The integration of multiple sensors in biomedical applications requires efficient and reliable data processing architectures. This paper proposes a Low-Power ASIC Architecture optimized for multi-sensor data processing in biomedical applications, leveraging nanoelectronics for enhanced performance and energy efficiency. The architecture employs 28 nm CMOS technology and features an advanced power gating technique to minimize power consumption, achieving a reduction of up to 45% in dynamic power dissipation compared to conventional designs. The proposed system integrates three distinct sensor modalities: ECG, temperature, and pressure sensors, for real-time monitoring and analysis. The multi-sensor fusion is facilitated by a customized data path, which reduces signal processing latency by 35% and enhances the overall system throughput by 20%. The system operates at a voltage of 0.9 V and delivers low-power consumption of 5.8 mW under typical operating conditions, ensuring long-term wearability for continuous health monitoring in wearable biomedical devices. Furthermore, the architecture incorporates nanoelectronic-based circuits such as memristors and nanotube field-effect transistors (CNTFETs), improving the system’s overall reliability and compactness. Experimental results demonstrate that the architecture maintains a signal-to-noise ratio (SNR) improvement of 10 dB over previous designs, while reducing the area efficiency by 30%. This design is particularly suitable for portable and battery-operated devices, addressing the critical need for low-power, high-performance biomedical monitoring systems.
Kumaran et al. (Sat,) studied this question.