Maciej Zajaczkowski

Cutaneous electrophysiology is a fundamental non-invasive technique for assessing electrically active organs such as the brain, heart, and muscles. Standard approaches, however, are limited in spatial resolution, reducing sensitivity to certain pathological features. The development of body surface potential mapping using electrode arrays has helped overcome these limitations, enhancing the diagnostic power of cutaneous recordings, yet clinical adoption remains constrained by challenges in electrode performance, wiring complexity, wearability, data transmission, and interpretability. Here, we present a hybrid e-textile electrode array system that overcomes these barriers, enabling simultaneous mapping of electrical activity along the cortico-muscular axis. The system combines application-specific conducting polymer coatings to improve electrode performance, a flexible fabrication process for robust connectivity and wearability, and interpretable machine learning algorithms for data analysis. In controlled single-subject experiments, we demonstrate reliable muscle and brain recordings, enabling classification of grasped object shapes and somatosensory stimuli. Simultaneous multi-site recordings along the cortico-muscular axis provide spatial maps of reaction time distributions and allow prediction of muscle activation patterns from cortical activity. This platform establishes a framework for wearable, multi-modal electrophysiological mapping and non-invasive study of cortico-muscular dynamics, representing a step towards practical brain–body interfaces with applications in neurorehabilitation, prosthetics, and human–machine interaction.

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.