• Journal of Biomedical Engineering Research
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• v.15 no.3
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• pp.281-288
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• 1994

In this paper, a new decomposition method of the interference EMG signal using MAMDF filtering and digital signal processor. The efficient software and hardware signal processing techniques are employed. The MAMDF filter is employed in order to estimate the presence and likely location of the respective templates which may include in the observed mixture, and high-resolution waveform alignment is employed in order to provide the optimal combination set and time delays of the selected templates. The TMS320C25 digital signal processor chip is employed in order to execute the intensive calculation part of the software. The method is verified through a simulation with real templates which are obtain ed from needle EMG. As a result, the proposed method provides an overall speed improvement of 32-40 times.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.05a
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• pp.285-288
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• 2008

In ubiquitous computing environment the biological signal ECG (Electrocardiogram signal) is usually recorded with noise components. Adaptive interference (or noise) canceller do adaptive filtering of the noise reference input to maximally match and subtract out noise or interference from the primary (signal plus noise) input thereby adaptively eliminate unwanted interference from the ECG signal. Measured Stress ECG (or exercise ECG signal) signal have three major noisy component like baseline wander noise, motion artifact noise and EMG (Electro-mayo-cardiogram) noise. These noises are not only distorted signal but also root of incorrect diagnosis while ECG data are analyzed. Motion artifact and EMG noises behave like wide band spectrum signals, and they considerably do overlapping with the ECG spectrum. Here the multidimensional adaptive method used for filtering which is more effective to improve signal to noise ratio.

• Proceedings of the KOSOMBE Conference
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• v.1997 no.11
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• pp.55-58
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• 1997

In this paper, we study a signal processing method which extracts each MUAP(motor unit action potential) from EMG(Electromyogram) interference pattern or clinical diagnostic purposes. First of all, differential digital filtering is selected or eliminating the spike components of the MUAP's from the background noise. And, the algorithm identifies the spikes over the certanin threshold by template matching in frequency domain. After missing or false firing actor is cut off at the IPI(inter pulse interval) histogram, we averages the MUAP waveforms from the raw signal using the identified spikes as triggers, and Finally, measures their amplitudes, durations, and numbers of phases. Specially, We introduce algorithm performed by template matching in the frequency domain. A typical 3-s signal recorded from the biceps brachii muscle using a conventional needle electrode during a isometric contraction is used. Finally, the method decomposed five simultaneous active MUAP's from original EMG signal.

• Proceedings of the KOSOMBE Conference
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• v.1993 no.11
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• pp.145-150
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• 1993

It is an important component of the diagnosis to research the morphological changes of EMG in pathological conditions. In order to provide an EMG signal resulting from a predetermined neuromuscular pathophysiology, we have initially developed a mathmatical model of electromyographic interference pattern(IP). It can be used to study the variation of the IP resulting from morphological and electrophysiological changes occurring in disease states, because the model computes the IP from the underlying fiber and muscle structure. We performed quantative analysis or the model output, focusing on IPs resulting from simulations of dystrophic fiber loss and the MU denervation and reinnervation typical of neuropathies. To discribe the characteristics of IPs associated with these pathologies, a set of frequency domain discriptors, activity, mobility, and complexity were used, as well as several measures of the spectral density function. These discriptors demonstrate distinct patterns of variation corresponding to morphological changes observed in disease states, and closely with results obtained from the classical method, turn/amp technique.

• Journal of Biomedical Engineering Research
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• v.32 no.1
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• pp.45-54
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• 2011

Cuff electrodes have a benefit for chronic electroneurogram(ENG) recording while minimizing nerve damage. However, the ENG signals are usually contaminated by electromyogram(EMG) activity from the surrounding muscle, the thermal noise generated within the source resistance, and the electric noise generated primarily at the first stage of the amplifier. This paper proposes a new cuff electrode to reduce the interference of EMG signals. An additional middle electrode was placed at the center of cuff electrode. As a result, the proposed cuff electrode achieved a higher signal-to-interference ratio compared to the conventional tripolar cuff. The cuff electrode was then assembled together with closure, headstage, and hermetic case including electronic circuits. This paper also presents a lownoise amplifier system to improve signal-to-noise ratio. The circuit was designed based on the noise analysis to minimize the electronic noise. The result shows that the total noise of the amplifier was below $1{\mu}V_{rms}$ for a cuff impedance of $1\;k{\Omega}$ and the common-mode rejection ratio was 115 dB at 1 kHz. In the current study, the performance of nerve cuff electrode system was evaluated by monitoring afferent nerve signals under mechanical stimuli in a rat animal model.