Project centers in Chennai

IEEE Final Year Project Topic for ECE

Base Paper Title

An Energy-Efficient ECG Processor With Weak-Strong Hybrid Classifier for Arrhythmia Detection

Our Title

IEEE Project Abstract

This brief presents an energy-efficient electrocardiogram processor for arrhythmia detection with a weak-strong hybrid classifier that includes a weak linear classifier (WLC) and a strong support vector machine (SVM) classifier. WLC can only identify the beats with distinct characteristics by performing simple threshold comparisons based on beat interval feature and a novel morphology feature named QRS area ratio. The beats that are unclassified by WLC will activate the more powerful but energy-guzzling SVM classifier. Principal component analysis (PCA) is applied for feature dimension reduction to lower the complexity of SVM classifier and a sparse matrix computing architecture is exploited to reduce the computation burden of PCA. Implemented in SMIC 40LL CMOS process, the processor has a total area of 0.12 mm 2 . It achieves 1.98-uW power consumption in WLC mode and 3.76-uW in SVM mode under 1.1-V voltage supply and 10-KHz operating frequency, with energy dissipation of 6.8/30.3 nJ per beat classification for the two modes, respectively. The overall accuracy for MIT-BIH arrhythmia database is 98.2% with energy reduction of 41.7% compared to a single SVM classifier.

Existing System

Drawback of Existing System

Proposed System

Advantage of Proposed System

Enhancement from Base Paper

Architecture

Technology Used : Hardware & Software

Existing Algorithm

Proposed Algorithm

Advantages of Proposed Algorithm

Project Modules

Literature Survey

Conclusion

Future Work

To View the Abstract Contents

Exclusive
Offer
Refer Your Friend
10%
CASHBACK
Refer Another Friend
Thanks for Referring Your Friend / Relation

Now it is Your Time to Shine.

Great careers Start Here.

We Guide you to Every Step

Success! You're Awesome

Thank you for filling out your information!

We’ve sent you an email with your Final Year Project PPT file download link at the email address you provided. Please enjoy, and let us know if there’s anything else we can help you with.

To know more details Call 900 31 31 555

The WISEN Team