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A novel low-complexity digital filter design for wearable ECG devices

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ABSTRACT

Wearable and implantable Electrocardiograph (ECG) devices are becoming prevailing tools for continuous real-time personal health monitoring. The ECG signal can be contaminated by various types of noise and artifacts (e.g., powerline interference, baseline wandering) that must be removed or suppressed for accurate ECG signal processing. Limited device size, power consumption and cost are critical issues that need to be carefully considered when designing any portable health monitoring device, including a battery-powered ECG device. This work presents a novel low-complexity noise suppression reconfigurable finite impulse response (FIR) filter structure for wearable ECG and heart monitoring devices. The design relies on a recently introduced optimally-factored FIR filter method. The new filter structure and several of its useful features are presented in detail. We also studied the hardware complexity of the proposed structure and compared it with the state-of-the-art. The results showed that the new ECG filter has a lower hardware complexity relative to the state-of-the-art ECG filters.

No MeSH data available.


IFIR filter technique employs a cascade of two filters to reduce the number of multipliers and structural adders.
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pone.0175139.g004: IFIR filter technique employs a cascade of two filters to reduce the number of multipliers and structural adders.

Mentions: Note that UPartial(z) has a very sharp transition band. In general, IFIR filter techniques are well-suited for the efficient implementation of filters with sharp transition band [19]. The IFIR implementation reduces the filter’s hardware complexity in terms of number of multipliers and structural adders by restructuring it as a cascade of two other filters, a model filter G(z) and an interpolator (or masking) filter I(z), as depicted in Fig 4. The parameter L is the stretch factor of the IFIR filter implementation which is usually chosen empirically.


A novel low-complexity digital filter design for wearable ECG devices
IFIR filter technique employs a cascade of two filters to reduce the number of multipliers and structural adders.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC5383230&req=5

pone.0175139.g004: IFIR filter technique employs a cascade of two filters to reduce the number of multipliers and structural adders.
Mentions: Note that UPartial(z) has a very sharp transition band. In general, IFIR filter techniques are well-suited for the efficient implementation of filters with sharp transition band [19]. The IFIR implementation reduces the filter’s hardware complexity in terms of number of multipliers and structural adders by restructuring it as a cascade of two other filters, a model filter G(z) and an interpolator (or masking) filter I(z), as depicted in Fig 4. The parameter L is the stretch factor of the IFIR filter implementation which is usually chosen empirically.

View Article: PubMed Central - PubMed

ABSTRACT

Wearable and implantable Electrocardiograph (ECG) devices are becoming prevailing tools for continuous real-time personal health monitoring. The ECG signal can be contaminated by various types of noise and artifacts (e.g., powerline interference, baseline wandering) that must be removed or suppressed for accurate ECG signal processing. Limited device size, power consumption and cost are critical issues that need to be carefully considered when designing any portable health monitoring device, including a battery-powered ECG device. This work presents a novel low-complexity noise suppression reconfigurable finite impulse response (FIR) filter structure for wearable ECG and heart monitoring devices. The design relies on a recently introduced optimally-factored FIR filter method. The new filter structure and several of its useful features are presented in detail. We also studied the hardware complexity of the proposed structure and compared it with the state-of-the-art. The results showed that the new ECG filter has a lower hardware complexity relative to the state-of-the-art ECG filters.

No MeSH data available.