KOSOMBE Conference
• /
• v.1997 no.11
• /
• pp.35-38
• /
• 1997

A new approach to the measurement of muscle fiber conduction velocity by surface electro-myography(EMG) is developed, based upon a robust time-delay estimation algorithm. Unlike previously reported methods, it does not require the Gaussian assumption of raw EMG signal, and can be applied accurately in non-gaussian impulsive EMG signal. For ive healthy subjects the conduction velocity in the biceps brachii and vastus medialis was measured and compared with various other techniques. As a result, the average muscle fiber conduction velocity was $4.59{\pm}0.20m/s$ in case of biceps brachii and $5.67{\pm}0.33m/s$ in vastus medialis.

• Proceedings of the KOSOMBE Conference
• /
• v.1997 no.11
• /
• pp.571-574
• /
• 1997

fMRI, functional MRI introduced recently appears based on the gradient echo technique which is sensitive to the field inhomogeneity developed due to the local susceptibility changes of blood oxygenation and deoxygenation. Common to all the gradient echo techniques is that the signal due to the susceptibility effects is generally decreased with increasing inhomogeneity due to the $T2^*$ effect or conventionally known as blood oxygenation level dependent (BOLD) effect. It is, also found that the BOLD sensitivity is also dependent on the imaging modes, namely whether the imaging is in axial, or coronal or sagittal mode as well as the directions of the vessels against the main magnetic field. We have, therefore, launched a systematic study of imaging mode dependent signal change or BOLD sensitivity as well as the signal changes due to the tilting angle of the imaging planes. Study has been made or both TRFGE sequence and CGE sequence to compare the distinctions of the each mode since each technique has different sensitivity against susceptibility effect. Method of computation and both the computer simulations and their corresponding experimental results are presented.

• Proceedings of the KOSOMBE Conference
• /
• v.1998 no.11
• /
• pp.96-97
• /
• 1998

3D TOF MR Angiography is able to obtain thinner slice thickness, higher SNR, therefore higher spatial resolution than 2D TOF MR Angiography. Since it uses longer TR than 2D TOF MRA to allow stronger in-flow effect, the background tissue may not be fully saturated. Thus background tissue signal can be further suppressed by MTS(Magnetization Transfer Saturation). Flow-compensation was accomplished by GMN(Gradient Moment Nulling), and tracking saturation was used to suppress vein signal. The different flow signal at the entry of the slab and output of the slab can be compensated by TONE(Tilted Optimized Non-saturating Excitation) RF pulse.

• Journal of Biomedical Engineering Research
• /
• v.26 no.3
• /
• pp.177-184
• /
• 2005

In this paper, we proposed a new hearing aid algorithm to improve SNR(signal to noise ratio) of noisy speech signal and speech perception. The proposed hearing aid algorithm is a multi-band loudness compensation based independent component analysis (ICA). The proposed algorithm was compared with a conventional spectral subtraction algorithm on behind-the-ear type hearing aid. The proposed algorithm successfully separated a target speech signal from background noise and from a mixture of the speech signals. The algorithms were compared each other by means of SNR. The average improvement of SNR by ICA based algorithm was 16.64dB, whereas spectral subtraction algorithm was 8.67dB. From the clinical tests, we concluded that our proposed algorithm would help hearing aid user to hear clearly a target speech in noisy conditions.

• Journal of Biomedical Engineering Research
• /
• v.16 no.4
• /
• pp.517-524
• /
• 1995

This paper is a study on the design of the cascade adaptive filter (CAF) for baseline wandering elimination in order to enhance the performance of the detection of ST segments in ECG. The CAF using Least Mean Square (LMS) algorithm consists of two filters. The primary adaptive filter which has the cutoff frequency of 0.3Hz eliminates the baseline wandering in raw ECG The secondary adaptive filter removes the remnant baseline wandering which is not eliminated by the primary adaptive filter. The performance of the CAF was compared with the standard filter, the recursive filter, and the adaptive impulse correlated filter (AICF). As a result, the CAF showed a lower signal distortion than the standard filter and the AICF. Also, the CAF showed a better perf'ormance in noise elimination than the standard filter and the recursive filter. In conclusion, considering the characteristics of the noise elimination and the signal distortion, the CAF shows a better performance in the removal of the baseline wandering than the other three Otters and suggests the high performance in the detection of ST segment.

• Journal of Biomedical Engineering Research
• /
• v.16 no.4
• /
• pp.395-402
• /
• 1995

The intravoxel spin phases in magnetic resonance imaging (MRI) usually vary due to susceptibility differences of materials to be imaged. The phase variation in the voxel results in a reduction of the signal intensity. This signal intensity reduction is known as the susceptibility effect in MRI and has been studied extensively. In this paper, a new spectral decomposition technique Is proposed and the signal change due to the susceptibility effect can be analyzed. A pulse sequence for the spectral decomposition of the susceptibility was developed and applied to susceptibility imaging of venous blood possessing paramagnetic properties. The computer simulations and their corresponding experimental results obtained using both a phantom and human volunteers are reported. Key words : susceptibility effect in MRI : spectral decomposition of susceptibility effect.

• Journal of Biomedical Engineering Research
• /
• v.16 no.4
• /
• pp.403-414
• /
• 1995

It is very difficult to quantize the ECG analysis because the decision criterion for ECG is different with each other depending on the medical specialists of the heart and there are measured detecting errors for each ECG measurement system. Therefore, we developed the real-time ECG identification system using digital fuzzy processor for STD-BUS, in order to reduce ambiguity generated in the process of ECG identification and to analyze the irregular ECG stastically to ECG's repetition interval. The variables such as AGE (months), width of QRS, average RRI, and RRI were used to classify the ECG, and were applied to ECG signal indentification system which is developed for the purpose of research. It was found that the automatic diagnosis of ECG signal was possible in the real time process which was impossible in general process of algorithm.

• Journal of Biomedical Engineering Research
• /
• v.27 no.5
• /
• pp.237-244
• /
• 2006

This study proposes an approach to the performance improvement of EMG(Electromyogram) pattern recognition. MFCC(Mel-Frequency Cepstral Coefficients)'s approach is molded after the characteristics of the human hearing organ. While it supplies the most typical feature in frequency domain, it should be reorganized to detect the features in EMG signal. And the dynamic aspects of EMG are important for a task, such as a continuous prosthetic control or various time length EMG signal recognition, which have not been successfully mastered by the most approaches. Thus, this paper proposes reorganized MFCC and HMM-GMM, which is adaptable for the dynamic features of the signal. Moreover, it requires an analysis on the most suitable system setting fur EMG pattern recognition. To meet the requirement, this study balanced the recognition-rate against the error-rates produced by the various settings when loaming based on the EMG data for each motion.

• Proceedings of the KOSOMBE Conference
• /
• v.1996 no.11
• /
• pp.118-121
• /
• 1996

This paper describes ECG signal labeling based on Fuzzy clustering, which is necessary at automated ECG diagnosis. The NPPA(Non parametric partitioning algorithm) compares the correlations of wave forms, which tends to recognize the same wave forms as different when the wave forms have a little morphological variation. We propose to apply Fuzzy clustering to ECG QRS Complex labeling, which prevents the errors to mistake by using If-then comparision. The process is divided into two parts. The first part is a parameters extraction process from ECG signal, which is composed of filtering, QRS detection by mapping to a phase space by time delay coordinates and generation of characteristic vectors. The second is fuzzy clustering by FCM(Fuzzy c-means), which is composed of a clustering, an assessment of cluster validity and labeling.