# Flexible Wearable Heart Rate Monitoring System and Low-Power Design: A Review
## 4 Design of the Flexible Wearable Heart Rate Signal Preprocessing Module
### Low-Power Hardware Design of Flexible Wearable Heart Rate Signal Preprocessing Module  
Heart rate signal preprocessing primarily encompasses filtering, noise reduction, signal amplification, baseline drift correction and so on. In this section, we focus on the hardware low-power design of the heart rate signal preprocessing module from the perspective of filtering. As the first step in signal preprocessing, filtering directly influences the energy consumption of subsequent processing units, and its importance is undeniable. To achieve hardware low-power design, various miniaturized filtering circuits [88], such as low-pass filters, high-pass filters, and band-pass filters, are typically integrated onto flexible printed circuit boards (FPCBs) to perform critical signal processing functions. The application of flexible low-pass filter circuits [89] module is particularly effective in suppressing high-frequency noise, which usually originates from sources such as environmental electromagnetic interference (EMI). These circuits operate on the fundamental principle of allowing low-frequency signals to pass unimpeded while significantly attenuating high-frequency components. As shown in Figure 4a, [PERSON] et al. [62] designed a low-power low-pass filter suitable for PPG signals by optimizing the resistor-capacitor (RC) configuration. Specifically, they optimized the RC network structure and circuit layout of the low-pass filter. By customizing the selection of resistor and capacitor parameters, the cutoff frequency of the filter was precisely set within the optimal range, effectively filtering out high-frequency noise in PPG signals. After calculation, its average power consumption is approximately 10 \(\upmu\)W, which is 40% lower than that of traditional filters with fixed resistor and capacitor values, while the noise suppression ratio of PPG signals is increased by 35 dB. \begin{table}
\begin{tabular}{p{42.7 pt} p{113.8 pt} p{113.8 pt} p{113.8 pt} p{113.8 pt}} \hline \hline
**Reference** & **Innovation** & **Practicality** & **Power Optimization Method** & **Power Consumption** & **Power Comparison** \\ \hline
[80] & The system achieves low-power operation at a high sampling rate of 400 Hz. & Support 137 h of continuous monitoring and meets daily monitoring needs. & Hardware–Algorithm co-design & Representing a 16.5\% reduction in power consumption compared to systems without compression algorithms. \\ \hline \hline \end{tabular}
\end{table} 
Table 2: _Cont._In addition, flexible high-pass filter circuits [90] module can eliminate low-frequency interference in heart rate signals, such as those caused by human respiration, slight limb movements, environmental and temperature changes. The elimination of such interference ensures signal stability. Compared with traditional high-pass filters that use fixed-parameter components, the high-pass filter circuit incorporating adjustable resistors and capacitors can dynamically adjust power consumption according to actual signal conditions while ensuring interference removal, thereby further reducing ineffective energy consumption. The flexible band-pass filter circuits [91] module combine the advantages of both low-pass and high-pass filters, allowing only signals within a specific frequency range to pass through. They can accurately retain the effective frequency band of heart rate signals while suppressing interference from other frequency bands. As shown in Figure 4b, [PERSON] et al. [44] realized the design of a low-power band-pass filter through two key aspects: hardware selection and circuit design. Firstly, in terms of hardware selection, they used adjustable pseudo-resistors to replace high-power-consuming components. Compared with the high-power fixed resistors used in traditional band-pass filters, this approach significantly optimized power consumption.