• Annals of Clinical Neurophysiology
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• 제5권1호
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• pp.27-33
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• 2003

Background: Motor unit number estimation (MUNE) can directly assess motor neuron populations in muscle and quantify the degree of physiologic and/or pathologic motor neuron degeneration. A high degree of reproducibility and reliability is required from a good quantitative tool. MUNE, in various ways, is being increasingly applied clinically and statistical MUNE has several advantages over alternative techniques. Nevertheless, the optimal method of applying statistical MUNE to improve reproducibility has not been established. Methods: We performed statistical MUNE by selecting the most compensated compound muscle action potential (CMAP) area as a test area and modified the results obtained by weighted mean surface-recorded motor unit potential (SMUP). Results: MUNE measures in amyotrophic lateral sclerosis (ALS) patients showed better reproducibility with sizeweighted modification. Conclusions: We suggest size-weighted MUNE testing of "neurogenically compensated"CMAP areas present an optimal method for statistical MUNE in ALS patients.

• 한국안전학회지
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• 제17권2호
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• pp.92-99
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• 2002

Safety-related motor operated valve(MOV) safety significance for Ulchin Unit 3 was categorized. The safety evaluation of MOV of domestic nuclear power plants affects the generic data used for the quantification of MOV common cause failure(CCF) events in Ulchin Units 3&4 PSA. Therefore, in this paper, MGL(multiple greek letter)parameter ${\beta}$, used for the evaluation of MOV CCF probabilities in Ulchin Units 3&4 probabilistic safety assessment(PSA), was re-estimated and the MOV safety significance was categorized. The re-estimation results of MGL parameter show that the value of(is decreased by 30% compared with the current value used in Ulchin Unit 3&4 PSA. The categorization results of MOV safety significance using the changed value of MGL parameter(show that the number of HSSCs(high safety significant components) is decreased by 54.5% compared with those using the current value of it used in Ulchin Units 3&4 PSA.

• 전자공학회논문지SC
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• 제48권5호
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• pp.81-92
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• 2011

본 논문에서는 표면 근전도(surface electromyogram : SEMG)와 근육모델링을 이용하여 신경근육 접합부(neuromuscular junction, NMJ)의 종판(end plate) 폭(widths)과 분포(distribution)에 따른 운동단위(motor unit, MU)수를 추정하는 새로운 방법을 제안하였다. 이를 위하여 MU-시뮬레이터(motor unit simulator)와 EPZ-시뮬레이터(end plate zone simulator)를 설계하고, 본 연구에서 제안된 방법과 기존방법들을 비교하였다. 제안된 MU-시뮬레이터로 시뮬레이션 된 SMUAP(single motor unit action potential : 단일운동단위활동전위)와 CMAP(compound muscle action potential : 복합근활동전위)은 검출된 근신호와 유사하였다. EPZ-시뮬레이터는 신경근육 접합부의 종판 폭과 분포를 바꾸어 가면서 운동단위수를 추정하기 위하여 설계하였다. 실험결과 운동단위 수는 약 450 개, 근섬유수 약 340 개, 종판 폭은 약 6 mm이고, 종판분포는 불규칙하게 분포된 것 (randomly distributed)으로 추정되었다. 본 연구에서 제안된 방법은 인간 근육의 생체조직검사로 측정한 운동단위의 수와 비교 가능한 결과가 나왔다.

• 전기학회논문지
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• 제56권3호
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• pp.632-640
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• 2007

The low force estimation method of skeletal muscle was proposed by using ICA(independent component analysis) and neuro-transmission model. An EMG decomposition is the procedure by which the signal is classified into its constituent MUAP(motor unit action potential). The force index of electromyography was due to the generation of MUAP. To estimate low force, current analysis technique, such as RMS(root mean square) and MAV(mean absolute value), have not been shown to provide direct measures of the number and timing of motoneurons firing or their firing frequencies, but are used due to lack of other options. In this paper, the method based on ICA and chemical signal transmission mechanism from neuron to muscle was proposed. The force generation model consists of two linear, first-order low pass filters separated by a static non-linearity. The model takes a modulated IPI(inter pulse interval) as input and produces isometric force as output. Both the step and random train were applied to the neuro-transmission model. As a results, the ICA has shown remarkable enhancement by finding a hidden MAUP from the original superimposed EMG signal and estimating accurate IPI. And the proposed estimation technique shows good agreements with the low force measured comparing with RMS and MAV method to the input patterns.

• 대한교통학회지
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• 제32권1호
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• pp.1-12
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• 2014

도로부문의 온실가스배출량 산정시 활용되는 tier3방법론은 주행거리데이터를 기반으로 한다. 하지만 기존 대부분의 자료들은 단독으로 지역단위의 주행거리를 대변할 수 없고 지역별, 차종별, 연료별, 도로유형별 특성을 반영한 통합활동자료(주행거리데이터)가 미흡하여 온실가스배출량 산정의 신뢰도가 부족하다. 따라서 본 연구는 첫째, 지자체단위(배출지점)의 정확한 온실가스배출량을 산정할 수 있는 주행거리기반의 활동자료(통합데이터베이스) 구축과 이를 활용한 온실가스배출량 산정방법론을 제시하는 것을 목적으로 한다. 이를 위해 교통안전공단의 주행거리자료, 국토해양부의 차량등록통계, 도로교통량, 한국교통연구원의 국가교통데이터베이스, 지방자치단체 평균속도 등을 활용하였으며, 이는 교통관련 데이터의 통행패턴(유 출입교통량, 내부교통량)을 반영하여 지자체단위(배출지점)의 산정방법을 제시하였다는 점에서 의의가 있다. 둘째, 본 연구에서 제시한 방법론 검증을 위해 적용대상지를 서울시로 하였으며, 본 연구에서 제시한 모형의 검증을 위하여 기존에 발표된 세 가지 온실가스배출량 산정결과와 비교하여 적정수준임을 제시하였다.