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

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.


The optimally factored-cascade IFIR implementation of U(z) = βG(z20) I2(z4).
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pone.0175139.g011: The optimally factored-cascade IFIR implementation of U(z) = βG(z20) I2(z4).

Mentions: To further reduce the hardware complexity of the design (in terms of numbers of multipliers and structural adders), we used the factoring filter design method of [20–22] to decompose the G(z20) and I2(z4) filters into their optimal sequence of factors. Fig 11 shows the resulted optimally factored-cascade IFIR implementation of U(z) = βG(z20) I2(z4), where β is the post-filter-multiplier. Note that one of the main advantages of our optimally-factored cascade structure is that each stage is followed by a post-stage power-of-two multiplier and a truncation operation to properly adjust the data path word length.


A novel low-complexity digital filter design for wearable ECG devices
The optimally factored-cascade IFIR implementation of U(z) = βG(z20) I2(z4).
© Copyright Policy
Related In: Results  -  Collection

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

pone.0175139.g011: The optimally factored-cascade IFIR implementation of U(z) = βG(z20) I2(z4).
Mentions: To further reduce the hardware complexity of the design (in terms of numbers of multipliers and structural adders), we used the factoring filter design method of [20–22] to decompose the G(z20) and I2(z4) filters into their optimal sequence of factors. Fig 11 shows the resulted optimally factored-cascade IFIR implementation of U(z) = βG(z20) I2(z4), where β is the post-filter-multiplier. Note that one of the main advantages of our optimally-factored cascade structure is that each stage is followed by a post-stage power-of-two multiplier and a truncation operation to properly adjust the data path word length.

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.