Toward Neuromorphic Diagnostics: Memristors in Noncommunicable Disease Detection and Sensory Emulation

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Authors: Debashis Panda, Arpan Acharya, Subhrakali Swain, C. T. Lo
Cited by: 1
References: 57

Abstract

Emerging materials‐based devices are revolutionizing healthcare by advancing diagnostics, monitoring, and therapeutic strategies. Among them, memristor devices capable of storing and processing information are attracting and receiving significant attention for their biomedical potential. Their tunable resistance enables sensitive, low‐power detection of major noncommunicable diseases such as diabetes and cancer. Devices fabricated with AlO x , SiO x , and GeO x have demonstrated effective glucose monitoring and biomarker detection, including sarcosine for prostate cancer and LOXL2 for breast cancer, offering pathways toward cost‐effective and early diagnosis. Beyond disease detection, memristor exhibit nociceptive properties such as threshold sensing, synaptic plasticity, and adaptive learning, enabling multifunctional applications in neurological and sensory systems. Artificial nociceptors emulate pain perception for prosthetics and robotics, photoreceptors integrate light sensing with memory for artificial vision, and memristors neuromodulatory platforms provide energy‐efficient seizure control and adaptive deep brain stimulation for Parkinson's disease. Collectively, these developments position memristors as versatile, compact, and biomimetic devices with the potential to unify diagnostics, therapy, and sensory replication in next‐generation biomedical technologies.

Fields of Study & Subjects

Advanced Memory and Neural Computing Advanced Sensor and Energy Harvesting Materials MXene and MAX Phase Materials

Publication details

Journal / source
ChemNanoMat
Publisher
Wiley
Volume
12
Issue
2
Publication date
1 February 2026
Language
EN