A Noise-Power-Area Optimized Biosensing Front End for Wireless Body Sensor Nodes and Medical Implantable Devices

In this paper, we present a noise, power, and area efficient biosensing front-end application specified integrated circuit (ASIC) for the next-generation wireless body sensor nodes and implantable devices. We identify the key design parameter tradeoffs in the biomedical recording systems and carry out a thorough analysis and optimization to maximize them. Based on our analysis and optimization of the front end, we propose a design methodology for the recording channel that is applicable to various biomedical applications. The ASIC is implemented in a 0.18-<inline-formula> <tex-math notation="LaTeX">$\mu \text{m}$ </tex-math></inline-formula> CMOS process to validate our optimization methodology. The ASIC is reconfigurable to accommodate various biopotentials with the high-pass and low-pass cutoff frequencies being 0.5–300 Hz and 150 Hz–10 kHz, respectively. The low-pass cutoff is provided by an ultralow power <inline-formula> <tex-math notation="LaTeX">$G_{m}$ </tex-math></inline-formula>-<inline-formula> <tex-math notation="LaTeX">${C}$ </tex-math></inline-formula> low-pass filter, which also acts as an antialiasing filter for the switching-optimized 10-b successive approximation register (SAR) analog-to-digital converter (ADC). The analog front end (AFE) gain is also programmable from 38 to 72 dB. A comprehensive power management unit provides the power supply, multiple reference voltages, and bias currents to the entire chip. The AFE and ADC dissipate only <inline-formula> <tex-math notation="LaTeX">$5.74~\mu \text{W}$ </tex-math></inline-formula> and 306 nW from the on-chip regulators, respectively. The measured input-referred noise is <inline-formula> <tex-math notation="LaTeX">$2.98~\mu \text{V}_{{\text {rms}}}$ </tex-math></inline-formula>, resulting in the noise efficiency factor and power efficiency factor equals 2.6 and 9.46, respectively. The active area of the AFE is 0.0228 mm². We verify the chip functionality in a number of <italic>in vivo</italic> and <italic>ex vivo</italic> biological experiments.