Design of Multi-Channel Signal Acquisition and Transmission Unit Based on Multi-core DSP

2021 ◽  
Author(s):  
Xin Liu ◽  
Jinyang Wang
Keyword(s):  
Signal Acquisition ◽  
Transmission Unit

A New Robust GPS Satellite Signal Acquisition Using Lifting Wavelet

2005 ◽  
Vol 63 (5) ◽  
pp. 389-403 ◽  
Author(s):  
D. Djebouri ◽  
A. Djebbari ◽  
M. Djebbouri
Keyword(s):  
Signal Acquisition ◽  
Satellite Signal ◽  
Lifting Wavelet

HYBRID CLASSIFICATION SCHEMES FOR HEART MURMUR DETECTION TO ASSIST PHONOCARDIOGRAM BASED SIGNAL ACQUISITION

2017 ◽  
Vol 13 (9) ◽  
pp. 6480-6488 ◽  
Author(s):  
A.D. Jeyarani ◽  
Reena Daphne ◽  
Solomon Roach
Keyword(s):  
Neural Network ◽  
Signal Acquisition ◽  
Heart Murmur ◽  
Classification Techniques ◽  
Classification Schemes ◽  
Neural Network Classification ◽  
Nonlinear Classification ◽  
Processing Step ◽  
System Characterization ◽  
Hybrid Classification

The main contribution of this paper has been to introduce nonlinear classification techniques to extract more information from the PCG signal. Especially, Artificial Neural Network classification techniques have been used to reconstruct the underlying system’s state space based on the measured PCG signal. This processing step provides a geometrical interpretation of the dynamics of the signal, whose structure can be utilized for both system characterization and classification as well as for signal processing tasks such as detection and prediction.

DEFINITION OF TIME SPENT ON REPAIR OF BUS TRANSMISSION UNITS TAKING INTO ACCOUNT TECHNOLOGICAL EQUIPMENT RELIABILITY

2020 ◽  
Vol 2020 (9) ◽  
pp. 29-33
Author(s):  
Sergey Bulatov
Keyword(s):  
Negative Impact ◽  
Probabilistic Method ◽  
Technological Equipment ◽  
Quality And Safety ◽  
Transmission Unit ◽  
Equipment Reliability ◽  
Hours Of Work ◽  
Definition Of ◽  
Time Decrease

The paper purpose is the effectiveness estimation in the technological equipment use, taking into account its reliability and productivity for defective transmission units of buses. The problem consists in the determination of time to be spent on repair of bus transmission units taking into account technological equipment reliability. In the paper there is used a probabilistic method for the prediction bus transmission units, and also a method of the dynamics of averages which allow ensuring minimum of costs for units downtime during repair and equipment cost. The need for repair of transmission units (gear box) arises on an average after 650 hours, the average productivity of the bench makes 4.2 bus / hour. The bench fails on the average after 4600 hours of work, the average time of the bench makes 2 hours. In such a way the solution of the problem specified allows analyzing the necessity of time decrease for transmission unit repair to avoid long downtimes of buses in repair areas without negative impact upon high repair quality and safety during the further operation.

The Development of a Myoelectric Training Tool for Above-Elbow Amputees

2012 ◽  
Vol 6 (1) ◽  
pp. 5-15 ◽  
Author(s):  
Michael R Dawson ◽  
Farbod Fahimi ◽  
Jason P Carey
Keyword(s):  
Degrees Of Freedom ◽  
Learning Task ◽  
Robotic Arm ◽  
Signal Acquisition ◽  
Myoelectric Prosthesis ◽  
Training Tool ◽  
Myoelectric Prostheses ◽  
Training Systems ◽  
Targeted Muscle Reinnervation

The objective of above-elbow myoelectric prostheses is to reestablish the functionality of missing limbs and increase the quality of life of amputees. By using electromyography (EMG) electrodes attached to the surface of the skin, amputees are able to control motors in myoelectric prostheses by voluntarily contracting the muscles of their residual limb. This work describes the development of an inexpensive myoelectric training tool (MTT) designed to help upper limb amputees learn how to use myoelectric technology in advance of receiving their actual myoelectric prosthesis. The training tool consists of a physical and simulated robotic arm, signal acquisition hardware, controller software, and a graphical user interface. The MTT improves over earlier training systems by allowing a targeted muscle reinnervation (TMR) patient to control up to two degrees of freedom simultaneously. The training tool has also been designed to function as a research prototype for novel myoelectric controllers. A preliminary experiment was performed in order to evaluate the effectiveness of the MTT as a learning tool and to identify any issues with the system. Five able-bodied participants performed a motor-learning task using the EMG controlled robotic arm with the goal of moving five balls from one box to another as quickly as possible. The results indicate that the subjects improved their skill in myoelectric control over the course of the trials. A usability survey was administered to the subjects after their trials. Results from the survey showed that the shoulder degree of freedom was the most difficult to control.

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