# Flexible Wearable Heart Rate Monitoring System and Low-Power Design: A Review
## 1 Introduction
Hybrid flexible systems [19] refer to systems that combine traditional rigid chip components such as silicon-based MCUs, ceramic capacitors with flexible substrates such as polyimide, polydimethylsiloxane through rigid-flexible integration technology. The flexibility of such systems stems from the mechanical adaptability of the substrate, with quantitative standards defined as a flexible substrate thickness of \(\leq\)50 \(\upmu\)m, an overall achievable bending radius of \(\leq\)10 mm, and rigid components accounting for \(\leq\)30% of the total area by area ratio [20]. These criteria ensure the system can conform to skin or curved carriers and avoid reduced comfort or conformity failure caused by excessively high rigid component ratios. Examples include the filter module in the flexible system mentioned in this paper, the processor module involved in computing, as well as the BLE module, Wi-Fi module, and Zigbee module and so on required for wireless communication. All these modules can be implemented through rigid-flexible integration technology. In addition to defining the concept of flexible systems, this paper also elaborates on the optimization of hardware, algorithms, and hardware--algorithm co-design for flexible wearable heart rate monitoring systems. In the hardware design of the system, flexible materials such as polymer materials [21], carbon-based materials [22], and liquid metals [23]are used to achieve the flexibility of the system. These flexible materials have good electrical conductivity and flexibility [24]. By designing their structures [25] (such as wavy or serpentine configurations), the flexible materials can absorb stress through rotation and buckling during stretching, avoiding damage to the conductive paths and improving conformability at the same time [26]. The devices made of these flexible materials have the advantages of high flexibility and comfort, which well solve the shortcomings of traditional systems. In addition to the use of flexible materials in hardware, flexible wearable heart rate monitoring systems also require corresponding algorithm optimization and adaptation. Algorithmic optimization can reduce the hardware load [27] and ensure the stable operation of the system. A typical example is the adoption of a distributed collaborative optimization algorithm [28] in the process of heart rate acquisition, which enables multiple flexible sensing nodes to automatically adjust the sampling frequency and precision during data acquisition, ensuring the integrity of physiological signals while reducing the synchronization error [29] caused by the flexible deformation of hardware. In terms of hardware-algorithm co-design optimization, hardware structure design can accelerate algorithms, while algorithms can reduce hardware burden. As described in Section 2.3 of this paper, when designing application-specific integrated circuits for flexible wearable systems, by designing system-specific circuit structures and combining them with model compression algorithms, the complexity of the flexible system is significantly reduced, the task processing capability of the flexible system is accelerated, and the system power consumption is lowered. The emergence of flexible wearable heart rate monitoring systems has enhanced the flexibility and comfort of heart rate monitoring systems. More importantly, it has broken through the limitations of usage scenarios [30; 31]. Such systems can be widely applied in various scenarios, including daily health management, sports training monitoring [32], and home care for chronic diseases [33]. For example, during marathon events, runners can use flexible wearable systems worn on their wrists to obtain real-time heart rate variability data, thereby optimizing their exercise rhythm. At the same time, the elderly can use washable flexible patches to achieve a 24 h arrhythmia early warning.