• Journal of Biomedical Engineering Research
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• v.16 no.3
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• pp.317-324
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• 1995

A need exists for the accurate identification of time series models having time varying parameters, as is important in the case of real time identification of nonstationary EMG signal. Thls paper describes real time identification and muscle fatigue monitoring method of nonstationary EMG signal. The method is composed of the efficient identifier which estimates the autoregressive parameters of nonstationary EMG signal model, and its real time implementation by using T805 parallel processing computer. The method is verified through experiment with real EMG signals which are obtained from surface electrode. As a result, the proposed method provides a new approach for real time Implementation of muscle fatigue monitoring and the execution time is 0.894ms/sample for 1024Hz EMG signal.

• Proceedings of the KOSOMBE Conference
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• v.1994 no.12
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• pp.113-116
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• 1994

Estimation of the evoked potential using the iterated bispectrum and cross-correlation (IBC) has been tried for both simulation and real clinical data. Conventional time average (TA) method suffers from synchronization error when the latency time of the evoked potential is random, which results in poor SNR distortion in the estimation of EP waveform. Instead of EP signal average in time domain, bispectrum is used which is insensitive to time delay. The EP signal is recovered by the inverse transform of the Fourier amplitude and phase obtained from the bispectrum. The distribution of the latency time is calculated using cross-correlation between EP signal estimated by the bispectrum and the acquired signal. For the simulation. EEG noise was added to the known EP signal and the EP signal was estimated by both the conventional technique and bispectrum technique. The proposed bispectrum technique estimates EP signal more accurately than the conventional technique with respect to the maximum amplitude of a signal, full width at half maximum(FWHM). signal-to-noise-ratio, and the position of maximum peak. When applied to the real visual evoked potential(VEP) signal. bispectrum technique was able to estimate EP signal more distinctively. The distribution of the latency time may play an important role in medical diagonosis.

• Journal of Biomedical Engineering Research
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• v.17 no.3
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• pp.319-326
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• 1996

Clinical myography(EMG) is a technique for diagnosing neuromuscular disorders by analyzing the electrical signal that can be records by needle electrode during a muscular contraction. The EMG signal arises from electrical discharges that accompany the generation of force by groups of muscular fiber, and the analysis of EMG signal provides symptoms that can distinguish disorder of mLecle from disor- ders of nerve. One of the methods for analysis of EMG signal is to separate the individual discharge-the motor unit action potentials(MVAPS) - from EMG signal. But we can only observe the EMG signal that is a superimposed version of time delayed MUAPS. To obtain the information about MUAP(, i.e., position, firing number, magnitude etc), first of all, a method that can separate each MUAP from the EMG signal must be developed Although the methods for MUAP separation have been proposed by many researcherl they have required heavy computational burden. In this paper, we proposed a new method that has less computational burden and performs more reliable separation of superimposed EMG signal using wavelet filter which has multiresolution analysis as major property. As a result, we develope the separation algorithm of superimposed EMG signal which has less computational burden than any other researchers and exacutes exact separation process. The performance of this method has been discussed in the automatic resolving procedure which is neccessary to identify every firing of every motor unit from the EMG pattern.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.16 no.4
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• pp.197-202
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• 2016

In this paper, a danger signal to tell caregivers when a dangerous situation occurs, the bio-signal analysis in infants to prevent sudden infant death sudden infant death propose a monitoring system. The Sudden infant death (SID) refers to a healthy baby is unexplained deaths between birth year in the month. Sudden infant death proposed monitoring system is composed of a processor unit and the monitoring and alarm part for processing part and the biological signal sensing biological signals. Using the PPG sensor to sense the bio-signal and the processor unit the signal obtained through the sensor by removing the motion artifact was able to alarm and monitoring the parent.The proposed system will send the alarm to monitoring and alerting caregivers if the risk situation by analyzing the heart rate of the infant. With the actual implementation of the system to evaluate the performance of the monitoring system.

• Molecules and Cells
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• v.43 no.6
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• pp.581-589
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• 2020

Neurons have multiple dendrites and single axon. This neuronal polarity is gradually established during early processes of neuronal differentiation: generation of multiple neurites (stages 1-2); differentiation (stage 3) and maturation (stages 4-5) of an axon and dendrites. In this study, we demonstrated that the neuron-specific n-glycosylated protein NELL2 is important for neuronal polarization and axon growth using cultured rat embryonic hippocampal neurons. Endogenous NELL2 expression was gradually increased in parallel with the progression of developmental stages of hippocampal neurons, and overexpression of NELL2 stimulated neuronal polarization and axon growth. In line with these results, knockdown of NELL2 expression resulted in deterioration of neuronal development, including inhibition of neuronal development progression, decreased axon growth and increased axon branching. Inhibitor against extracellular signal-regulated kinase (ERK) dramatically inhibited NELL2-induced progression of neuronal development and axon growth. These results suggest that NELL2 is an important regulator for the morphological development for neuronal polarization and axon growth.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.9
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• pp.3559-3571
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• 2015

This paper addresses the problem of signal acquisition with a sparse representation in a given orthonormal basis using fewer noisy measurements. The authors formulate the problem statement for randomly measuring with strong signal noise. The impact of white Gaussian signals noise on the recovery performance is analyzed to provide a theoretical basis for the reasonable design of the measurement matrix. With the idea that the measurement matrix can be adapted for noise suppression in the adaptive CS system, an adapted selective compressive sensing (ASCS) scheme is proposed whose measurement matrix can be updated according to the noise information fed back by the processing center. In terms of objective recovery quality, failure rate and mean-square error (MSE), a comparison is made with some nonadaptive methods and existing CS measurement approaches. Extensive numerical experiments show that the proposed scheme has better noise suppression performance and improves the support recovery of sparse signal. The proposed scheme should have a great potential and bright prospect of broadband signals such as biological signal measurement and radar signal detection.

• Journal of Biomedical Engineering Research
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• v.13 no.1
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• pp.1-8
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• 1992

In the field of prosthesis arm control, the pattern classification of the EMG signal is a required basis process and also the estimation of force from collected EMG data is another necessary duty. But unfortunately, what we've got is not real force but an EMG signal which contains the information of force. This is the reason why we estimate the force from the EMG data. In this paper, when we handle the EMG signal to estimate the force, spatial prewhitening process is applied from which the spatial correlation between the channels are removed. And after the orthogonal transformation which is used in the force estimation process, the transformed signal Is inputed into the probabilistic model for pattern classification. To verify the different results of the multiple channels, SNR(signal to noise ratio) function is introduced.

• Proceedings of the KOSOMBE Conference
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• v.1989 no.05
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• pp.19-22
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• 1989

This paper represents a syntactic peak detection algorithm which detects peaks in the ECG signal. In the algorithm, the input waveform is linearly approximated by "split-and-merge" method, and then each line segment is symbolized with primitive set. The peeks in the symbolized input waveform are recognized by the finite-state automata, which the deterministic finite-state language is parsed by. This proposed algorithm correctly detects peaks in a normal ECG signal as well as in the abnormal ECG signal such as tachycardia and the contaminated signal with noise.

• Proceedings of the KOSOMBE Conference
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• v.1998 no.11
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• pp.115-116
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• 1998

Pulse echo techniques have been used for the conventional medical ultrasound imaging systems. However, their resolution is limited in the transmitted signal power. To overcome this limit, pulse compression method used in the radar systems was proposed. This system transmits a continuous coded signal and then compresses the received signal into the short and high resolution pulse by using correlator. The reflectors can be detected by cross-correlation between the transmitted signal and the received signal with the depth information. In this paper, we will present a comparative study of the performances of the most common sequences(pseudo-chirp, m-sequences, modified Golay code). The best result for improving resolution is obtained with the modified Golay Code.

• Proceedings of the KOSOMBE Conference
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• v.1995 no.05
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• pp.183-185
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• 1995

We present a visual programming system for signal analysis; it allows the user to construct signal processing algorithms by assembling visually fundamental signal processing blocks, and to observe the processed signals as well as the original signals in detail by magnifying a portion and measuring the time interval and amplitude between two points. Each fundamental signal processing block is implemented as an independent dynamically linked library module. Therefore, the user can expand the system processing capability by simply adding dynamically linked library modules without restructuring the entire system.