Mirbakht, Seyed Sajjad and Ballıpınar, Faruk and Arman Kuzubaşoğlu, Burcu and Taşdelen, Melih Can and Güler, Saygun and Yapıcı, Murat Kaya (2026) Inkjet-printed aqueous graphene suspensions on flexible substrates for multimodal wearable continuous health monitoring. ACS Nanoscience Au, 6 (4). pp. 582-595. ISSN 2694-2496
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Official URL: https://dx.doi.org/10.1021/acsnanoscienceau.5c00195
Abstract
Flexible and gel-free dry electrophysiological electrodes offer excellent alternatives to the benchmark with better skin conformality and dispensing with the hydrogel electrolyte layer, where the integrity of recorded signals highly depends on the resilience of this layer. However, the implicit complex fabrication methods and resource-intensive nature of existing dry electrodes, designed for single use, necessitate additional technological innovations. This paper presents an original integration of inkjet-printing, graphene, and poly(ethylene terephthalate) (PET) substrates to create flexible, inexpensive, and reusable dry electrodes for monitoring human physiological biopotential signals, including ECG, EEG, EOG, and EMG. The electrodes exhibited high electrical conductivity (80 Ω/□) and maintained their performance even after 100 cyclic bends. Additionally, they demonstrated robust signal collection even 90 days postfabrication, with reusability and strong graphene-substrate bonding verified through Scotch tape experiments. Assessing against gel-based commercial electrodes, a 99.34% correlation ratio was obtained from the recorded ECG signals. Similarly, a correlation ratio of 95.14 ± 4.75% was achieved with 10 diverse participants. The capability of these electrodes to effectively record neural signals in practical applications was demonstrated in real-time detection of sleep and drowsiness in car drivers. These findings highlight the potential of inkjet-printed graphene electrodes in advancing wearable health monitoring technologies.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | biopotential monitoring; functional inks; neural signals; printed electronics; printing process optimization |
| Divisions: | Faculty of Engineering and Natural Sciences Sabancı University Nanotechnology Research and Application Center |
| Depositing User: | Murat Kaya Yapıcı |
| Date Deposited: | 09 Sep 2026 10:25 |
| Last Modified: | 09 Sep 2026 10:25 |
| URI: | https://research.sabanciuniv.edu/id/eprint/54466 |

