• 전자공학회논문지B
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• 제28B권7호
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• pp.590-598
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• 1991

This paper represents a syntactic peak detection algorithm which detects peak in the ECG signal.

• 한국감성과학회:학술대회논문집
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• 한국감성과학회 2001년도 추계학술대회 논문집
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• pp.104-111
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• 2001

정서와 생리반응 (자율신경계 반응) 간의 관계에 관하여 성인을 대상으로 최근가지 많은 연구가 행해져 왔다. 본 연구에서는 동일한 실험참여자를 대상으로 일정 기간 동안 여러 회의 반복실험을 통해 정서(기쁨, 슬픔, 분노, 공포, 혐오)에 따른 자율신경계의 반응의 일관성과 정서별 자율신경계 반응 패턴을 규명하고자 하였다. 본 실험에 앞서 저서를 유발하기 우한 도구인 정서유발자극세트와 정서에 대한 심리반응을 평가하기 위한 정서평가척도가 제작되었다. 정서유발자극세트는 2-4분 정도의 각 정서 장면이 포함된 총 5개의 동영상 장면들이다. 예비실험을 통해 70％ 이상의 적합성 및 효과성을 가진 4개의 세트를 추출하여 본 실험에 사용하였다. 본 실험은 남녀 대학생 12명을 대상으로 4회 반복해서 실시되었다. 실험참여자들은 각 정서 장면을 시청 후, 유발된 정서에 대한 심리적인 평가를 하였다. 측정한 자율신경계 생리반응 변수는 ECG, PPG, EDA, SKT이었다. 연구 결과, 심리반응에서 정서유발자극세트는 75％ 이상의 적합성 및 효과성을 보였다. 생리반응(ECG, EDA) 분석 결과, 정서에 따른 자율신경계 반응은 회기별로 일관적이었으며, 각 정서별로 특정적인 생리반응 패턴을 가지는 것으로 나타났다.

• 대한의용생체공학회:의공학회지
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• 제12권2호
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• pp.131-138
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• 1991

This paper describes an algorithm of pattern analysis of ECG signals by significant points extraction method. The significant points can be extracted by modified zerocrossing method, which method determines the real significant point among the significant point candidates by zerocrossing method and slope rate of left side and right side. This modified zerocrossing method improves the accuracy of detection of real slgnficant polnt Position. This Paper also describes the pattern matching algorithm by a hierarchical AND/OR graph of ECG signals. The decomposition of ECG signals by a hierarchical AND/ OR graph can make the pattern matching process easy and fast, Furthermore the pattern matching to the significant points reduces the processing time of ECG analysis.

• 대한의용생체공학회:학술대회논문집
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• 대한의용생체공학회 1991년도 추계학술대회
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• pp.129-132
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• 1991

This paper describes the ECG pattern recognition using the syntatic pattern recognition algorithm. The algorithm uses the BNF rule wi th the semantic evaluation which has the structural Information of the ECG. This algorithm is constructed with (1) removing the baseline drift by the Cubic spline function and exract the significant point by the line-approximation algorithm, (2) syntatic peak recognition algorithm with the extracted significant point, (3) produce the token which is used pattern recognition, (4) pattern recognition of the ECG by the syntatic pattern recognition algorithm, (5) extract the parameter with the pattern recognized ECG signal.

• 전자공학회논문지B
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• 제30B권6호
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• pp.67-75
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• 1993

ECG pattern was classified using a back-propagation neural network. An improved feature extractor of ECG is proposed for better classification capability. It is consisted of preprocessing ECG signal by an FIR filter faster than conventional one by a factor of 5. QRS complex recognition by moving-window integration, and peak extraction by quadratic approximation. Since the FIR filter had a periodic frequency spectrum, only one-fifth of usual processing time was required. Also, segmentation of ECG signal followed by quadratic approximation of each segment enabled accurate detection of both P and T waves. When improtant features were extracted and fed into back-propagation neural network for pattern classification, the required number of nodes in hidden and input layers was reduced compared to using raw data as an input, also reducing the necessary time for study. Accurate pattern classification was possible by an appropriate feature selection.

• 한국의류산업학회지
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• 제10권5호
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• pp.676-682
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• 2008

In this study a guideline of the 3D-fit pattern for the ECG(electrocardiogram) measurement of elderly's u-healthcare clothes was proposed. In the screening test of the ECG measurement band, ECG peak band was observable at the band pressure of 0.20 kPa. By employing a 3D body image, tight-fit 3D patterns were made at two different reduction rates of 21%(pattern 1) and 33%(pattern 2), and corresponding pressure of both of the clothes were 0.25 kPa and 0.54 kPa, respectively. Typical waves of ECG were found in both stationary and moving position. In terms of the subjective evaluation of the u-healthcare clothes when worn, it was confirmed that reduction pattern 1(0.25 kPa) conveyed comfortable clothing pressure and pleasantness, which is very close to the result of screening test of ECG band experiment. As results, it is recommended that reduction rate should be adjusted, so that clothing pressure is about 0.2 kPa for the elderly's comfortable and efficient u-healthcare clothes.

• 한국의류학회지
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• 제36권11호
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• pp.1174-1185
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• 2012

This study develops tight-fitting upper clothing to measure electrocardiography (ECG) data. Taking into consideration the elasticity of the clothing, we made 4 experimental clothes by applying to each a weft reduction rate of 40%, 50%, 60%, and 70%. The 4 experimental clothes were used to measure resting ECG, exercise ECG, and post-exercise ECG for 4 men in their 20s. We compared clothing pressures using sensors on the human body and on a dressform. Subjective wear sensations of the 4 experimental clothes were evaluated using a subjective 7-point scale (with 7 being most excellent). We measured clothing pressures by using the air type pressure (AMI 3037-2) for upper and lower chest sensors in the developed tight-fitting upper clothing. The lower chest sensor showed that the clothing pressure on a human body and dressform changed consistently as the weft reduction rate decreased. The upper chest sensor showed inconsistent changes in clothing pressure as the weft reduction rate decreased. The wearing-test result for preliminary subjects showed that the lower chest sensor was more stable than the upper chest sensor; therefore, we inserted the sensor at the lower chest position before performing ECG. Except for Subject 4, the resting ECGs were stably measured for 3 subjects (Subject 1, Subject 2, and Subject 3) in all the developed clothes (A clothing, B clothing, C clothing, and D clothing). However, D clothing showed stable ECG values after exercise. The results of the experiment showed that we could measure ECG without difficulty using clothes with a weft reduction rate of 40% when the movement was not intense; however, tight-fitting upper clothing with a weft reduction rate of 70% was necessary to measure exercise ECG and post-exercise ECG values.

• 대한의용생체공학회:학술대회논문집
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• 대한의용생체공학회 1991년도 춘계학술대회
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• pp.51-55
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• 1991

This paper describes an algorithm of pattern analysis of ECG signals by significant points extraction method. The significant points can be extracted by modified zerocrossing method, which method determines the real significant point among the significant point candidates by zerocrossing method and slope rate of left side and right side. This modified zerocrossing method improves the accuracy of detection of real significant point position. This paper also describes the pattern matching algorithm by a hierarchical AND/OR graph of ECG signals. The decomposition of ECG signals by a hierarchical AND/OR graph can make the pattern matching process easy and fast. Furthermore the pattern matching to the significant points reduces the processing time of ECG analysis.

• 대한전기학회논문지
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• 제41권4호
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• pp.433-441
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• 1992

This paper describes an algorithm that can efficiently analyze the ECG signal using frame knowledge representation technique. Input to the analysis process is a set of significant points which have been extracted from an original sampled signal(lead II) by the syntactic peak recognition algorithm. The hierarchical property of ECG signal is represented by hierarchical AND/OR graph. The semantic information and constraints of the ECG signal are desctibed by frame. As the control mechanism for labeling points, the search mechanism with the mixed paradigms of data-driven and model driven hypothesis formation, scoring function, hypothesis modification network and instance inheritance are used. We used the CSE database in order to evaluate the performance of the proposed algorithm.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1990년도 한국자동제어학술회의논문집(국내학술편); KOEX, Seoul; 26-27 Oct. 1990
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• pp.575-579
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• 1990

This paper describes an algorithm that can efficiently analyze the multichannel ECG signal using the frame. The input is a set of significant features (points) which have been extracted from an original sampled signal by using the split-and-merge algorithm. A signal from each channel can be hierarchical ADN/OR graph on the basis of the priori knowledge for ECG signal. The search mechanisms with some heuristics and the mixed paradigms of data-driven hypothesis formation are used as the major control mechanisms. The mutual relations among features are also considered by evaluating a score based on the relational spectrum. For recognition of morphologies corresponding to OR nodes, an hypothesis modification strategy is used. Other techniques such as instance, priority update of prototypes, and template matching facility are also used. This algorithm exactly recognized the primary points and supporting points from the multichannel ECG signals.