This paper presents the implementation of the first fully integrated pulse oximeter front-end with a power consumption lower than 1 mW. This is enabled by system- and block-level noise optimisation, also detailed in the manuscript. The proposed design features an analogue feedback loop that enables fast and accurate regulation of the detected photocurrent level and a serial-to-parallel interface allowing for extensive programmability of several operation parameters. The front-end was fabricated in the AMS 0.35 μm technology and occupies an area of 1.35 mm ² . Extensive measured results, both electrical and physiological from human subjects are reported, demonstrating an estimated SNR of 39 dB and ability to detect 2% changes in S _p O ₂ , similar to commercial pulse oximeters. This is despite the constrained power consumption which amounts to 0.31 mW for the LEDs and 0.53 mW for the rest of the front-end from a 3.3 V supply. Statistical results from 20 chips verify good matching across the Red and Infrared channels of the front-end and the accurate operation of the proposed analogue feedback loop.

Background: We present a miniature (30 × 34 mm) 64-channel data acquisition headstage optimized for high-density surface electromyography. Methods: The headstage is made up of a multi-channel ASIC analogue front-end utilizing only MOS transistors, fabricated in 350 nm CMOS technology (IC die dimensions 6.9 × 1.8 mm), combined with an off-the-shelf multi-channel current-input ADC (DDC264, Texas Instruments). The ASIC analogue front-end employs MOS-based capacitors for both processing and AC-coupling. Results: The combination of these two sub-circuits enables the simultaneous recording of 64 channels at a typical sampling rate of 4 KHz with a maximum analogue bandwidth of 0.5–1500 Hz and a resolution of 20-bits. Typical input-referred-noise, determined by the analogue front-end, is 3.5 μV_RMS for a surface EMG bandwidth of interest of 20–500 Hz. This two-chip solution results in a power consumption of 5 mW per channel. Analogue performance variability of the custom ASIC was characterized across a dataset of 960-channels (15 dies) from two fabrication runs. Conclusions: This work practically demonstrates the viability of using both a MOS-only analogue front-end and commercially available off-shelf high-performance back-end hardware already developed for medical imaging applications to record high-density surface biosignals. The aforementioned techniques can be employed to reduce the size and cost for systems or wearable devices; facilitating the translation of high-density bio-acquisition setups from the research environment to more affordable commercial products.