• Title/Summary/Keyword: Beats

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The vision thresholds of nigro (Cichlasoma nigrofasciatum) on white LED light through ECG analysis (심전도 분석을 통한 백색 LED광에 대한 니그로 (Cichlasoma nigrofasciatum)의 시각역치)

  • HEO, Min-A;KIM, Min-Son;SHIN, Hyeon-Ok
    • Journal of the Korean Society of Fisheries and Ocean Technology
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    • v.52 no.1
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    • pp.42-47
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    • 2016
  • This study was conducted to investigate visual threshold of nigro (Cichlasoma nigrofasciatum) on white LED light. The visual threshold was obtained by analyzing electrocardiogram (ECG) of the nigro. 5 individuals (body weight: 15.62~45.49 g; TL: 8.9~12.4 cm) were trained for lights by an electric stimulus. And then the heart rate (beats/10s) before and after switching on the light were compared. Light intensity range was from 0.00 to 226.4 lux. Average heart rate was 10.36 beats/10s in the normal condition. When the fish perceived the light, the heart rate was decreased. Visual threshold of the fish was 2.59 lux.

Assessment of Premature Ventricular Contraction Arrhythmia by K-means Clustering Algorithm

  • Kim, Kyeong-Seop
    • Journal of the Korea Society of Computer and Information
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    • v.22 no.5
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    • pp.65-72
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    • 2017
  • Premature Ventricular Contraction(PVC) arrhythmia is most common abnormal-heart rhythm that may increase mortal risk of a cardiac patient. Thus, it is very important issue to identify the specular portraits of PVC pattern especially from the patient. In this paper, we propose a new method to extract the characteristics of PVC pattern by applying K-means machine learning algorithm on Heart Rate Variability depicted in Poinecare plot. For the quantitative analysis to distinguish the trend of cluster patterns between normal sinus rhythm and PVC beat, the Euclidean distance measure was sought between the clusters. Experimental simulations on MIT-BIH arrhythmia database draw the fact that the distance measure on the cluster is valid for differentiating the pattern-traits of PVC beats. Therefore, we proposed a method that can offer the simple remedy to identify the attributes of PVC beats in terms of K-means clusters especially in the long-period Electrocardiogram(ECG).

A Mobile System for Tinnitus Diagnostics and Therapy using Various Sound Stimuli (다양한 자극음을 이용한 모바일 이명 진단과 치료 시스템)

  • Lee, YoungRok;Park, DongGyu;Kim, HyoungWook
    • Journal of Korea Multimedia Society
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    • v.21 no.11
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    • pp.1317-1326
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    • 2018
  • A common treatment for tinnitus rehabilitation is to use a device called a sound generator to continuously supplying the sound stimuli. The devices usually provides a sound called white noise, or pink noise, which are common in nature. In this paper, we developed a mobile system for tinnitus diagnostics and therapy using Android mobile applications. The first step for tinnitus diagnostics is detecting an exact tinnitus frequency of the patients, therefore we provide a bark scale tinnitus detection algorithm for fast and accurate diagnostics. Also, the system can provide various stimuli sounds including white noise, pink noise, brown noise, nature sounds, and binaural beats. Also we provides the therapeutic functions through questionnaires to solve existing problems of the patients.

Adoption of Artificial Neural Network for Rest, Enhanced Postprocessing of Beats, and Initial Melody Processing for Automatic Composition System (자동작곡시스템에서 쉼표용 인공신경망 도입 및 개선된 박자후처리와 초기멜로디 처리)

  • Kim, Kyunghwan;Jung, Sung Hoon
    • Journal of Digital Contents Society
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    • v.17 no.6
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    • pp.449-459
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    • 2016
  • This paper proposes a new method to improve the three problems of existing automatic composition method using artificial neural networks. The first problem is that the existing beat post-processing to fit into music theories could not handle all the cases of occurring. The second one is that the pitch space generated by artificial neural networks is distorted because the rest is trained with the pitch on the same neural network with large values. The last problem is caused by the difference between the initial melody and beats given by user and those generated by an artificial neural network in the process of new composition. In order to treat these problems, we propose an enhanced post-processing of beats, initial melody processing, and adoption of artificial neural network for rest. It was found from experiments that the proposed methods totally resolved the three problems.

Comparison of rhythmic and non-rhythmic aerobic exercises on depression and balance in the elderly

  • Kwon, Il-Ho;Song, Jun-Young;Kim, Do-Ye;Son, Je-Yeong;Shim, Yu-Jin;Shin, Won-Seob
    • Physical Therapy Rehabilitation Science
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    • v.6 no.3
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    • pp.146-151
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    • 2017
  • Objective: The purpose of this study was to investigate the effects rhythmic and non-rhythmic aerobic exercises on depression and balance of healthy elderly people. Design: Randomized controled trial. Methods: Nineteen older subjects were randomly divided into 2 groups for rhythmic and non-rhythmic aerobic exercises. Both aerobic exercises consisted of functional movements such as turning in opposite directions, and running in place, the exercise consisted of movements that could activate balance. The rhythmic training group initially used music with 8 beats, and then later progressed to 16 beats. Additionally, we adjusted the pace of the music using songs from 125 beats per minute (bpm) to 160 bpm. Both groups were exercised for 50 minutes a day, twice a week, for a total of 8 weeks. We measured the condition of the patients before the intervention, and after 8 weeks of intervention. The Beck depression inventory (BDI) was used to measure the degree of depression. The Berg balance scale (BBS) was used to measure static and dynamic balance ability. We measured the subject's subjective balance confidence using the fall efficacy scale (FES). Results: Both groups showed significant improvement in BDI, BBS, and FES (p<0.05). The rhythmic aerobic exercise group showed a significant improvement only in the BBS change values compared to the non-rhythmic group (p<0.05). Conclusions: According to this study, both rhythmic and non-rhythmic aerobic exercises resulted in significant improvement in the degree of depression and balance ability of the elderly. The rhythmic aerobic exercise was more effective for dynamic balance ability.

Auto-Walking Training After Incomplete Spinal Cord Injury (불완전 척수손상 후의 자동보행훈련)

  • Jeong, Jae-Hoon
    • Physical Therapy Korea
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    • v.10 no.3
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    • pp.81-90
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    • 2003
  • This study was conducted to assess the effects of the gait training method in incomplete spinal cord injured persons using an auto-walking machine. Persons with incomplete spinal cord injury level C or D on the American Spinal Injury Association impairment scale participated for eight weeks in an auto-walking training program. The gait training program was carried out for 15 minutes, three times per day for 8 weeks with an auto-walking machine. The foot rests of the auto-walking machine can be moved forward, downward, backward and upward to make the gait pattern with fixed on crank. The patient's body weight is supported by a harness during waking training. We evaluated the gait speed, physiologic cost index, motor score of lower extremities and the WISCI (walking index for spinal cord injury) level before the training and after the forth and eighth week of walking training. 1. The mean gait speed was significantly increased from .22 m/s at pre-training to .28 m/s after 4 weeks of training and .31 m/s after 8 weeks of training (p=.004). 2. The mean physiologic cost index was decreased from 4.6 beats/min at pre-training to 3.0 beats/min after 4 weeks and 2.0 beats/min after 8 weeks of training, but it was not statistically significant (p=.140). 3. The mean motor score of lower extrernities was significantly increased from 29.8 to 35.8 after 8 weeks of training (p=.043). 4. The mean WISCI level was significantly increased from level 10 to level 19 after 8 weeks of training (p=.007). The results of this study suggest that the gait training program using the auto-walking machine increased the gait speed, muscle strength and galt pattern (WISCI level) in persons with incomplete spinal cord injury. A large, controlled study of this technique is warranted.

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Toxicity of PFCs in Embryos of the Oryzias latipes Using Flow though Exposure System (유수식 연속노출장비를 이용한 과불화화합물(PFOS, PFOA)이 송사리 (Oryzias latipes) 알의 초기발생과정에 미치는 영향 연구)

  • Cho, Jae-Gu;Kim, Kyung-Tae;Ryu, Tae-Kwon;Park, Yu-Ri;Yoon, Jun-Heon;Lee, Chul-Woo;Kim, Hyun-Mi;Choi, Kyung-Hee;Jung, Ki-Eun
    • Environmental Analysis Health and Toxicology
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    • v.25 no.2
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    • pp.145-151
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    • 2010
  • Perfluorinated chemicals (PFCs) is a kinds of persistent organic pollutants, and have the potential toxicity of which is causing great concern. In this study, we employed Oryzias latipes embryos to investigate the developmental toxicity of perfluorooctane sulfonate (PFOS) and perfluorooctanoic acid (PFOA)s compound using flowthrow system for 14 day. O. latipes embryos were exposed to solvent control, 20, 40 and 80 mg/L of PFOS and 62.5, 130, 260 mg/L of PFOA respectively. After exposure, hatchability, mortality, total length and heart beats were examined. Hatching rates were reduced approximately 27% in the 80 mg/L PFOS-treated group and 17% in the 62.5, 130 mg/L PFOA-treated groups. Heart beats in the PFOS-treated groups were reduced at 7 day but, PFOA-treated groups were increased heart beats. 80 mg/L PFOS treated group showed significant reduction in growth (total length) level to 90% of control. But PFOA did not showed significant effect on growth. In the 14 days $LC_{50}$ of PFOS and PFOA was 22.74 mg/L and 173 mg/L, respectively. The overall results indicated that the early stage of O. latipes might be a reliable model for the testing of developmental toxicity to perfluorinated chemicals.

The Kinematic Comparison of Energy Walking and Normal Walking (에너지보행과 일반보행의 운동학적 비교)

  • Shin, Je-Min;Jin, Young-Wan
    • Korean Journal of Applied Biomechanics
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    • v.16 no.4
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    • pp.61-71
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    • 2006
  • The purpose of this study was to compare kinematic characteristics on the limbs at 3 different walking speed during the energy and the normal walking. Eight subjects performed energy walking and normal walking at the slow speed(65 beats/min), the normal speed(115beats/min), the fast speed(160 beats/min). The 3-d angle was calculated by vector projected with least squares solution with three-dimensional cinematography(Motion Analysis corporation). The range of motion was calculated on the trunk, shoulder, elbow, hip, knee joint. The results showed that stride length was no difference of the two walking pattern. The duration of support phase was also no difference of the two walking pattern. The range of motion of shoulder joint significantly increased in the sagittal and frontal planes, and the range of motion of elbow joint significantly increased as the energy walking. The range of motion of hip joint had no significant difference in the any planes in changing of walking speed. But the most remarkable difference of the two walking patterns revealed at the trunk. The range of flexion/extension angle had significant increasing $2.36^{\circ}$ at normal speed, and the range of the right/left flexion angle had significant increasing below $4^{\circ}$ at the 3 walking speed, and The range of rotation angle had significant increasing $7.35^{\circ}$, $9.22^{\circ}$, respectively at the normal and slow speed. But there was no significant difference of range of motion at the hip and knee joints between energy walking and normal walking.

Classification of Normal and Abnormal QRS-complex for Home Health Management System (재택건강관리 시스템을 위한 정상 및 비정상 심전도의 분류)

  • 최안식;우응제;박승훈;윤영로
    • Journal of Biomedical Engineering Research
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    • v.25 no.2
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    • pp.129-135
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    • 2004
  • In the home health management system, we often face the situation to handle biological signals that are frequently measured from normal subjects. In such a case, it is necessary to decide whether the signal at a certain moment is normal or abnormal. Since ECC is one of the most frequently measured biological signals, we describe algorithms that detect QRS-complex and decide whether it is normal or abnormal. The developed QRS detection algorithm is a simplified version of the conventional algorithm providing enough performance for the proposed application. The developed classification algorithm that detects abnormal from mostly normal beats is based on QRS width, R-R interval and QRS shape parameter using Karhunen-Loeve transformation. The simplified QRS detector correctly detected about 99% of all beats in the MTT/BIH ECG database. The classification algorithm correctly classified about 96% of beats as normal or abnormal. The QRS detection and classification algorithm described in this paper could be used in home health management system.

Comparative Learning based Deep Learning Algorithm for Abnormal Beat Detection using Imaged Electrocardiogram Signal (비정상심박 검출을 위해 영상화된 심전도 신호를 이용한 비교학습 기반 딥러닝 알고리즘)

  • Bae, Jinkyung;Kwak, Minsoo;Noh, Kyeungkap;Lee, Dongkyu;Park, Daejin;Lee, Seungmin
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.26 no.1
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    • pp.30-40
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    • 2022
  • Electrocardiogram (ECG) signal's shape and characteristic varies through each individual, so it is difficult to classify with one neural network. It is difficult to classify the given data directly, but if corresponding normal beat is given, it is relatively easy and accurate to classify the beat by comparing two beats. In this study, we classify the ECG signal by generating the reference normal beat through the template cluster, and combining with the input ECG signal. It is possible to detect abnormal beats of various individual's records with one neural network by learning and classifying with the imaged ECG beats which are combined with corresponding reference normal beat. Especially, various neural networks, such as GoogLeNet, ResNet, and DarkNet, showed excellent performance when using the comparative learning. Also, we can confirmed that GoogLeNet has 99.72% sensitivity, which is the highest performance of the three neural networks.