Adaptive algorithm and integrated circuit implementation for signal sensing of low-power pacemakers

Cardiac pacemakers are key implantable devices in modern medicine for treating arrhythmias. The accuracy and reliability of their sensing function directly determine the success or failure of treatment. To address the issue that traditional fixed-parameter sensing paradigms struggle to cope with the complex dynamic characteristics of intracardiac electrical signals, leading to clinical risks such as under-sensing or oversensing, a systematic review of the evolution of adaptive sensing technology is conducted. The architecture, principles, and interaction logic of adaptive sensing algorithms, from classic to intelligent, are deeply analyzed. Key technologies of application-specific integrated circuits (ASICs) that support the implementation of these algorithms are elaborated, including high-precision analog front-end design, analog-digital mixed signal coordination, and ultra-low power optimization. A comprehensive system implementation and performance evaluation framework is established, covering model-based design, hardware-in-the-loop testing, and preclinical validation in compliance with medical device regulations. A complete technical chain of adaptive sensing technology is systematically reviewed, and the key points of algorithm and hardware co-design are clarified. This system can effectively enhance the safety, specificity, and individual adaptability of the sensing system in complex physiological and noisy environments, and provide rigorous validation methods for clinical application. Adaptive sensing technology is a core direction to break through the performance bottlenecks of traditional pacemakers. Future technologies will develop towards multi-modal sensor fusion, personalized adaptation, and predictive maintenance.