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.

Enhanced Hearing Aid Performance with an African Buffalo Optimization-Based Frequency Response Masking Filter

“…The proposed model is compared with existing models like the Signed Approximate Multiplier FRM (SAM-FRM) filter [31], AWD [15], and Non-uniform Filter Bank (NF) approach [18] for evaluating the performance of the proposed model. The comparison of matching errors for different HLs is detailed in Table 8.…”

“…In our proposed non-uniform filter design with three sub band distribution schemes, the use of FRM technique further optimized with ABO algorithm in hybrid combination with distributed arithmetic method resulted in variable customized non-uniform sub band distribution with narrow transition bandwidth and optimized filter coefficients leading to improved matching error and delay as against the SAM-FRM [31] and AWD [15] based designs.…”

Low Complexity Non Maximally Coefficient Symmetry Multi Rate Filter Bank for Wideband Channelization

“…sparse nature of Frequency Response Masking filter coefficients makes the filter low hardware complex for high-resolution uses. Provided the prototype symmetrical impulse response linear phase lowpass filter ( ) a known as Model filter or prototype filter for order , the complementary filter ( ) could represented as, By replacing the D delays outcoming in interpolated linear-phase FIR filters [19] ( ) and ( ), delay of the model filter such as ( ) and ( ) is removed successfully. The transition width of these IFIR filter is 1 times that of ( ).In Frequency Response Masking techniques, both masking filters ( ) ( ) are cascade to ( ) and ( ) , respectively, as given in Figure.2.…”