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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.


Magnitude responses of IFIR components of U(z): G(z20) and I2(z4).
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pone.0175139.g009: Magnitude responses of IFIR components of U(z): G(z20) and I2(z4).

Mentions: Note that the interpolator filter I(z) removes all magnitude response peaks except for the first passband at DC as illustrated in Fig 7. On the other hand, the magnitude response of G(z20) provides all the required components of the desired magnitude response of U(z) at DC, ±0.5π and π. Hence, to convert UPartial(z) to U (z), we only need to change the interpolator filter I(z) to avoid the removal of the desired peaks at ±0.5π and π. This desired masking is illustrated in Fig 9 in solid blue which shows the magnitude response of I2(z4), the stretched (by a factor of four) version of the new interpolator filter I2(z). In fact, by employing this properly designed interpolator filter, one can select the desired set of peaks from the magnitude response of model filter G(z20). Thus, filter U(z) is realized using two stretched factors G(z20) and I2(z4). Our analysis revealed that the interpolator filter I2(z) has an order of 7 (4 multipliers and 4 structural adders). Hence, the effective total order of U(z) = G(z20) I2(z4) filter is 20×27+4×7 = 568. Therefore, our double-stretch-factor IFIR implementation of U(z) resulted in a filter with an order of 568, consisting of 18 multipliers and 34 structural adders.


A novel low-complexity digital filter design for wearable ECG devices
Magnitude responses of IFIR components of U(z): G(z20) and I2(z4).
© Copyright Policy
Related In: Results  -  Collection

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

pone.0175139.g009: Magnitude responses of IFIR components of U(z): G(z20) and I2(z4).
Mentions: Note that the interpolator filter I(z) removes all magnitude response peaks except for the first passband at DC as illustrated in Fig 7. On the other hand, the magnitude response of G(z20) provides all the required components of the desired magnitude response of U(z) at DC, ±0.5π and π. Hence, to convert UPartial(z) to U (z), we only need to change the interpolator filter I(z) to avoid the removal of the desired peaks at ±0.5π and π. This desired masking is illustrated in Fig 9 in solid blue which shows the magnitude response of I2(z4), the stretched (by a factor of four) version of the new interpolator filter I2(z). In fact, by employing this properly designed interpolator filter, one can select the desired set of peaks from the magnitude response of model filter G(z20). Thus, filter U(z) is realized using two stretched factors G(z20) and I2(z4). Our analysis revealed that the interpolator filter I2(z) has an order of 7 (4 multipliers and 4 structural adders). Hence, the effective total order of U(z) = G(z20) I2(z4) filter is 20×27+4×7 = 568. Therefore, our double-stretch-factor IFIR implementation of U(z) resulted in a filter with an order of 568, consisting of 18 multipliers and 34 structural adders.

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.