High-sensitivity and robust laser-induced graphene sensing arrays for spatiotemporal pulse mapping

Real-time pulse monitoring could enable the diagnosis of cardiovascular conditions and thus has potential application value in cardiovascular health assessment and long-term physiological status monitoring. However, current pulse sensors are predominantly limited to point-pixel signal acquisition, which fails to emulate the 3D spatial perception inherent in traditional Chinese medicine, posing a significant challenge for subsequent diagnosis. Herein, a wearable laser-induced graphene (LIG) pulse sensor array was developed. Before fabrication of LIG, precision mechanical processing was utilized to mill an array of groove structures on the polyimide (PI) substrate to achieve stress-concentration structures, thereby enhancing sensitivity. Then, the obtained porous LIG framework was modified with MoS₂ through a dip-coating process. Unexpectedly, the MoS₂ nanosheets filled the micropores or cracks of porous LIG and mitigated cross-unit variations within the sensing array, achieving excellent batch-to-batch consistency across different sensor arrays. Furthermore, a novel chemical bond between PI and outer polydimethylsiloxane (PDMS) was developed for flexible encapsulation to prevent the adverse effects of atmospheric humidity on the functional properties of LIG and thus ensure long-term stability. The as-fabricated sensors exhibited several superior properties that are characterized by enhanced sensitivity (2.205 kPa⁻¹) in the low-pressure range (0–15 kPa), excellent consistency (maximum interdevice error of 6.61%), fast response/relaxation times (approximately 23/30 ms), high stability (over 10000 mechanical cycles), and excellent minimum detectable pressure (approximately 35 Pa). Due to the above advantages, this sensor array is applied for the detection and 3D reconstruction of pulse signals in the Cun, Guan, and Chi pulse diagnosis positions of humans. This work opens up a new avenue for wearable pulse monitoring and potential diagnosis.