• Title/Summary/Keyword: Signal Compression

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Verification of Effectiveness of Wearing Compression Pants in Wearable Robot Based on Bio-signals (생체신호에 기반한 웨어러블 로봇 내 부분 압박 바지 착용 시 효과 검증)

  • Park, Soyoung;Lee, Yejin
    • Journal of the Korean Society of Clothing and Textiles
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    • v.45 no.2
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    • pp.305-316
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    • 2021
  • In this study, the effect of wearing functional compression pants is verified using a lower-limb wearable robot through a bio-signal analysis and subjective fit evaluation. First, the compression area to be applied to the functional compression pants is derived using the quad method for nine men in their 20s. Subsequently, functional compression pants are prepared, and changes in Electroencephalogram (EEG) and Electrocardiogram (ECG) signals when wearing the functional compression and normal regular pants inside a wearable robot are measured. The EEG and ECG signals are measured with eyes closed and open. Results indicate that the Relative alpha (RA) and Relative gamma wave (RG) of the EEG signal differ significantly, resulting in increased stability and reduced anxiety and stress when wearing the functional compression pants. Furthermore, the ECG analysis results indicate statistically significant differences in the Low frequency (LF)/High frequency (HF) index, which reflect the overall balance of the autonomic nervous system and can be interpreted as feeling comfortable and balanced when wearing the functional compression pants. Moreover, subjective sense is discovered to be effective in assessing wear fit, ease of movement, skin friction, and wear comfort when wearing the functional compression pants.

Communication-Power Overhead Reduction Method Using Template-Based Linear Approximation in Lightweight ECG Measurement Embedded Device (경량화된 심전도 측정 임베디드 장비에서 템플릿 기반 직선근사화를 이용한 통신오버헤드 감소 기법)

  • Lee, Seungmin;Park, Kil-Houm;Park, Daejin
    • IEMEK Journal of Embedded Systems and Applications
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    • v.15 no.5
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    • pp.205-214
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    • 2020
  • With the recent development of hardware and software technology, interest in the development of wearable devices is increasing. In particular, wearable devices require algorithms suitable for low-power and low-capacity embedded devices. Among them, there is an increasing demand for a signal compression algorithm that reduces communication overhead, in order to increase the efficiency of storage and transmission of electrocardiogram (ECG) signals requiring long-time measurement. Because normal beats occupy most of the signal with similar shapes, a high rate of signal compression is possible if normal beats are represented by a template. In this paper, we propose an algorithm for determining the normal beat template using the template cluster and Pearson similarity. Also, the template is expressed effectively as a few vertices through linear approximation algorithm. In experiment of Datum 234 of MIT-BIH arrhythmia database (MIT-BIH ADB) provided by Physionet, a compression ratio was 33.44:1, and an average distribution of root mean square error (RMSE) was 1.55%.

Electrocardiogram Signal Compression with Reconstruction via Radial Basis Function Interpolation Based on the Vertex

  • Ryu, Chunha;Kim, Tae-Hun;Kim, Jungjoon;Choi, Byung-Jae;Park, Kil-Houm
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.13 no.1
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    • pp.31-38
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    • 2013
  • Patients with heart disease need long-term monitoring of the electrocardiogram (ECG) signal using a portable electrocardiograph. This trend requires the miniaturization of data storage and faster transmission to medical doctors for diagnosis. The ECG signal needs to be utilized for efficient storage, processing and transmission, and its data must contain the important components for diagnosis, such as the P wave, QRS-complex, and T wave. In this study, we select the vertex which has a larger curvature value than the threshold value for compression. Then, we reconstruct the compressed signal using by radial basis function interpolation. This technique guarantees a lower percentage of root mean square difference with respect to the extracted sample points and preserves all the important features of the ECG signal. Its effectiveness has been demonstrated in the experiment using the Massachusetts Institute of Technology and Boston's Beth Israel Hospital arrhythmia database.

Near Lossless Medical Image Compression using Wavelet Transform (웨이블릿변환을 이용한 무손실에 가까운 의료영상압축)

  • Yoon, Ki-Byung;Ahn, Chang-Beom
    • Proceedings of the KOSOMBE Conference
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    • v.1995 no.11
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    • pp.113-116
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    • 1995
  • Medical image compression using the wavelet transform has been tried. Due to the flexibility in representing nonstationary image signal in both time and frequency domains and its ability to adapt human visual characteristics, wavelet transform has unique advantage in images compression. In the proposed wavelet compression original image is decomposed into multi-scale bands. Different scale factors are employed in the quantization of wavelet decomposed images in different bands. For the lowest band, a predictor is designed and error signal is entropy coded. For high scale bands, runlength coding for toro run is used with Huffman coding. From simulation with magnetic resonance images($256\times256$ size, 256 graylevels) the proposed algorithm is superior to the JPEG by more than 2.5 dB in near lossless compression (CR = 8 - 10).

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Performance Evaluation of ECG Compression Algorithms using Classification of Signals based PQSRT Wave Features (PQRST파 특징 기반 신호의 분류를 이용한 심전도 압축 알고리즘 성능 평가)

  • Koo, Jung-Joo;Choi, Goang-Seog
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.37 no.4C
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    • pp.313-320
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    • 2012
  • An ECG(Electrocardiogram) compression can increase the processing speed of system as well as reduce amount of signal transmission and data storage of long-term records. Whereas conventional performance evaluations of loss or lossless compression algorithms measure PRD(Percent RMS Difference) and CR(Compression Ratio) in the viewpoint of engineers, this paper focused on the performance evaluations of compression algorithms in the viewpoint of diagnostician who diagnosis ECG. Generally, for not effecting the diagnosis in the ECG compression, the position, length, amplitude and waveform of the restored signal of PQRST wave should not be damaged. AZTEC, a typical ECG compression algorithm, is validated its effectiveness in conventional performance evaluation. In this paper, we propose novel performance evaluation of AZTEC in the viewpoint of diagnostician.

A Color Image Watermarking Method for Embedding Audio Signal

  • Kim Sang Jin;Kim Chung Hwa
    • Proceedings of the IEEK Conference
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    • 2004.08c
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    • pp.631-635
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    • 2004
  • The rapid development of digital media and communication network urgently brings about the need of data certification technology to protect IPR (Intellectual property right). This paper proposed a new watermarking method for embedding contents owner's audio signal in order to protect color image IPR. Since this method evolves the existing static model and embeds audio signal of big data, it has the advantage of restoring signal transformed due to attacks. Three basic stages of watermarking include: 1) Encode analogue ID owner's audio signal using PCM and create new 3D audio watermark; 2) Interleave 3D audio watermark by linear bit expansion and 3) Transform Y signal of color image into wavelet and embed interleaved audio watermark in the low frequency band on the transform domain. The results demonstrated that the audio signal embedding in color image proposed in this paper enhanced robustness against lossy JPEG compression, standard image compression and image cropping and rotation which remove a part of image.

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HEARING AND HOWLING SUPPRESSION BY ADAPTIVE FEEDBACK CANCELLATION WITH FREQUENCY COMPRESSION

  • Harry Alfonso L. Joson;futoshi Asano;Yoiti Suzuki;Toshio Sone
    • Proceedings of the Acoustical Society of Korea Conference
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    • 1994.06a
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    • pp.919-924
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    • 1994
  • The use of adaptive feedback cancellation to prevent howling requires a reference signal that is correlated with the feedback signal by is not correlated with the input signal. Such a signal is hard to obtain in hearing aids. In this paper, the use fo frequency compression to decorrelate the output signal with input signal for use as reference is presented. Performance evaluation results indicate that with the proper choice of system parameters, the use of this system can provide a significant increase in howling margin with minimal deterioration in output signal quality.

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Determination of the Optimum-Bandwidth of Chirp-Signal for Pulse Compression Technique (펄스압축 기술을 위한 chirp 신호의 최적대역폭 결정)

  • Ko, Dae-Sik;Moon, Gun
    • The Journal of the Acoustical Society of Korea
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    • v.16 no.2
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    • pp.5-9
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    • 1997
  • In this paper, when we use the chirp signal as input signal of ultrasonic signal system the technique for determining the bandwidth of the chirp signal that maximizes the amplitude of the compressed ultrasonic echo signal has been studied. In ultrasonic signal processing systems, the signal-to-noise ratio of the echo signal can be too low due to damping and scattering of the ultrasonic wave during transmission. Method of pulse compression using chirp signal is a means to increase the signal-to-noise ratio in ultrasonic pulse-echo systems. Simulation and experimental results showed that the output signal of ultrasonic system was increased by pulse width of chirp signal and the optimum-bandwidth of the chirp signal was 1.15 times larger than the bandwidth of the ultrasonic system.

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EEG data compression using subband coding techniques (대역 분할 부호화 기법을 이용한 EEG 데이타 압축)

  • Lee, Jong-Ug;Huh, Jae-Man;Kim, Taek-Soo;Park, Sang-Hui
    • Proceedings of the KIEE Conference
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    • 1993.11a
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    • pp.338-341
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    • 1993
  • A EEG(ElectroEncephaloGram) compression scheme based on subband coding techniques is presented in this paper. Considering the frequency characteristics of EEG, the raw signal was decomposed into different frequency bands. After decomposition, optimal bit allocation was done by adapting to the standard deviation in each frequency bands, and decomposed signals were quantized using pdf(probability density function)-optimized nonuniform quantizer. Based on the above mentioned coding scheme, coding results of various multichannel EEG signal were shown with compression ratio and SNR(signal-to-noise ratio).

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