• Title/Summary/Keyword: Correlated Signals

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Characteristics of Initiation and Termination of Muscle Contraction in Early Hemiparetic Wrists: Analysis of Median Frequency (초기 편마비 환자에서 손목 근수축 개시 및 종료의 특성: 중앙주파수 분석)

  • Chung, Yi-Jung;Cho, Sang-Hyun;Kwon, Oh-Yun;Lee, Young-Hee
    • Physical Therapy Korea
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    • v.13 no.1
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    • pp.38-46
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    • 2006
  • The purposes of this study were to investigate the median frequency (MDF) between initiation and termination of muscle contraction through surface electromyographic (sEMG) analysis and to propose the basis of clinical treatment for movement problems in early hemiparetic upper limbs. Thirteen patients who had stroke with onset less than 3 months prior to the study and seven control subjects participated in the study. The median frequency in initiation and termination of muscle contraction was recorded from wrist flexor and extensor muscles using the sEMG, with 3 second beeper signals, during maximal isometric wrist flexion and extension. Flexion and extension must be done as quickly and forcefully as possible. The results of the study were as follows: 1. The MDF of the onset and offset sections were significantly lower on the paretic than the nonparetic and control sides. 2. The MDF of the offset section significantly decreased on the paretic and nonparetic sides. Consequently, this study showed that the lowering of the MDF was due to the hemiparetic wrist motor impairment and muscle weakness. These results are also related to Fugl-Meyer motor assessment (FMA) scores in hemiparetic upper limbs. This study also suggests that since muscle weakness of early stroke patients affects the functional decrease of upper limbs, further studies must focus on the treatment to improve muscle agility and muscle fiber recruitment efficiency that can induce the functional recovery correlated to motor control.

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Predictive model of fatigue crack detection in thick bridge steel structures with piezoelectric wafer active sensors

  • Gresil, M.;Yu, L.;Shen, Y.;Giurgiutiu, V.
    • Smart Structures and Systems
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    • v.12 no.2
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    • pp.97-119
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    • 2013
  • This paper presents numerical and experimental results on the use of guided waves for structural health monitoring (SHM) of crack growth during a fatigue test in a thick steel plate used for civil engineering application. Numerical simulation, analytical modeling, and experimental tests are used to prove that piezoelectric wafer active sensor (PWAS) can perform active SHM using guided wave pitch-catch method and passive SHM using acoustic emission (AE). AE simulation was performed with the multi-physic FEM (MP-FEM) approach. The MP-FEM approach permits that the output variables to be expressed directly in electric terms while the two-ways electromechanical conversion is done internally in the MP-FEM formulation. The AE event was simulated as a pulse of defined duration and amplitude. The electrical signal measured at a PWAS receiver was simulated. Experimental tests were performed with PWAS transducers acting as passive receivers of AE signals. An AE source was simulated using 0.5-mm pencil lead breaks. The PWAS transducers were able to pick up AE signal with good strength. Subsequently, PWAS transducers and traditional AE transducer were applied to a 12.7-mm CT specimen subjected to accelerated fatigue testing. Active sensing in pitch catch mode on the CT specimen was applied between the PWAS transducers pairs. Damage indexes were calculated and correlated with actual crack growth. The paper finishes with conclusions and suggestions for further work.

A Neural Network and Kalman Filter Hybrid Approach for GPS/INS Integration

  • Wang, Jianguo Jack;Wang, Jinling;Sinclair, David;Watts, Leo
    • Proceedings of the Korean Institute of Navigation and Port Research Conference
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    • v.1
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    • pp.277-282
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    • 2006
  • It is well known that Kalman filtering is an optimal real-time data fusion method for GPS/INS integration. However, it has some limitations in terms of stability, adaptability and observability. A Kalman filter can perform optimally only when its dynamic model is correctly defined and the noise statistics for the measurement and process are completely known. It is found that estimated Kalman filter states could be influenced by several factors, including vehicle dynamic variations, filter tuning results, and environment changes, etc., which are difficult to model. Neural networks can map input-output relationships without apriori knowledge about them; hence a proper designed neural network is capable of learning and extracting these complex relationships with enough training. This paper presents a GPS/INS integrated system that combines Kalman filtering and neural network algorithms to improve navigation solutions during GPS outages. An Extended Kalman filter estimates INS measurement errors, plus position, velocity and attitude errors etc. Kalman filter states, and gives precise navigation solutions while GPS signals are available. At the same time, a multi-layer neural network is trained to map the vehicle dynamics with corresponding Kalman filter states, at the same rate of measurement update. After the output of the neural network meets a similarity threshold, it can be used to correct INS measurements when no GPS measurements are available. Selecting suitable inputs and outputs of the neural network is critical for this hybrid method. Detailed analysis unveils that some Kalman filter states are highly correlated with vehicle dynamic variations. The filter states that heavily impact system navigation solutions are selected as the neural network outputs. The principle of this hybrid method and the neural network design are presented. Field test data are processed to evaluate the performance of the proposed method.

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Augmented reality and dynamic infrared thermography for perforator mapping in the anterolateral thigh

  • Cifuentes, Ignacio Javier;Dagnino, Bruno Leonardo;Salisbury, Maria Carolina;Perez, Maria Eliana;Ortega, Claudia;Maldonado, Daniela
    • Archives of Plastic Surgery
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    • v.45 no.3
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    • pp.284-288
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    • 2018
  • Dynamic infrared thermography (DIRT) has been used for the preoperative mapping of cutaneous perforators. This technique has shown a positive correlation with intraoperative findings. Our aim was to evaluate the accuracy of perforator mapping with DIRT and augmented reality using a portable projector. For this purpose, three volunteers had both of their anterolateral thighs assessed for the presence and location of cutaneous perforators using DIRT. The obtained image of these "hotspots" was projected back onto the thigh and the presence of Doppler signals within a 10-cm diameter from the midpoint between the lateral patella and the anterior superior iliac spine was assessed using a handheld Doppler device. Hotspots were identified in all six anterolateral thighs and were successfully projected onto the skin. The median number of perforators identified within the area of interest was 5 (range, 3-8) and the median time needed to identify them was 3.5 minutes (range, 3.3-4.0 minutes). Every hotspot was correlated to a Doppler sound signal. In conclusion, augmented reality can be a reliable method for transferring the location of perforators identified by DIRT onto the thigh, facilitating its assessment and yielding a reliable map of potential perforators for flap raising.

Effects of Dangkwisoo-San, Ginger and Curcumin on Transient Receptor Potential Melastatin 7 Channels (당귀수산, 생강, 커큐민의 대사성 질환과 관련된 일과성 수용체 전압 이온통로조절에 관한 연구)

  • Kim, Byung Joo
    • Journal of Korean Medicine for Obesity Research
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    • v.18 no.1
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    • pp.10-18
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    • 2018
  • Objectives: Metabolic syndrome is correlated with increased cardiovascular risk and characterized by several factors, including visceral obesity, hypertension, insulin resistance, and dyslipidemia. Several members of a large family of nonselective cation entry channels, e.g., transient receptor potential (TRP) melastatin 7 (TRPM7) channels have been associated with the development of cardiovascular diseases. The purpose of this study was to investigate the effects of Dangkwisoo-san, ginger and curcumin on TRPM7 channel. Methods: Human embryonic kidney (HEK) 293 cells stably transfected with the TRPM7 expression vectors were maintained in Dulbecco's modified Eagle's medium (DMEM) supplemented with 10% fetal bovine serum (FBS), 1% penicillin/streptomycin, $5{\mu}g/mL$ blasticidin, and 0.4 mg/mL zeocin in a humidified 20% $O_2$/10% $CO_2$ atmosphere at $37^{\circ}C$. Whole-cell patch clamp recordings were obtained using an Axopatch 700B amplifier and pClamp v.10.4 software, and signals were digitalized at 5 kHz using Digidata 1422A. Results: Dangkwisoo-san extract (100, 200, 300, 400, and $500{\mu}g/mL$) inhibited the outward and inward TRPM7 whole-cell currents at dose dependent manner and the half maximal inhibitory concentration $(IC)_{50}$ of Dangkwisoo-san was $218.3{\mu}g/mL$. Also, ginger extract (100, 200, 300, 400, and $500{\mu}g/mL$) inhibited the outward and inward of TRPM7 whole-cell currents in a dose dependent manner and the $IC_{50}$ of ginger was $877.2{\mu}g/mL$. However, curcumin had no effects on TRPM7 whole-cell currents. Conclusions: These results suggest that both Dangkwisoo-san and ginger have good roles to inhibit the TRPM7 channel, suggesting that Dangkwisoo-san and ginger are considered one of the candidate agents for the treatment of metabolic syndrome such as cardiovascular disease.

Kernel Regression Model based Gas Turbine Rotor Vibration Signal Abnormal State Analysis (커널회귀 모델기반 가스터빈 축진동 신호이상 분석)

  • Kim, Yeonwhan;Kim, Donghwan;Park, SunHwi
    • KEPCO Journal on Electric Power and Energy
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    • v.4 no.2
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    • pp.101-105
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    • 2018
  • In this paper, the kernel regression model is applied for the case study of gas turbine abnormal state analysis. In addition to vibration analysis at the remote site, the kernel regression model technique can is useful for analyzing abnormal state of rotor vibration signals of gas turbine in power plant. In monitoring based on data-driven techniques correlated measurements, the fault free training data of shaft vibration obtained during normal operations of gas turbine are used to develop a empirical model based on auto-associative kernel regression. This data-driven model can be used to predict virtual measurements, which are compared with real-time data, generating residuals. Any faults in the system may cause statistically abnormal changes in these residuals and could be detected. As the result, the kernel regression model provides information that can distinguish anomalies such as sensor failure in a shaft vibration signal.

Ionospheric Responses to the Earthquake in the Gulf of Alaska and the Kusatsu-Shiranesan Volcanic Eruption on 23 January 2018

  • Shahbazi, Anahita;Park, Jihye
    • Journal of Positioning, Navigation, and Timing
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    • v.11 no.4
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    • pp.305-316
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    • 2022
  • Numerous research revealed a strong association between the ionospheric perturbations and various natural hazards. The ionospheric measurements from Global Navigation Satellite System (GNSS) observations provide the state of electron contents in the ionosphere that contributes to investigate the source events. In this study, two geophysical events occurred on 23 January 2018, the 7.9 Mw earthquake in Alaska and Kusatsu-Shiranesan volcanic eruption in Japan, are examined to characterize the fingerprint of each event in the ionosphere. Firstly, we extracted the Total Electron Content (TEC) from GNSS measurements, then isolated disturbed wave signatures from the TEC measurements that is referred to as a traveling ionospheric disturbance (TID). As TIDs are short-term ionospheric variations, the major trend of GNSS TEC measurements should be properly removed. We applied a natural neighbor interpolation method together with a leave-one-out cross validation technique for detrending. After detrending the TEC, the remaining signals are further enhanced by applying a band-pass filter and TIDs are detected from them. Finally, the detected TIDs are verified as the response of the ionosphere to Kusatsu-Shiranesan volcanic eruption and Gulf of Alaska earthquake which propagated through the ionosphere with an average velocity of 530 m/s and 724 m/s, respectively. In addition, a coherence analysis is conducted to discriminate between the signatures from a volcanic explosion and an earthquake. The analysis reveals the TID waveforms from each single event are highly correlated, while a low correlation is found between the TIDs from the earthquake and explosion. This study supports the claim that different geophysical events induce the distinctive characteristics of TIDs that are detectable by the ionospheric measurements of GNSS.

Evaluation of Setting Time in Cement Paste with Fly Ash Replacement Using Piezoelectric Sensors (압전센서를 이용한 플라이애시 치환 시멘트 페이스트의 응결 시점 평가)

  • Jun-Cheol Lee;Tae-Yong Go;Chang-Yong Yi
    • Journal of the Korean Recycled Construction Resources Institute
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    • v.12 no.2
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    • pp.162-168
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    • 2024
  • This study investigated the setting characteristics of cement paste with varying proportions of fly ash replacement using the electro-mechanical impedance (EMI) sensing technique. Cement paste samples were prepared with a water-to-binder ratio of 40 %, substituting fly ash for 10 %, 20 %, and 30 % of the cement weight. Piezoelectric (PZT) sensors were embedded in the center of each cement paste sample to continuously monitor the EMI signals. Vicat needle test and semi-adiabatic calorimetry test were conducted to validate the reliability of the EMI sensing technique in monitoring the setting of cement paste. Experimental results revealed notable changes in the magnitude and resonant frequency of the EMI resonant peaks during the setting time. It was confirmed that the setting times measured through the EMI sensing technique were correlated with those determined by the Vicat needle test and semi-adiabatic calorimetry test.

Effects of vowel types and sentence positions in standard passage on auditory and cepstral and spectral measures in patients with voice disorders (모음 유형과 표준문단의 문장 위치가 음성장애 환자의 청지각적 및 켑스트럼 및 스펙트럼 분석에 미치는 효과)

  • Mi-Hyeon Choi;Seong Hee Choi
    • Phonetics and Speech Sciences
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    • v.15 no.4
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    • pp.81-90
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    • 2023
  • Auditory perceptual assessment and acoustic analysis are commonly used in clinical practice for voice evaluation. This study aims to explore the effects of speech task context on auditory perceptual assessment and acoustic measures in patients with voice disorders. Sustained vowel phonations (/a/, /e/, /i/, /o/, /u/, /ɯ/, /ʌ/) and connected speech (a standardized paragraph 'kaeul' and nine sub-sentences) were obtained from a total of 22 patients with voice disorders. GRBAS ('G', 'R', 'B', 'A', 'S') and CAPE-V ('OS', 'R', 'B', 'S', 'P', 'L') auditory-perceptual assessment were evaluated by two certified speech language pathologists specializing in voice disorders using blind and random voice samples. Additionally, spectral and cepstral measures were analyzed using the analysis of dysphonia in speech and voice model (ADSV).When assessing voice quality with the GRBAS scale, it was not significantly affected by the vowel type except for 'B', while the 'OS', 'R' and 'B' in CAPE-V were affected by the vowel type (p<.05). In addition, measurements of CPP and L/H ratio were influenced by vowel types and sentence positions. CPP values in the standard paragraph showed significant negative correlations with all vowels, with the highest correlation observed for /e/ vowel (r=-.739). The CPP of the second sentence had the strongest correlation with all vowels. Depending on the speech stimulus, CAPE-V may have a greater impact on auditory-perceptual assessment than GRBAS, vowel types and sentence position with consonants influenced the 'B' scale, CPP, and L/H ratio. When using vowels in the voice assessment of patients with voice disorders, it would be beneficial to use not only /a/, but also the vowel /i/, which is acoustically highly correlated with 'breathy'. In addition, the /e/ vowel was highly correlated acoustically with the standardized passage and sub-sentences. Furthermore, given that most dysphonic signals are aperiodic, 2nd sentence of the 'kaeul' passage, which is the most acoustically correlated with all vowels, can be used with CPP. These results provide clinical evidence of the impact of speech tasks on auditory perceptual and acoustic measures, which may help to provide guidelines for voice evaluation in patients with voice disorders.

Prediction of the Following BCI Performance by Means of Spectral EEG Characteristics in the Prior Resting State (뇌신호 주파수 특성을 이용한 CNN 기반 BCI 성능 예측)

  • Kang, Jae-Hwan;Kim, Sung-Hee;Youn, Joosang;Kim, Junsuk
    • KIPS Transactions on Computer and Communication Systems
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    • v.9 no.11
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    • pp.265-272
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    • 2020
  • In the research of brain computer interface (BCI) technology, one of the big problems encountered is how to deal with some people as called the BCI-illiteracy group who could not control the BCI system. To approach this problem efficiently, we investigated a kind of spectral EEG characteristics in the prior resting state in association with BCI performance in the following BCI tasks. First, spectral powers of EEG signals in the resting state with both eyes-open and eyes-closed conditions were respectively extracted. Second, a convolution neural network (CNN) based binary classifier discriminated the binary motor imagery intention in the BCI task. Both the linear correlation and binary prediction methods confirmed that the spectral EEG characteristics in the prior resting state were highly related to the BCI performance in the following BCI task. Linear regression analysis demonstrated that the relative ratio of the 13 Hz below and above the spectral power in the resting state with only eyes-open, not eyes-closed condition, were significantly correlated with the quantified metrics of the BCI performance (r=0.544). A binary classifier based on the linear regression with L1 regularization method was able to discriminate the high-performance group and low-performance group in the following BCI task by using the spectral-based EEG features in the precedent resting state (AUC=0.817). These results strongly support that the spectral EEG characteristics in the frontal regions during the resting state with eyes-open condition should be used as a good predictor of the following BCI task performance.