• Title/Summary/Keyword: signal recognition

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Active Spinning Training System using Complex Physiological Signals (복합 생체신호를 이용한 능동형 스피닝 트레이닝 시스템)

  • Kim, Cheol-Min;Kang, Gyeong-Heon;Kim, Eun-Seok
    • The Journal of the Korea Contents Association
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    • v.15 no.7
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    • pp.591-600
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    • 2015
  • Recently high interest in health and fitness has led to vibrant researches for the active fitness system to learn and enjoy the exercise program for oneself. In this paper, we design and implement the active spinning training system which enables user to have self-learning and experience of customized spinning training program by the biometric and movement information acquired from user's physiological signals. The proposed system provides the appropriate difficulty of spinning program which reflects the concordance rate of spinning dance gestures and the amount of exercising by analyzing the physical status of participant from his brain and pulse waves and recognizing the skeletal movement in real time. For the higher exercise effect, the system offers a virtual personal trainer to show the correct poses and controls the level of difficulty depending on the concordance rate of participant's motions. The experiment with various participants through the proposed system shows that it is able to help users in getting the available exercise effect in comparatively short time.

Decoding Brain Patterns for Colored and Grayscale Images using Multivariate Pattern Analysis

  • Zafar, Raheel;Malik, Muhammad Noman;Hayat, Huma;Malik, Aamir Saeed
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.14 no.4
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    • pp.1543-1561
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    • 2020
  • Taxonomy of human brain activity is a complicated rather challenging procedure. Due to its multifaceted aspects, including experiment design, stimuli selection and presentation of images other than feature extraction and selection techniques, foster its challenging nature. Although, researchers have focused various methods to create taxonomy of human brain activity, however use of multivariate pattern analysis (MVPA) for image recognition to catalog the human brain activities is scarce. Moreover, experiment design is a complex procedure and selection of image type, color and order is challenging too. Thus, this research bridge the gap by using MVPA to create taxonomy of human brain activity for different categories of images, both colored and gray scale. In this regard, experiment is conducted through EEG testing technique, with feature extraction, selection and classification approaches to collect data from prequalified criteria of 25 graduates of University Technology PETRONAS (UTP). These participants are shown both colored and gray scale images to record accuracy and reaction time. The results showed that colored images produces better end result in terms of accuracy and response time using wavelet transform, t-test and support vector machine. This research resulted that MVPA is a better approach for the analysis of EEG data as more useful information can be extracted from the brain using colored images. This research discusses a detail behavior of human brain based on the color and gray scale images for the specific and unique task. This research contributes to further improve the decoding of human brain with increased accuracy. Besides, such experiment settings can be implemented and contribute to other areas of medical, military, business, lie detection and many others.

Content-based Music Information Retrieval using Pitch Histogram (Pitch 히스토그램을 이용한 내용기반 음악 정보 검색)

  • 박만수;박철의;김회린;강경옥
    • Journal of Broadcast Engineering
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    • v.9 no.1
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    • pp.2-7
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    • 2004
  • In this paper, we proposed the content-based music information retrieval technique using some MPEG-7 low-level descriptors. Especially, pitch information and timbral features can be applied in music genre classification, music retrieval, or QBH(Query By Humming) because these can be modeling the stochasticpattern or timbral information of music signal. In this work, we restricted the music domain as O.S.T of movie or soap opera to apply broadcasting system. That is, the user can retrievalthe information of the unknown music using only an audio clip with a few seconds extracted from video content when background music sound greeted user's ear. We proposed the audio feature set organized by MPEG-7 descriptors and distance function by vector distance or ratio computation. Thus, we observed that the feature set organized by pitch information is superior to timbral spectral feature set and IFCR(Intra-Feature Component Ratio) is better than ED(Euclidean Distance) as a vector distance function. To evaluate music recognition, k-NN is used as a classifier

A Study on Korean Phoneme Classification using Recursive Least-Square Algorithm (Recursive Least-Square 알고리즘을 이용한 한국어 음소분류에 관한 연구)

  • Kim, Hoe-Rin;Lee, Hwang-Su;Un, Jong-Gwan
    • The Journal of the Acoustical Society of Korea
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    • v.6 no.3
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    • pp.60-67
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    • 1987
  • In this paper, a phoneme classification method for Korean speech recognition has been proposed and its performance has been studied. The phoneme classification has been done based on the phonemic features extracted by the prewindowed recursive least-square (PRLS) algorithm that is a kind of adaptive filter algorithms. Applying the PRLS algorithm to input speech signal, precise detection of phoneme boundaries has been made, Reference patterns of Korean phonemes have been generated by the ordinery vector quantization (VQ) of feature vectors obtained manualy from prototype regions of each phoneme. In order to obtain the performance of the proposed phoneme classification method, the method has been tested using spoken names of seven Korean cities which have eleven different consonants and eight different vowels. In the speaker-dependent phoneme classification, the accuracy is about $85\%$ considering simple phonemic rules of Korean language, while the accuracy of the speaker-independent case is far less than that of the speaker-dependent case.

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An Analysis on Phone-Like Units for Korean Continuous Speech Recognition in Noisy Environments (잡음환경하의 연속 음성인식을 위한 유사음소단위 분석)

  • Shen Guang-Hu;Lim Soo-Ho;Seo Jun-Bae;Kim Joo-Gon;Jung Ho-Youl;Chung Hyun-Yeol
    • Proceedings of the Acoustical Society of Korea Conference
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    • autumn
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    • pp.123-126
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    • 2004
  • 본 논문은 잡음환경 하에서의 효율적인 문맥의존 음향 모델 구성에 대한 기초연구로서 잡음환경 하에서의 유사 음소단위 수에 따른 연속 음성인식 성능을 비교, 평가한 결과에 대한 보고이다. 기존의 연구[1,2]로부터 연속음성 인식의 경우 문맥종속모델은 변이음을 고려한 39유사음소를 이용한 경우가 48유사음소를 이용하는 것보다 더 좋은 인식성능을 나타냄을 알 수 있었다. 이 연구 결과를 바탕으로 본 연구에서는 잡음환경에서도 효율적인 문맥 의존 음향모델을 구성하기 위한 기초 연구를 수행하였다. 다양한 잡음환경을 고려하기 위해 White, Pink, LAB 잡음을 신호 대 잡음비(Signal to Noise Ratio) 5dB, 10dB, 15dB 레벨로 음성에 부가한 후 각 유사음소단위 수에 따른 연속음성인식 실험을 수행하였다. 그 결과, 39유사음소를 이용한 경우가 48유사음소를 이용한 경우보다 clear 환경인 경우에 약 $7\%$$17\%$ 향상된 단어인식률과 문장 인식률을 얻을 수 있었으며, 각 잡음환경에서도 39유사음소를 이용한 경우가 48유사음소를 이용한 경우보다 평균 적으로 $17\%$$28\%$ 향상된 단어인식률과 문장인식률을 얻을 수 있어 39유사음소 단위가 한국어 연속음성인식에 더 적합하고 잡음환경에서도 유효함을 확인할 수 있었다.

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System for Transmitting Army Hand Signals Using Motion Sensors (모션 센서를 이용한 군대 수신호 전송 시스템)

  • Shin, Geon;Jeon, Jaechol;Jeon, Minho;Choi, Sukwon;Kim, Iksu
    • KIPS Transactions on Computer and Communication Systems
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    • v.5 no.10
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    • pp.331-338
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    • 2016
  • In this paper, we propose a system for transmitting army hand signals using motion sensors. The proposed system consists of a squad commander device, squad member devices, and a server. The squad command device and squad member device have been implemented using a micro arduino, an accelerometer sensor, and a gyroscope sensor, and the server has been implemented using a Rasberry Pi 3. Because the devices are made in the form of band, they are lightweight and portable. The proposed system can transmit the hand signals through vibration in conditions of poor visibility. We have designed and implemented the squad member device to be able to recognize four military hand signals. Through experiments, the proposed system have shown 88.82% of correct recognition. In conclusion, we expect to increase effectiveness of army operations and survival rate of soldiers.

Processing of an Intracellular Immature Pullulanase to the Mature Form Involves Enzymatic Activation and Stabilization in Alkaliphilic Bacillus sp. S-1

  • Lee, Moon-Jo;Kang, Bong-Seok;Kim, Dong-Soo;Kim, Yong-Tae;Kim, Se-Kwon;Chung, Kang-Hyun;Kim, Jume-Ki;Nam, Kyung-Soo;Lee, Young-Choon;Kim, Cheorl-Ho
    • BMB Reports
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    • v.30 no.1
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    • pp.46-54
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    • 1997
  • Alkaliphilic Bacillus sp. S-1 secretes a large amount (approximately 80% of total pullulanase activity) of an extracellular pullulanase (PUL-E). The pullulanase exists in two forms: a precursor form (PUL-I: $M_r$ 180,000), and a processed form (PUL-E: $M_r$ 140,000). Two forms were purified to homogeneity and their properties were compared. PUL-I was different in molecular weight, isoelectric point, $NH_2$-terminal amino acid sequence, and stabilities over pH and temperature ranges. The catalytic activities of PUL-I were also distinguishable in the $K_m$ and $V_{max}$ values for various substrates, and in the specific activity for pullulan hydrolysis. PUL-E showed 10-fold higher specific activities than PUL-I. However. PUL-I is immunologically identical to PUL-E, suggesting that PUL-I is initially synthesized and proteolytically processed to the mature form of PUL-E. Processing was inhibited by PMSF, but not by pepstatin, suggesting that some intracellular serine proteases could be responsible for processing of the PUL-I. PUL-I has a different conformational structure for antibody recognition from that of PUL-E. It is also postulated that the translocation of alkaline pullulanase(AP) in the bacterium possibly requires processing of the $NH_2$-terminal region of the AP protein. Processing of the precursor involves a conformational shift. resulting in a mature form. Therefore. precursor processing not only cleaves the signal peptide, but also induces conformational shift. allowing development of active form of the enzyme.

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Multi-functional Automated Cultivation for House Melon;Development of Tele-robotic System (시설멜론용 다기능 재배생력화 시스템;원격 로봇작업 시스템 개발)

  • Im, D.H.;Kim, S.C.;Cho, S.I.;Chung, S.C.;Hwang, H.
    • Journal of Biosystems Engineering
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    • v.33 no.3
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    • pp.186-195
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    • 2008
  • In this paper, a prototype tele-operative system with a mobile base was developed in order to automate cultivation of house melon. A man-machine interactive hybrid decision-making system via tele-operative task interface was proposed to overcome limitations of computer image recognition. Identifying house melon including position data from the field image was critical to automate cultivation. And it was not simple especially when melon is covered partly by leaves and stems. The developed system was composed of 5 major modules: (a) main remote monitoring and task control module, (b) wireless remote image acquisition and data transmission module, (c) three-wheel mobile base mounted with a 4 dof articulated type robot manipulator (d) exchangeable modular type end tools, and (e) melon storage module. The system was operated through the graphic user interface using touch screen monitor and wireless data communication among operator, computer, and machine. Once task was selected from the task control and monitoring module, the analog signal of the color image of the field was captured and transmitted to the host computer using R.F. module by wireless. A sequence of algorithms to identify location and size of a melon was performed based on the local image processing. Laboratory experiment showed the developed prototype system showed the practical feasibility of automating various cultivating tasks of house melon.

Sensor-based Recognition of Human's Hand Motion for Control of a Robotic Hand (로봇 핸드 제어를 위한 센서 기반 손 동작 인식)

  • Hwang, Myun Joong
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.15 no.9
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    • pp.5440-5445
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    • 2014
  • Many studies have examined robot control using human bio signals but complicated signal processing and expensive hardware are necessary. This study proposes a method to recognize a human's hand motion using a low-cost EMG sensor and Flex sensor. The method to classify movement of the hand and finger is determined from the change in output voltage measured through MCU. The analog reference voltage is determined to be 3.3V to increase the resolution of movement identification through experiment. The robotic hand is designed to realize the identified movement. The hand has four fingers and a wrist that are controlled using pneumatic cylinders and a DC servo motor, respectively. The results show that the proposed simple method can realize human hand motion in a remote environment using the fabricated robotic hand.

A Non-invasive Real-time Respiratory Organ Motion Tracking System for Image Guided Radio-Therapy (IGRT를 위한 비침습적인 호흡에 의한 장기 움직임 실시간 추적시스템)

  • Kim, Yoon-Jong;Yoon, Uei-Joong
    • Journal of Biomedical Engineering Research
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    • v.28 no.5
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    • pp.676-683
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    • 2007
  • A non-invasive respiratory gated radiotherapy system like those based on external anatomic motion gives better comfortableness to patients than invasive system on treatment. However, higher correlation between the external and internal anatomic motion is required to increase the effectiveness of non-invasive respiratory gated radiotherapy. Both of invasive and non-invasive methods need to track the internal anatomy with the higher precision and rapid response. Especially, the non-invasive method has more difficulty to track the target position successively because of using only image processing. So we developed the system to track the motion for a non-invasive respiratory gated system to accurately find the dynamic position of internal structures such as the diaphragm and tumor. The respiratory organ motion tracking apparatus consists of an image capture board, a fluoroscopy system and a processing computer. After the image board grabs the motion of internal anatomy through the fluoroscopy system, the computer acquires the organ motion tracking data by image processing without any additional physical markers. The patients breathe freely without any forced breath control and coaching, when this experiment was performed. The developed pattern-recognition software could extract the target motion signal in real-time from the acquired fluoroscopic images. The range of mean deviations between the real and acquired target positions was measured for some sample structures in an anatomical model phantom. The mean and max deviation between the real and acquired positions were less than 1mm and 2mm respectively with the standardized movement using a moving stage and an anatomical model phantom. Under the real human body, the mean and maximum distance of the peak to trough was measured 23.5mm and 55.1mm respectively for 13 patients' diaphragm motion. The acquired respiration profile showed that human expiration period was longer than the inspiration period. The above results could be applied to respiratory-gated radiotherapy.