Publication | Open Access
Adaptive Biosensing and Neuromorphic Classification Based on an Ambipolar Organic Mixed Ionic–Electronic Conductor
93
Citations
35
References
2022
Year
Medical ElectronicsEngineeringBiomedical EngineeringChemistryNeurochipBiosensing SystemsNeuromorphic EngineeringBiohybrid SystemsCation SensingBio-electronic InterfacesBiophysicsElectrical EngineeringImplantable SensorComputer EngineeringComplementary Logic InverterElectrochemistryBiomedical SensorsNeuromorphic ClassificationBioelectronicsIonic ConductorHeartbeat Anomaly DetectionAdaptive BiosensingElectrophysiologyElectroanalytical SensorFunctional Materials
Organic mixed ionic-electronic conductors (OMIECs) are central to bioelectronic applications such as biosensors, health-monitoring devices, and neural interfaces, and have facilitated efficient next-generation brain-inspired computing and biohybrid systems. Despite these examples, smart and adaptive circuits that can locally process and optimize biosignals have not yet been realized. Here, a tunable sensing circuit is shown that can locally modulate biologically relevant signals like electromyograms (EMGs) and electrocardiograms (ECGs), that is based on a complementary logic inverter combined with a neuromorphic memory element, and that is constructed from a single polymer mixed conductor. It is demonstrated that a small neuromorphic array based on this material effects high classification accuracy in heartbeat anomaly detection. This high-performance material allows for straightforward monolithic integration, which reduces fabrication complexity while also achieving high on/off ratios with excellent ambient p- and n-type stability in transistor performance. This material opens a route toward simple and straightforward fabrication and integration of more sophisticated adaptive circuits for future smart bioelectronics.
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