scholarly journals Biomimetic Sonar for Electrical Activation of the Auditory Pathway

2017 ◽  
Vol 2017 ◽  
pp. 1-10 ◽  
Author(s):  
D. Menniti ◽  
S. A. Pullano ◽  
M. G. Bianco ◽  
R. Citraro ◽  
E. Russo ◽  
...  
Keyword(s):  
Spatial Information ◽  
Electronic Device ◽  
Principal Component ◽  
Auditory Pathway ◽  
Brain Response ◽  
Implanted Electrodes ◽  
System A ◽  
Signal Features ◽  
New Perspective ◽  
Rate Frequency

Relying on the mechanism of bat’s echolocation system, a bioinspired electronic device has been developed to investigate the cortical activity of mammals in response to auditory sensorial stimuli. By means of implanted electrodes, acoustical information about the external environment generated by a biomimetic system and converted in electrical signals was delivered to anatomically selected structures of the auditory pathway. Electrocorticographic recordings showed that cerebral activity response is highly dependent on the information carried out by ultrasounds and is frequency-locked with the signal repetition rate. Frequency analysis reveals that delta and beta rhythm content increases, suggesting that sensorial information is successfully transferred and integrated. In addition, principal component analysis highlights how all the stimuli generate patterns of neural activity which can be clearly classified. The results show that brain response is modulated by echo signal features suggesting that spatial information sent by biomimetic sonar is efficiently interpreted and encoded by the auditory system. Consequently, these results give new perspective in artificial environmental perception, which could be used for developing new techniques useful in treating pathological conditions or influencing our perception of the surroundings.

scholarly journals A Historical Perspective of Cardiac Implantable Electronic Device Infection: How a Menace Can Drive Technological and Clinical Improvement

Hearts ◽  
2021 ◽  
Vol 2 (2) ◽  
pp. 202-212
Author(s):  
Giulia Massaro ◽  
Igor Diemberger ◽  
Matteo Ziacchi ◽  
Andrea Angeletti ◽  
Giovanni Statuto ◽  
...  
Keyword(s):  
Electronic Device ◽  
Positive Impact ◽  
Delayed Diagnosis ◽  
Implantation Rate ◽  
Major Complication ◽  
Lead Extraction ◽  
Cardiac Implantable Electronic Devices ◽  
Device Infection ◽  
New Perspective ◽  
Poor Outcomes

In recent decades there has been a relevant increase in the implantation rate of cardiac implantable electronic devices (CIEDs), albeit with relevant geographical inhomogeneities. Despite the positive impact on clinical outcomes, the possibility of major complications is not negligible, particularly with respect to CIED infections. CIED infections significantly affect morbidity and mortality, especially in instances of delayed diagnosis and appropriate treatment. In the present review, we will start to depict the factors underlying the development of CIED infection as well as the difficulties related to its diagnosis and treatment. We will explain the reasons underlying the need to focus on prophylaxis rather than treatment, in view of the poor outcomes despite improvements in lead extraction procedures. This will lead to the consideration of management of this complication in a hub-spoke manner, and to our analysis of the several technological and procedural improvements developed to minimize this complication. These include prolongation of CIED longevity, the development of leadless devices, and integrated prophylactic approaches. We will conclude with a discussion regarding new devices and strategies under development. This complete excursus will provide the reader with a new perspective on how a major complication can drive technological improvements.

scholarly journals Patch-Based Principal Component Analysis for Face Recognition

2017 ◽  
Vol 2017 ◽  
pp. 1-9 ◽  
Author(s):  
Tai-Xiang Jiang ◽  
Ting-Zhu Huang ◽  
Xi-Le Zhao ◽  
Tian-Hui Ma
Keyword(s):  
Principal Component Analysis ◽  
Face Recognition ◽  
Nearest Neighbor ◽  
Spatial Information ◽  
Principal Component ◽  
Component Analysis ◽  
Two Dimensional ◽  
Face Images ◽  
Pca Method ◽  
Local Spatial Information

We have proposed a patch-based principal component analysis (PCA) method to deal with face recognition. Many PCA-based methods for face recognition utilize the correlation between pixels, columns, or rows. But the local spatial information is not utilized or not fully utilized in these methods. We believe that patches are more meaningful basic units for face recognition than pixels, columns, or rows, since faces are discerned by patches containing eyes and noses. To calculate the correlation between patches, face images are divided into patches and then these patches are converted to column vectors which would be combined into a new “image matrix.” By replacing the images with the new “image matrix” in the two-dimensional PCA framework, we directly calculate the correlation of the divided patches by computing the total scatter. By optimizing the total scatter of the projected samples, we obtain the projection matrix for feature extraction. Finally, we use the nearest neighbor classifier. Extensive experiments on the ORL and FERET face database are reported to illustrate the performance of the patch-based PCA. Our method promotes the accuracy compared to one-dimensional PCA, two-dimensional PCA, and two-directional two-dimensional PCA.

scholarly journals Principal component analysis implementation for brainwave signal reduction based on cognitive activity

2017 ◽  
Vol 3 (3) ◽  
pp. 125 ◽  
Author(s):  
Ahmad Azhari ◽  
Murein Miksa Mardhia
Keyword(s):  
Principal Component Analysis ◽  
Cognitive Task ◽  
Cognitive Activity ◽  
Electrical Potential ◽  
Principal Component ◽  
Component Analysis ◽  
Wave Form ◽  
Brain Response ◽  
Cumulative Rate ◽  
Main Component

Human has the ability to think that comes from the brain. Electrical signals generated by brain and represented in wave form.  To record and measure the activity of brainwaves in the form of electrical potential required electroencephalogram (EEG). In this study a cognitive task is applied to trigger a specific human brain response arising from the cognitive aspect.  Stimulation is given by using nine types of cognitive tasks including breath, color, face, finger, math, object, password thinking, singing, and sports. Principal component analysis (PCA) is implemented as a first step to reduce data and to get the main component of feature extraction results obtained from EEG acquisition. The results show that PCA succeeded reducing 108 existing datasets to 2 prominent factors with a cumulative rate of 65.7%. Factor 1 (F1) includes mean, standard deviation, and entropy, while factor 2 (F2) includes skewness and kurtosis.

scholarly journals Comparison of LSS-IV and LISS-III+LISS-IV merged data for classification of crops

2014 ◽  
Vol II-8 ◽  
pp. 101-105 ◽  
Author(s):  
R. Hebbar ◽  
M. V. R. Sesha Sai
Keyword(s):  
Image Quality ◽  
Data Fusion ◽  
Classification Accuracy ◽  
Spatial Information ◽  
Principal Component ◽  
Pass Filter ◽  
Simultaneous Acquisition ◽  
Liss Iii ◽  
Image Quality Index ◽  
Selection Of

Resourcesat-1 satellite with its unique capability of simultaneous acquisition of multispectral images at different spatial resolutions (AWiFS, LISS-III and LISS-IV MX / Mono) has immense potential for crop inventory. The present study was carried for selection of suitable LISS-IV MX band for data fusion and its evaluation for delineation different crops in a multi-cropped area. Image fusion techniques namely intensity hue saturation (IHS), principal component analysis (PCA), brovey, high pass filter (HPF) and wavelet methods were used for merging LISS-III and LISS-IV Mono data. The merged products were evaluated visually and through universal image quality index, ERGAS and classification accuracy. The study revealed that red band of LISS-IV MX data was found to be optimal band for merging with LISS-III data in terms of maintaining both spectral and spatial information and thus, closely matching with multispectral LISS-IVMX data. Among the five data fusion techniques, wavelet method was found to be superior in retaining image quality and higher classification accuracy compared to commonly used methods of IHS, PCA and Brovey. The study indicated that LISS-IV data in mono mode with wider swath of 70 km could be exploited in place of 24km LISS-IVMX data by selection of appropriate fusion techniques by acquiring monochromatic data in the red band.

scholarly journals EEG and Deep Learning Based Brain Cognitive Function Classification

Computers ◽  
2020 ◽  
Vol 9 (4) ◽  
pp. 104
Author(s):  
Saraswati Sridhar ◽  
Vidya Manian
Keyword(s):  
Deep Learning ◽  
Motor Imagery ◽  
Cognitive Aging ◽  
Classification Accuracy ◽  
Short Term Memory ◽  
Principal Component ◽  
Learning System ◽  
Detection Accuracy ◽  
Band Power ◽  
Signal Features

Electroencephalogram signals are used to assess neurodegenerative diseases and develop sophisticated brain machine interfaces for rehabilitation and gaming. Most of the applications use only motor imagery or evoked potentials. Here, a deep learning network based on a sensory motor paradigm (auditory, olfactory, movement, and motor-imagery) that employs a subject-agnostic Bidirectional Long Short-Term Memory (BLSTM) Network is developed to assess cognitive functions and identify its relationship with brain signal features, which is hypothesized to consistently indicate cognitive decline. Testing occurred with healthy subjects of age 20–40, 40–60, and >60, and mildly cognitive impaired subjects. Auditory and olfactory stimuli were presented to the subjects and the subjects imagined and conducted movement of each arm during which Electroencephalogram (EEG)/Electromyogram (EMG) signals were recorded. A deep BLSTM Neural Network is trained with Principal Component features from evoked signals and assesses their corresponding pathways. Wavelet analysis is used to decompose evoked signals and calculate the band power of component frequency bands. This deep learning system performs better than conventional deep neural networks in detecting MCI. Most features studied peaked at the age range 40–60 and were lower for the MCI group than for any other group tested. Detection accuracy of left-hand motor imagery signals best indicated cognitive aging (p = 0.0012); here, the mean classification accuracy per age group declined from 91.93% to 81.64%, and is 69.53% for MCI subjects. Motor-imagery-evoked band power, particularly in gamma bands, best indicated (p = 0.007) cognitive aging. Although the classification accuracy of the potentials effectively distinguished cognitive aging from MCI (p < 0.05), followed by gamma-band power.

Acoustic Patterns of Infant Vocalizations Expressing Emotions and Communicative Functions

2002 ◽  
Vol 45 (2) ◽  
pp. 311-317 ◽  
Author(s):  
C. Papaeliou ◽  
G. Minadakis ◽  
D. Cavouras
Keyword(s):  
Classification Accuracy ◽  
Acoustic Analysis ◽  
Cooperative Interaction ◽  
First Year ◽  
Vocal Repertoire ◽  
System A ◽  
Communicative Functions ◽  
Infant Vocalizations ◽  
Signal Features ◽  
Acoustic Pattern

The present study aimed at identifying the acoustic pattern of vocalizations, produced by 7- to 11-month-old infants, that were interpreted by their mothers as expressing emotions or communicative functions. Participants were 6 healthy, first-born English infants, 3 boys and 3 girls, and their mothers. The acoustic analysis of the vocalizations was performed using a pattern recognition (PR) software system. A PR system not only calculates signal features, it also automatically detects patterns in the arrangement of such features. The following results were obtained: (a) the PR system distinguished vocalizations interpreted as emotions from vocalizations interpreted as communicative functions with an overall accuracy of 87.34%; (b) the classification accuracy of the PR system for vocalizations that convey emotions was 85.4% and for vocalizations that convey communicative functions was 89.5%; and (c) compared to vocalizations that express emotions, vocalizations that express communicative functions were shorter, displayed lower fundamental frequency values, and had greater overall intensity. These findings suggest that in the second half of the first year, infants possess a vocal repertoire that contributes to regulating cooperative interaction with their mothers, which is considered one of the major prerequisites for language acquisition.

Video Copy Detection Based on Principal Component Analysis

2014 ◽  
Vol 548-549 ◽  
pp. 693-697
Author(s):  
Yan Yan Hou
Keyword(s):  
Principal Component Analysis ◽  
Spatial Information ◽  
False Positive Rate ◽  
Principal Component ◽  
Component Analysis ◽  
Video Copy Detection ◽  
Copy Detection ◽  
Key Frame ◽  
Detection Algorithms ◽  
Positive Rate

Content-based video hashing was proposed for the purpose of video copy detection. Conventional video copy detection algorithms apply image hashing algorithm to either every frame or key frame which is sensitive to video variation. In our proposed algorithm, key frames including temporal and spatial information are used to video copy detection, Discrete cosine transform (DCT) is done for video key frame and feature vector is extracted by principal component analysis ( PCA ). An average true positive rate of 99.31% and false positive rate of 0.37% demonstrate the robustness and uniqueness of the proposed algorithm. Experiments indicate that it is easy to implement and more efficient than other video copy detection algorithms.

Effects of L-Baclofen and D-Baclofen on the Auditory System: A Study of Click-Evoked Potentials from the Inferior Colliculus in the Rat

1995 ◽  
Vol 104 (5) ◽  
pp. 399-404 ◽  
Author(s):  
William S. Szczepaniak ◽  
Aage R. Møller
Keyword(s):  
Inferior Colliculus ◽  
Cochlear Nucleus ◽  
Auditory Pathway ◽  
Detectable Effect ◽  
Potential Treatment ◽  
Racemic Form ◽  
System A ◽  
Auditory Disorders ◽  
Severe Tinnitus ◽  
Second Peak

The drug baclofen is a potential treatment for severe tinnitus, but its action in relieving tinnitus is not known. Baclofen is available as an approved drug only in racemic form with about equal content of the two enantiomers. In the present paper we show that l-baclofen causes a considerable (40.7%) suppression of the amplitude of the second peak in the click-evoked response from the cochlear nucleus. Bipolar recordings from the external nucleus of the inferior colliculus showed that l-baclofen caused a reduction in the amplitude of three or four distinct peaks in this response. d-Baclofen had no detectable effect on the response from the cochlear nucleus, and had only a slight effect on one component of the response from the external nucleus of the inferior colliculus. The demonstrated effect of l-baclofen on excitation in the ascending auditory pathway indicates that this drug may be a potential treatment for hyperactive auditory disorders such as tinnitus and hyperacusis.

scholarly journals Quantitative Analysis of the Sustainable Development Capacity of Regional Water Resources：A case study of Sichuan Province

2020 ◽  
Vol 143 ◽  
pp. 02005
Author(s):  
Xuedong Liang ◽  
Li Yang ◽  
Meng Ye ◽  
Guoying Deng
Keyword(s):  
Sustainable Development ◽  
Water Resources ◽  
Water Resource ◽  
Principal Component ◽  
Resource Development ◽  
Measurement Model ◽  
Water Resource Development ◽  
System A ◽  
Sustainable Water Resource ◽  
Regional Water

Limited water resources have become a serious problem in recent decades. Based on previous research results, this article develops an index system to evaluate sustainable water resource development that includes a water resource condition system, a water resource development and utilization system, a water resource protection and management system, and a socio-economic system. A measurement model is then constructed based on a principal component analysis (PCA) -entropy weights-weighted average method to optimize the evaluation index system for dimensionality reduction, to assign weights to the principal component factors, and allow for a comprehensive evaluation of water resource sustainability. The measurement model is applied to an empirical analysis of sustainable water resource development in Sichuan Province from 2008 to 2017, from which it is found that coordinated sustainable regional water resource and social economic development can be achieved through rational exploitation, efficient utilization, and environmental water pollution control. This research could provide a reference for regional sustainable development of water resources and policy developments.

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