Real-Time Respiration and Heartbeat Detector Using a Compact 1.6 GHz Single-Channel Doppler Sensor

The paper aims to determine the characteristic frequencies of an electric drill, by measuring and analyzing comparatively the variations of the acoustic intensity level, using the Fast Fourier Transform method (FFT). This was applied using a stand which had been specifically developed for the presented work. In two channel and multichannel systems, digital methods have been used for the calculation of cross properties as they were the only practical methods. Using digital techniques has gained considerable ground, being nowadays applied to problems once solved by resorting to analog methods. The increasing use of Fast Fourier Transform methods is found in single channel real time narrow band measurements and the Digital Filtering is replacing the Analog Filter bank which was used as the basis for real time analyzers operating with constant percentage bandwidth.

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Single channel wireless EEG device for real-time fatigue level detection

2015 International Joint Conference on Neural Networks (IJCNN) ◽

10.1109/ijcnn.2015.7280817 ◽

2015 ◽

Cited By ~ 1

Author(s):

Li-Wei Ko ◽

Wei-Kai Lai ◽

Wei-Gang Liang ◽

Chun-Hsiang Chuang ◽

Shao-Wei Lu ◽

...

Keyword(s):

Real Time ◽

Single Channel ◽

Wireless Eeg

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COMPUTER SYSTEMS FOR REAL‐TIME MARINE EXPLORATION

Geophysics ◽

10.1190/1.1440341 ◽

1973 ◽

Vol 38 (2) ◽

pp. 301-309 ◽

Cited By ~ 1

Author(s):

E. K. Darby ◽

E. J. Mercado ◽

R. M. Zoll ◽

J. R. Emanuel

Keyword(s):

Real Time ◽

Seismic Data ◽

Magnetic Tape ◽

Single Channel ◽

Magnetic Measurements ◽

Data Gathering ◽

Time Of Day ◽

Magnetic Profile ◽

Multichannel Seismic Data ◽

Marine Exploration

The goals of the Gulfrex are to perform marine exploration and to conduct research and development in the various facets of marine exploration. The Gulfrex is equipped with various geologic and geophysical data‐gathering instruments along with a highly sophisticated navigational package. Computerized control systems were designed to output data in real time so that preliminary interpretations could be made concurrently with data collection. One system, based on an EMR‐6130 computer, handles multichannel seismic data. This system includes routines for real‐time demultiplexing, normal moveout, stacking, and deconvolution. Output of demultiplexed data is to magnetic tape and optionally to paper records. Output of moveout‐corrected, stacked data is to a visual monitor and to magnetic tape via a PDP‐8 computer. Deconvolution may be applied to either the single‐channel traces or the stacked traces. A moveout‐corrected, CDP group is output to a paper record every 24 shots so that estimates of average velocities can be made for a normal‐moveout correction. Another system, designed for a PDP‐8 computer, is used to collect data from devices interfaced to it. These include single‐channel seismic data, gravity and magnetic measurements, and navigational measurements such as course, speed, ship position, and direction. Deconvolved single‐channel seismic data are plotted in real time on a visual monitor along with a corrected gravity profile, magnetic profile, speed, course, and time of day. A map of the ship’s course is plotted in real time on a drum plotter Inquiries may be made of the system for current position in latitude and longitude.

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DEVELOPMENT OF A REAL-TIME SINGLE CHANNEL BRAIN–COMPUTER INTERFACE SYSTEM FOR DETECTION OF DROWSINESS

Biomedical Engineering Applications Basis and Communications ◽

10.4015/s1016237217500193 ◽

2017 ◽

Vol 29 (03) ◽

pp. 1750019 ◽

Cited By ~ 4

Author(s):

Malhar Pathak ◽

A. K. Jayanthy

Keyword(s):

Real Time ◽

Single Channel ◽

Detection System ◽

Brain Computer Interface ◽

Reference Electrode ◽

Computer Interface ◽

Processing Unit ◽

Eeg Signal ◽

Drowsiness Detection ◽

Interface System

Drowsiness or fatigue condition refers to feeling abnormally sleepy at an inappropriate time, especially during day time. It reduces the level of concentration and slowdown the response time, which eventually increases the error rate while doing any day-to-day activity. It can be dangerous for some people who require higher concentration level while doing their work. Study shows that 25–30% of road accidents occur due to drowsy driving. There are number of methods available for the detection of drowsiness out of which most of the methods provide an indirect measurement of drowsiness whereas electroencephalography provides the most reliable and direct measurement of the level of consciousness of the subject. The aim of this paper is to design and develop a portable and low cost brain–computer interface system for detection of drowsiness. In this study, we are using three dry electrodes out of which two active electrodes are placed on the forehead whereas the reference electrode is placed on the earlobe to acquire electroencephalogram (EEG) signal. Previous research shows that, there is a measurable change in the amplitude of theta ([Formula: see text]) wave and alpha ([Formula: see text]) wave between the active state and the drowsy state and based on this fact theta ([Formula: see text]) wave and alpha ([Formula: see text]) wave are separated from the normal EEG signal. The signal processing unit is interfaced with the microcontroller unit which is programmed to analyze the drowsiness based on the change in the amplitude of theta ([Formula: see text]) wave. An alarm will be activated once drowsiness is detected. The experiment was conducted on 20 subjects and EEG data were recorded to develop our drowsiness detection system. Experimental results have proved that our system has achieved real-time drowsiness detection with an accuracy of approximately 85%.

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