Authentication and Identification is primary part of biometric technology. Currently, electrocardiogram (ECG) is not only being used as a diagnostic tool for clinical purposes, but also as a new biometric tool for high level security system because of its liveliness and uniqueness that is hard to imitate and manipulate. There are many fiducial (signal mark) that is classified from ECG morphology (QRS Complex, P, T waves) has already been researched for this purpose. For non fiducial, many researches are focus on dynamic character from heartbeat (ECG Signal). Heart Rate Variability (HRV) analysis is part of non fiducial classifier. This paper reviews Heart Rate Variability analysis (time and frequency domain) as part of multi matches, one of scenario from multimodal biometric. Sample of person’s heartbeat signal is taken from ECG Database MIT-BIH (MIT and Harvard) and the result of every parameter will be analyzed by Biometric Performance Standards Tools (ISO/IEC IS 19795-1) such as: False Non-Match Rate (FNMR), False Match Rate (FMR) and Thresholds EER (Equal Error Rate). Analysis should show accuracy of multi matches Heart Rate Variability (HRV). As integrator tool, LabView is used to collect offline ECG, process the data and generate HRV Analysis.

Electro Cardyogram (ECG) is signal that produced by Medical Equipment named Electrocardyograph. Reading and Intepretation of ECG Record used manually by Paramedics as a main tool to diagnose heart abnormality and other disfunction internal body part. ECG Analyzer is digitally reading ECG by electronic. When applied with signal processing and Expert System, it will get accureate reading and intepretationn For ECG Electronic signal processing (such as ECG Analyzer), need Noise-Free ECG Signal. For this purpose, Denoising Filter as pre conditioning signal processing strongly recommend.Purpose of this paper is to get denoising filter (Transfer Function and Electronic Circuit). This Result can be integrated with ECG Analyzer in the future. Approach for denoising filter design in this paper using Butterworth Approximation (s-domain). To get ideal coefficient of Denoising Filter, this paper used Particle Swarm Optimization (PSO) as Optimization iteration. Matlab used for Filter Design and Optimization. Proteus applied for Electronic Circuit Simulation. ECG Offline Data tested as sample input to see the response. As a result, already got Transfer Function and Electronic Circuit Prototype as per ECG Free-Noise requirement.Keywords : Electro Cardio Gram (ECG), Denoising Filter, Analog Filter, Particle Swarm OptimizationABSTRAKSinyal ECG (Electro Cardiogram) adalah sinyal yang dihasilkan Peralatan Medis yang bernama Electrocardyograph. Bacaan dan Intepretasi record ECG secara manual, digunakan sebagai alat bantu utama paramedis dalam mendiagnosa ketidaknormalan jantung dan organ tubuh yang lain. ECG Analyzer adalah digitalisasi bacaan ECG secara elektronik. Dimana melalui pengolahan sinyal (Signal processing) dan Algoritma Expert System, nantinya akan didapat intepretasi bacaan yang akurat. Untuk analisa bacaan sinyal ECG secara elektronik (ECG Analyzer), diperlukan sinyal ECG yang bebas derau (noise). Untuk keperluan itu, diperlukan blok denoising filter yang merupakan pre-conditioning sinyal elektronik.Tujuan riset ini adalah untuk mendapatkan denoising filter berupa Transfer Function dan rangkaian elektronik teroptimasi. Yang bisa digunakan selanjutnya untuk pengintegrasian dengan ECG Analyzer. Pendekatan untuk desain denoising filter ini adalah Aproksimasi Analog (Butterworth Approximation). Sedang untuk optimasi (mendapatkan koefisien koefisien filter ideal) digunakan algoritma optimasi Particle Swarm Optimization (PSO). Digunakan Matlab untuk desain dan optimasi Denoising Filter dan Proteus untuk simulasi electronic circuitnya. Data ECG Offline diujikan sebagai sample input. Dari desain dan optimasi akhir telah didapat Transfer Function dan prototype rangkaian elektronika analog yang bebas noise dan siap untuk diintegrasikan dengan ECG Analyzer baik secara analog maupun digital nantinyaKata kunci: Electro Cardio Gram (ECG), Filter Denoising, Filter Analog, Optimasi Penyebaran Partikel

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