Steps Involved in Heart Sound Analysis- A Review of Existing Trends
Journal Title: INTERNATIONAL JOURNAL OF ENGINEERING TRENDS AND TECHNOLOGY - Year 2013, Vol 4, Issue 7
Abstract
This paper reviews the heart sounds thought to be extremely important to access the condition of heart and covers the stages involved in Phonocardiograph (PCG) signal analysis which includes signal acquisition, methods of feature extraction, feature reduction and classification. The recent advancements and researches are included in chronological order in order to establish the time to time advancements in this field.
Authors and Affiliations
Amandeep Cheema1 , Mandeep Singh
Keywords
Related Articles
- EP ID EP156804
- DOI -
- Views 112
- Downloads 0
Energy Efficient Clustering using Jumper Firefly Algorithm in Wireless Sensor Networks
Wireless Sensor Network (WSN) is a major and very interesting technology, which consists of small battery powered sensor nodes with limited power resources. The sensor nodes are inaccessible to the user once they are dep...
Low Power Fir Filter Design Using Truncated Multiplier
In this paper Low-cost finite impulse response(FIR) design are presented using the concept of faithfully rounded truncated multipliers. We jointly consider the effective of bit width and hardware resources without sacrif...
A Wireless Approach with Sensor Network for Real Time Railway Track Surveillance System
This paper report discusses the safeness analysis of a railway track. A sensor network has been used to detect the cracks in the railway track. This sensor network incorporates an IR sensor and a photodiode. An Arduino U...
A NOVEL CONTROL METHOD FOR UNIFIED POWER QUALITY CONDITIONER USING NINE-SWITCH POWER CONDITIONER
The load-reactive power compensation in most of the UPQC based power quality compensation application is done by shunt APF, whereas, the series APF is generally utilized to compensate voltage related problems. In...
Designing an FPGA Synthesizable Computer Vision Algorithm to Detect the Greening of Potatoes
Potato quality control has improved in the last years thanks to automation techniques like machine vision, mainly making the classification task between different quality degrees faster, safer and less subjective. In our...