• Journal of IKEEE
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• v.13 no.1
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• pp.77-86
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• 2009

A wavelet Electrocardiogram(ECG) detector and its analog-to-digital converter(ADC) for low-power implantable cardiac pacemakers are presented in this paper. The proposed wavelet-based ECG detector consists of a wavelet decomposer with wavelet filter banks, a QRS complex detector of hypothesis testing with wavelet-demodulated ECG signals, and a noise detector with zero-crossing points. To achieve high-detection performance with low-power consumption, the multi-scaled product algorithm and soft-threshold algorithm are efficiently exploited. To further reduce the power dissipation, a low-power ADC, which is based on a Successive Approximation Register(SAR) architecture with an on/off-time controlled comparator and passive sample and hold, is also presented. Our algorithmic and architectural level approaches are implemented and fabricated in standard $0.35{\mu}m$ CMOS technology. The testchip shows a good detection accuracy of 99.32% and very low-power consumption of $19.02{\mu}W$ with 3-V supply voltage.

• Speech Sciences
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• v.10 no.4
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• pp.117-124
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• 2003

Speaker recognition is the technology that confirms the identification of speaker by using the characteristic of speech. Such technique is classified into speaker identification and speaker verification: The first method discriminates the speaker from the preregistered group and recognize the word, the second verifies the speaker who claims the identification. This method that extracts the information of speaker from the speech and confirms the individual identification becomes one of the most efficient technology as the service via telephone network is popularized. Some problems, however, must be solved for the real application as follows; The first thing is concerning that the safe method is necessary to reject the imposter because the recognition is not performed for the only preregistered customer. The second thing is about the fact that the characteristic of speech is changed as time goes by, So this fact causes the severe degradation of recognition rate and the inconvenience of users as the number of times to utter the text increases. The last thing is relating to the fact that the common characteristic among speakers causes the wrong recognition result. The silence parts being included the center of speech cause that identification rate is decreased. In this paper, to make improvement, We proposed identification rate can be improved by removing silence part before processing identification algorithm. The methods detecting speech area are zero crossing rate, energy of signal detect end point and starting point of the speech and process DTW algorithm by using two methods in this paper. As a result, the proposed method is obtained about 3% of improved recognition rate compare with the conventional methods.

• The Journal of the Acoustical Society of Korea
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• v.14 no.3
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• pp.61-70
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• 1995

In this paper, the PLP cepstrum which is close to human perceptual characteristics was extracted through the spread time area to get the temperal feature. Phonemes were recognized by artificial neural network similar to the learning method of human. The phoneme strings were matched by Markov models which well suited for sequence. Phoneme recognition for the continuous Korean speech had been done using speech blocks in which speech frames were gathered with unequal numbers. We parameterized the blocks using 7th order PLPs, PTP, zero crossing rate and energy, which neural network used as inputs. The 100 data composed of 10 Korean sentences which were taken from the speech two men pronounced five times for each sentence were used for the the recognition. As a result, maximum recognition rate of 94.4% was obtained. The sentence was recognized using Markov models generated by the phoneme strings recognized from earlier results the recognition for the 200 data which two men sounded 10 times for each sentence had been carried out. The sentence recognition rate of 92.5% was obtained.

• Journal of Biomedical Engineering Research
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• v.28 no.4
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• pp.556-568
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• 2007

Unsatisfied results of return of spontaneous circulation (ROSC) estimates were caused by the fact that the predictability of the predictors was insufficient. This unmet estimate of the predictors may be affected by transitional events due to behaviors which occur during cardiopulmonary resuscitation (CPR). We thus hypothesized that the discrepancy of ROSC estimates found in statistical characteristics due to transitional CPR events, may affect the performance of the predictors, and that the performance of the classifier dichotomizing between ROSC and No-ROSC might be different during CPR. In a canine model (n=18) of prolonged ventricular fibrillation (VF), standard CPR was provided with administration of two doses of epinephrine 0 min or 3 min later of the onset of CPR. For the analysis of the likelihood of a successful defibrillation during CPR, Support Vector Classification was adopted to evaluate statistical peculiarity combining time and frequency based predictors: median frequency, frequency band-limited power spectrum, mean segment amplitude, and zero crossing rates. The worst predictable period showed below about 1 min after the onset of CPR, and the best predictable period could be observed from about 1.5 min later of the administering epinephrine through 2.0-2.2 min. As hypothesized, the discrepancy of statistical characteristics of the predictors was reflected in the differences of the classification performance during CPR. These results represent a major improvement in defibrillation prediction can be achieved by a specific timing of the analysis, as a change in CPR transition.

• Journal of the Optical Society of Korea
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• v.15 no.3
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• pp.293-299
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• 2011

In this study, we demonstrated Fourier-domain/swept-source optical coherence tomography (FD/SS-OCT) at a center wavelength of 800 nm for in vivo human retinal imaging. A wavelength-swept source was constructed with a semiconductor optical amplifier, a fiber Fabry-Perot tunable filter, isolators, and a fiber coupler in a ring cavity. Our swept source produced a laser output with a tuning range of 42 nm (779 to 821 nm) and an average power of 3.9 mW. The wavelength-swept speed in this configuration with bidirectionality is 2,000 axial scans per second. In addition, we suggested a modified zero-crossing method to achieve equal sample spacing in the wavenumber (k) domain and to increase the image depth range. FD/SS-OCT has a sensitivity of ~89.7 dB and an axial resolution of 10.4 ${\mu}m$ in air. When a retinal image with 2,000 A-lines/frame is obtained, an acquisition speed of 2.0 fps is achieved.

• Journal of the Institute of Convergence Signal Processing
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• v.9 no.2
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• pp.121-128
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• 2008

Accurate voice activity detection have a great impact on performance of speech applications including speech recognition, speech coding, and speech communication. In this paper, we propose methods for voice activity detection that can adapt to various car noise situations during driving. Existing voice activity detection used various method such as time energy, frequency energy, zero crossing rate, and spectral entropy that have a weak point of rapid. decline performance in noisy environments. In this paper, the approach is based on existing spectral entropy for VAD that we propose voice activity detection method using MFB(Met-frequency filter banks) spectral entropy, gradient FFT(Fast Fourier Transform) spectral entropy. and gradient MFB spectral entropy. FFT multiplied by Mel-scale is MFB and Mel-scale is non linear scale when human sound perception reflects characteristic of speech. Proposed MFB spectral entropy method clearly improve the ability to discriminate between speech and non-speech for various in noisy car environments that achieves 93.21% accuracy as a result of experiments. Compared to the spectral entropy method, the proposed voice activity detection gives an average improvement in the correct detection rate of more than 3.2%.

• Journal of IKEEE
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• v.5 no.2 s.9
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• pp.190-200
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• 2001

This paper is addressed to welding defect feature vector selection and implementation method of welding defect classifier using fuzzy techniques. We compare IAV, zero-crossing number as time domain analysis, power spectrum coefficient as frequency domain, histogram as both domain for welding defect feature selection. We choose histogram as feature vector by graph analysis and find out that maximum frequent occurrence number and section of corresponding signal scale in relative histogram show obvious difference between normal welding and voiding with penetration depth defect. We implement a fuzzy welding defect classifier using these feature vector, test it to verify its effectiveness for 695 welding data frame which consist of 4000 sampled data. As result of test, correct classification rate is 92.96%. Lab experimental results show a effectiveness of fuzzy welding defect classifier using relative histogram for practical Laser welding monitoring system in industry.

• Journal of Internet Computing and Services
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• v.2 no.1
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• pp.31-38
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• 2001

Speech database built of phonemes is significant in the studies of speech recognition, speech synthesis and analysis, Phoneme, consist of voiced sounds and unvoiced ones, Though there are many feature differences in voiced and unvoiced sounds, the traditional algorithms for detecting the boundary between phonemes do not reflect on them and determine the boundary between phonemes by comparing parameters of current frame with those of previous frame in time domain, In this paper, we propose the assort algorithm, which is based on a block and reflecting upon the feature differences between voiced and unvoiced sounds for phoneme segmentation, The assort algorithm uses the distance measure based upon MFCC(Mel-Frequency Cepstrum Coefficient) as a comparing spectrum measure, and uses the energy, zero crossing rate, spectral energy ratio, the formant frequency to separate voiced sounds from unvoiced sounds, N, the result of out experiment, the proposed system showed about 79 percents precision subject to the 3 or 4 syllables isolated words, and improved about 8 percents in the precision over the existing phonemes segmentation system.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.18 no.2
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• pp.218-230
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• 1993

A power line modem(PLM) which transfers data safely through power lines in houses or small offices is considered. When a power line is used for communications, transmitted signals could be affected by the channel characteristics such as frequency-selective fading, interference, and time-varying attenuation. In order to overcome these impairments, a direct sequence(DS) technique which is well known as an effective instrument against a variety of interferences and hostile channel properties is employed. Using a DS technique, however, requires more circuits such as PN code generator circuits, code modification circuits, and complicated synchronization circuits, and it also results in substantial acquisition delay. In this paper, some of these circuits are implemented via software programmed in the system controller, and the complicated synchronization circuits are replaced by simple circuits utilizing a 60 Hz power signal for synchronization. The synchronization ciruits used in this paper virtually eliminate the substantial acquisition delay, and is also designed to free influence of 60 Hz zero crossing jitters which reside in a power signal. As a result, a PLM using a DS technique is realized in the form of wall-socket plug, and the PLM hardware would be very much simplified.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.18 no.1
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• pp.129-136
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• 2004

In this paper, we proposed quad variable rates ADPCM coding method for efficient speech transmission and real time porcessing is implemented on TMS320C6711-DSP. The modified ADPCM with four variable coding rates, 16[kbps], 24[kbps], 32[kbps] and 40[kbps] are used for speech window samples for good quality speech transmission at a small data bits and real time encoding and decoding is implemented using DSP. ZCR is used to identify the influence of the noise on the speech signal and to decide the rate change threshold. For noise superior signals, low coding rates are applied to minimize data bit and for noise inferior signals, high coding rates are applied to enhance the speech quality. In most speech telecommunications, silent period takes more than half of the signals, speech quality close to 40[kbps] can be obtained at comparabley low data bits and this is shown by simulation and experiments. TMS320C6711-DSK board has 128K flash memory and performance of 1333MIPS and has meets the requirements for real time implementation of proposed coding algorithm.