• 전력전자학회:학술대회논문집
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• 전력전자학회 2008년도 하계학술대회 논문집
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• pp.437-439
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• 2008

This paper presents the training system of myoelectric hand prosthesis controlling according to myoelectric signal generated in the human muscle. The training system consist of a trainer, a program for training. The experimental results proved the reliability of proposed training system.

• 대한전기학회논문지
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• 제41권9호
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• pp.1051-1059
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• 1992

In this paper, two general methods using time-series analysis in the functional separation of the myoelectric signal of human arm movements are developed. Autocorrelation, covariance method and sequential least squares algorithm were used to determine the model parameters and the order of signal model to describe six arm movement patterns` the forearm flexion and extension, the wrist pronation and supination, rotation-in and rotation-out. The confidence interval to classify the functions of arm movement was defined by the mean and standard deviation of total squared error. With the error signals of autoregressive(AR) model, the result showed that the highest success rate was obtained in the case of 4th order, and success rate was decreased with increase of order. Autocorrelation was the method of choice for better success rate. This technique might be applied to biomedical and rehabilitation engineering.

• 전자공학회논문지SC
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• 제42권6호
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• pp.67-76
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• 2005

본 논문에서는 근전의수용 소형 근전위 센서를 제안한다. 근전의수용 근전위 센서를 의수 소켓에 내장시키기 위해서는 소형이어야 한다. 제안된 근전위 센서는 피부와 접촉하는 전극과 신호처리를 위한 회로부가 일체화된 형태로 소형화 하였다. 기준 전극은 두 입력전극의 가운데에 나란히 배치되고, 입력전극은 막대형, 기준전극은 막대형과 원형의 두 가지 형상으로 설계하였다. 두 입력전극 사이의 간격은 근섬유의 근전위 신호의 전도속도와 중심주파수를 고려하여 18mm, 20mm, 22mm 의 세 개의 서로 다른 간격을 가진 전극을 제작하였다. 사용된 전극의 재료는 땀이나 습기에 강한 SUS440 금속을 사용하였다. 신호처리 회로부는 대역통과 필터를 갖는 차동 증폭기, 전원노이즈를 제거하기 위한 대역저지 필터, 교류결합증폭기, 절대평균값 회로로 구성되어 있다. 실험에서는 정상인의 전완에서 근전위 신호를 취득하여 주파수 분석하고, 입력전극 사이의 간격과 기준전극의 형상에 따른 출력특성 평가하였다. 본 논문에서는 실험의 결과로부터 두 입력전극간의 거리가 18mm 이면서, 입력전극의 형상과 기준전극의 형상이 모두 막대형인 표면 근전위 센서가 근전의수에 최적임을 보인다.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2003년도 하계종합학술대회 논문집 V
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• pp.2733-2736
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• 2003

This paper proposes a dry-type active surface EMG electrode for the myoelectric prosthetic hand. The designed electrode is small size for embedding in the socket of prosthetic hand, and it has three leads including the reference of signal. To acquire EMG signal rejected the power noise, a precision differential amplifier and various filters such as the band pass filter band rejection filter, low pass and high pass filter are embedded on the electrode. The final output of the electrode is integrated absolute EMG (IEMG) obtained by full rectifier and moving average circuits. From experimental results using the implemented dry-type active surface EMG electrode, the proposed electrode is feasible for the myoelectric prosthetic hand.

• 대한의용생체공학회:학술대회논문집
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• 대한의용생체공학회 1995년도 춘계학술대회
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• pp.215-220
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• 1995

In this paper, we study myoelectric signal variation through kyungrak needle stimulation. The signal are detected from two kyunrak route of arm; before and after stimulation of a needle, and before and after needle rotation. The detected signals are analyzed at frequency domain to search a characteristic parameters. At the rotation method, spectrum denity of the signals varies large but spectrum is not detected before and after rotation. We can not see any relation bet ween spectrum variation and rotational direction. As the results, when the same stimulation method is used at two different kyungrak route respectively, it is found that the variation of the myoelectric signal is not same.

• Archives of Plastic Surgery
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• 제46권4호
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• pp.303-310
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• 2019

Background Prosthetic hands with a myoelectric interface have recently received interest within the broader category of hand prostheses, but their high cost is a major barrier to use. Modern three-dimensional (3D) printing technology has enabled more widespread development and cost-effectiveness in the field of prostheses. The objective of the present study was to evaluate the clinical impact of a low-cost 3D-printed myoelectric-interface prosthetic hand on patients' daily life. Methods A prospective review of all upper-arm transradial amputation amputees who used 3D-printed myoelectric interface prostheses (Mark V) between January 2016 and August 2017 was conducted. The functional outcomes of prosthesis usage over a 3-month follow-up period were measured using a validated method (Orthotics Prosthetics User Survey-Upper Extremity Functional Status [OPUS-UEFS]). In addition, the correlation between the length of the amputated radius and changes in OPUS-UEFS scores was analyzed. Results Ten patients were included in the study. After use of the 3D-printed myoelectric single electromyography channel prosthesis for 3 months, the average OPUS-UEFS score significantly increased from 45.50 to 60.10. The Spearman correlation coefficient (r) of the correlation between radius length and OPUS-UEFS at the 3rd month of prosthetic use was 0.815. Conclusions This low-cost 3D-printed myoelectric-interface prosthetic hand with a single reliable myoelectrical signal shows the potential to positively impact amputees' quality of life through daily usage. The emergence of a low-cost 3D-printed myoelectric prosthesis could lead to new market trends, with such a device gaining popularity via reduced production costs and increased market demand.

• 전자공학회논문지B
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• 제30B권4호
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• pp.76-84
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• 1993

In this thesis, general method using autoregressive model in the functional separation of the myoelectric signal of human arm movements are suggested. Covariance method and sequential least squares algorithm were used to determine the model parameters and the order of signal model to describe six arm movement patterns` the forearm flexion and extension, the wrist pronation and supination, rotation-in and rotation out. The confidence interval to classify the functions of arm movement was defined by the mean and standard deviation of total squares error. With the error signals of autoregressive(AR) model, the result showed that the highest success, rate was abtained in the case of 4th order, and success rate was decreased with increase of order. This technique might be applied to biomedical-and rehabilitation-engi-neering.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2002년도 추계학술대회 논문집
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• pp.1070-1073
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• 2002

The biomechanical interaction between the stump and the prosthetic socket is critically important to achieve close-to-normal ambulation. Many investigators suggested that the pressure changes during gait of transfemoral amputees are closely related to the prosthetic alignment, the socket shape, the stump size, and the residual muscle activity. The effects of the prosthetic alignment, the socket shape, and the stump size on the interface pressure were investigated previously. However, there is no report how the residual muscle activities in the transfemoral stump affect the socket interface pressure characteristics during gait. Since designs of socket fur lower limb amputees need to consider the socket interface pressure characteristics, the interface pressure patterns by the residual muscle activities during gait should be investigated. In this study, myoelectric signals (MES) and socket interface pressure in residual limb of transfemoral amputees were measured during the stance and swing phases of gait. For the purpose, specially designed quadrilateral sockets that MES electrodes could be instrumented were fabricated. A total of two transfemoral amputees were participated in the experiments. The measured temporal MES amplitude and interface pressure in knee flexor (biceps femoris) and extensor (rectus femoris) had significant correlations (P ＜ 0.05). Based on the test results, It was suggested that the residual muscle activity of transfemoral amputees stump is an important factor affecting socket pressure changes during walk.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.842-847
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• 2005

This paper proposes a novel real-time EMG pattern recognition for the control of a multifunction myoelectric hand from four channel EMG signals. To cope with the nonstationary signal property of the EMG, features are extracted by wavelet packet transform. For dimensionality reduction and nonlinear mapping of the features, we also propose a linear-nonlinear feature projection composed of PCA and SOFM. The dimensionality reduction by PCA simplifies the structure of the classifier, and reduces processing time for the pattern recognition. The nonlinear mapping by SOFM transforms the PCA-reduced features to a new feature space with high class separability. Finally a multilayer neural network is employed as the pattern classifier. We implement a real-time control system for a multifunction virtual hand. From experimental results, we show that all processes, including virtual hand control, are completed within 125 msec, and the proposed method is applicable to real-time myoelectric hand control without an operation time delay.

• 대한전기학회논문지
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• 제43권6호
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• pp.1027-1035
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• 1994

This paper aims to make an artificial arm control strategy. For this, we propose a new feature extraction method and design artificial neural network for the functional classification of myoelectric signal(MES). We first transform the two channel myoelectric signals (MES) for biceps and triceps into frequency domain using fast Fourier transform (FFT). And features were obtained by comparing the magnitudes of ensemble spectrum data and used as inputs to the three-layer neural network for the learning. By changing the number of units in hidden layer of neural network we observed the improvement of classification performance. To observe the effeciency of the proposed scheme we performed experiments for classification of six arm functions to the three subjects. And we obtained on average 94[%] the ratio of classification.