Frequency response masking based FIR filter using approximate multiplier for bio-medical applications

Abstract

The advancements in medical healthcare networks and bio-medical sensor technologies enabled the use of wearable and body implantable intelligent devices for healthcare monitoring. These battery-operated devices must be capable of very low power operation for ensuring long battery life and also to prevent intense radiations. The major power consuming part of these devices are the multipliers built into the digital filters for performing signal processing operations. This paper proposes a low power signed approximate multiplier architecture for bio-medical signal processing applications. The circuit characteristics and error metrics of the proposed multiplier are estimated to verify its performance advantage over other approximate multipliers. In order to validate the efficacy of the approximate multiplier in real time signal processing applications, a band pass finite impulse response filter (FIR) filter is designed using frequency response masking technique and used in the Pan Tompkins method for the extraction of QRS complex from raw ECG data. The sensitivity, positive predictivity, and detection error rate of the QRS detection method are estimated and the results show that the approximate filtering method implemented gives a comparable performance as that of exact methods.