Lung Movement Detection Method using Sound Waves for Continuous Breathing Monitoring

2020 ◽  
Author(s):  
Hiroki Furuyama ◽  
Motoyuki Imai ◽  
Takahiro Yoshida
Keyword(s):  
Detection Method ◽  
Movement Detection ◽  
Sound Waves ◽  
Breathing Monitoring

scholarly journals Efficient Movement Compensation and Detection Algorithm using Blob Detection and Modified Kalman Filter

2020 ◽  
Vol 9 (5) ◽  
pp. 1187-1193
Keyword(s):  
Kalman Filter ◽  
Video Sequence ◽  
Detection Method ◽  
Detection Algorithm ◽  
Movement Detection ◽  
Blob Detection ◽  
Modified Kalman Filter ◽  
Filtering Technique ◽  
Movement Compensation ◽  
Time Required

In various real time applications such as security and surveillance etc., detection of movement from video sequence is commonly used. In such applications, time required to detect the movement and its accuracy is very crucial. In this paper, an efficient motion compensation and detection algorithm using Blob detection and modified Kalman filter techniques is proposed. The method is mainly based on Kalman filtering technique which is modified to compensate and detect the unwanted movement caused by the camera. Also the shadow effect caused by the variation in the intensity of light and object is removed using thresholding technique. Accuracy of movement detection is improved by implementing the blob detection method. The experimental results obtained from the developed algorithm is compared with few methods existing in the literature for validation.

Nonlinear eye movement detection method for drowsiness studies

1996 ◽  
Vol 43 (3) ◽  
pp. 227-242 ◽  
Author(s):  
Alpo Värri ◽  
Kari Hirvonen ◽  
Veikko Häkkinen ◽  
Joel Hasan ◽  
Pekka Loula
Keyword(s):  
Eye Movement ◽  
Detection Method ◽  
Movement Detection

Solid-phase immunoelectron microscopy for rapid diagnosis of enteroviruses

1984 ◽  
Vol 42 ◽  
pp. 226-227 ◽  
Author(s):  
K. Pegg-Feige ◽  
F. W. Doane
Keyword(s):  
Electron Microscopy ◽  
Cell Culture ◽  
Immunoelectron Microscopy ◽  
Detection Method ◽  
Solid Phase ◽  
Protein A ◽  
Plant Viruses ◽  
Rapid Diagnosis ◽  
Virus Diagnosis ◽  
Antiviral Antibody

Immunoelectron microscopy (IEM) applied to rapid virus diagnosis offers a more sensitive detection method than direct electron microscopy (DEM), and can also be used to serotype viruses. One of several IEM techniques is that introduced by Derrick in 1972, in which antiviral antibody is attached to the support film of an EM specimen grid. Originally developed for plant viruses, it has recently been applied to several animal viruses, especially rotaviruses. We have investigated the use of this solid phase IEM technique (SPIEM) in detecting and identifying enteroviruses (in the form of crude cell culture isolates), and have compared it with a modified “SPIEM-SPA” method in which grids are coated with protein A from Staphylococcus aureus prior to exposure to antiserum.

Lantern Slide Illustrating Sound Waves

1894 ◽  
Vol 70 (25) ◽  
pp. 395-395
Author(s):  
M. Hopkins
Keyword(s):  
Sound Waves ◽  
Lantern Slide

A Fault Detection Approach Based on Sound Signal Analysis for Equipment Monitoring

2020 ◽  
pp. 129-139
Author(s):  
Weihai Sun ◽  
Lemei Han
Keyword(s):  
Fault Detection ◽  
Signal Analysis ◽  
Energy Analysis ◽  
Detection Method ◽  
Sound Signal ◽  
Practical Significance ◽  
Time Frequency ◽  
Detection Approach ◽  
Machine Fault ◽  
Learning Data

Machine fault detection has great practical significance. Compared with the detection method that requires external sensors, the detection of machine fault by sound signal does not need to destroy its structure. The current popular audio-based fault detection often needs a lot of learning data and complex learning process, and needs the support of known fault database. The fault detection method based on audio proposed in this paper only needs to ensure that the machine works normally in the first second. Through the correlation coefficient calculation, energy analysis, EMD and other methods to carry out time-frequency analysis of the subsequent collected sound signals, we can detect whether the machine has fault.

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