A Human-Computer Interaction Strategy for An FPGA Platform Boosted Integrated "Perception-Memory" System Based on Electronic Tattoos and Memristors.

The integrated "perception-memory" system is receiving increasing attention due to its crucial applications in humanoid robots, as well as in the simulation of the human retina and brain. Here, a Field Programmable Gate Array (FPGA) platform-boosted system that enables the sensing, recognition, and memory for human-computer interaction is reported by the combination of ultra-thin Ag/Al/Paster-based electronic tattoos (AAP) and Tantalum Oxide/Indium Gallium Zinc Oxide (Ta2O5/IGZO)-based memristors. Notably, the AAP demonstrates exceptional capabilities in accommodating the strain caused by skin deformation, thanks to its unique structural design, which ensures a secure fit to the skin and enables the prolonged monitoring of physiological signals. By utilizing Ta2O5/IGZO as the functional layer, a high switching ratio is conferred to the memristor, and an integrated system for sensing, distinguishing, storing, and controlling the machine hand of multiple human physiological signals is constructed together with the AAP. Further, the proposed system implements emergency calls and smart homes using facial electromyogram signals and utilizing logical entailment to realize the control of the music interface. This innovative "perception-memory" integrated system not only serves the disabled, enhancing human-computer interaction but also provides an alternative avenue to enhance the quality of life and autonomy of individuals with disabilities.

Genome-wide association study identifies genomic regions associated with key reproductive traits in Korean Hanwoo cows.

BACKGROUND: Conducting genome-wide association studies (GWAS) for reproductive traits in Hanwoo cattle, including age at first calving (AFC), calving interval (CI), gestation length (GL), and number of artificial inseminations per conception (NAIPC), is of paramount significance. These analyses provided a thorough exploration of the genetic basis of these traits, facilitating the identification of key markers for targeted trait improvement. Breeders can optimize their selection strategies, leading to more efficient and sustainable breeding programs, by incorporating genetic insights. This impact extends beyond individual traits and contributes to the overall productivity and profitability of the Hanwoo beef cattle industry. Ultimately, GWAS is essential in ensuring the long-term genetic resilience and adaptability of Hanwoo cattle populations. The primary goal of this study was to identify significant single nucleotide polymorphisms (SNPs) or quantitative trait loci (QTLs) associated with the studied reproductive traits and subsequently map the underlying genes that hold promise for trait improvement. RESULTS: A genome-wide association study of reproductive traits identified 68 significant single nucleotide polymorphisms (SNPs) distributed across 29 Bos taurus autosomes (BTA). Among them, BTA14 exhibited the highest number of identified SNPs (25), whereas BTA6, BTA7, BTA8, BTA10, BTA13, BTA17, and BTA20 exhibited 8, 5, 5, 3, 8, 2, and 12 significant SNPs, respectively. Annotation of candidate genes within a 500 kb region surrounding the significant SNPs led to the identification of ten candidate genes relevant to age at first calving. These genes were: FANCG, UNC13B, TESK1, TLN1, and CREB3 on BTA8; FAM110B, UBXN2B, SDCBP, and TOX on BTA14; and MAP3K1 on BTA20. Additionally, APBA3, TCF12, and ZFR2, located on BTA7 and BTA10, were associated with the calving interval; PAX1, SGCD, and HAND1, located on BTA7 and BTA13, were linked to gestation length; and RBM47, UBE2K, and GPX8, located on BTA6 and BTA20, were linked to the number of artificial inseminations per conception in Hanwoo cows. CONCLUSIONS: The findings of this study enhance our knowledge of the genetic factors that influence reproductive traits in Hanwoo cattle populations and provide a foundation for future breeding strategies focused on improving desirable traits in beef cattle. This research offers new evidence and insights into the genetic variants and genome regions associated with reproductive traits and contributes valuable information to guide future efforts in cattle breeding.

Functional brain network analysis using electroencephalography in late-onset Lennox-Gastaut syndrome.

OBJECTIVE: We aimed to explore the clinical characteristics and functional network properties of patients with late-onset Lennox-Gastaut syndrome (LGS). METHODS: Late-onset LGS was defined by the appearance of LGS features after 8 years of age. We reviewed the medical charts of 9 patients with late-onset LGS, and performed electroencephalography connectivity analysis using graph theory. We assessed the clustering coefficient (CC) and characteristic path length (CPL), which are common basic measures of functional networks that represent local segregation and global integration. The characteristics and brain parameters of late-onset LGS were compared with a typical age-onset LGS group. RESULTS: Late onset LGS subjects were older than typical age onset LGS at the time of testing, but otherwise there were no significant differences in clinical characteristics. The late-onset group showed higher median CC values in the alpha (p = 0.045) and beta (p < 0.001) bands over brain regions implicated in cognitive processing. There were no significant differences in CPL between the LGS groups. CONCLUSIONS: Higher clustering coefficient values, in alpha/beta bands over brain regions implicated in cognitive processing, are consistent with increased cognitive network segregation in late onset LGS compared to typical age-onset LGS. Given network segregation is a normal aspect of brain maturation, these results imply that this process is less disturbed when the LGS process begins later in childhood.

Radio frequency hyperthermia system for skin tightening effect by filled waveguide aperture antenna with compact metamaterials.

Radio frequency (RF) hyperthermia focuses on raising the target area temperature to a value exceeding 45°C. Collagen is stimulated when the temperature rises to 45°C at the dermal layer, resulting in skin tightening. However, most studies on RF hyperthermia have focused on tumor ablation or using electrodes to radiate an electromagnetic field, which is highly inefficient. This study proposed a non-invasive RF hyperthermia skin-tightening system with a compact metamaterial-filled waveguide aperture antenna. The proposed RF system increased the temperature by 11.6°C and 35.3°C with 20 and 80 W of 2.45 GHz RF power, respectively, within 60 s and exhibited a very focused effective area. Furthermore, a metamaterial was proposed to reduce the size of the waveguide aperture antenna and focus the electromagnetic field in the near-field region. The proposed metamaterial-filled waveguide aperture antenna was compact, measuring 10 mm × 17.4 mm, with a peak gain of 2.2 dB at 2.45 GHz. The measured hyperthermia performance indicated that the proposed RF system exhibited better power- and time-efficient hyperthermia performance than other RF hyperthermia systems in the cosmetic skin lifting commercial market. The proposed RF hyperthermia systems will be applied into a new generation of beauty cosmetic devices.

A Multilayered GaAs IPD Resonator with Five Airbridges for Sensor System Application.

This work proposes a microwave resonator built from gallium arsenide using integrated passive device (IPD) technology. It consists of a three-layered interlaced spiral structure with airbridges and inner interdigital structures. For integrated systems, IPD technology demonstrated outstanding performance, robustness, and a tiny size at a low cost. The airbridges were made more compact, with overall dimensions of 1590 × 800 µm2 (0.038 × 0.019 λg2). The designed microwave resonator operated at 1.99 GHz with a return loss of 39 dB, an insertion loss of 0.07 dB, and a quality factor of 1.15. Additionally, an experiment was conducted on the properties of the airbridge and how they affected resistance, inductance, and S-parameters in the construction of the resonator. To investigate the impact of airbridges on the structure, E- and H-field distributions of the resonator were simulated. Furthermore, its use in sensing applications was explored. Various concentrations of glucose solutions were used in the experiment. The proposed device featured a minimum detectable concentration of 0.2 mg/mL; high sensitivity, namely, 14.58 MHz/mg·mL-1, with a linear response; and a short response time. Thus, this work proposes a structure that exhibits potential in integrated systems and real-time sensing systems with high sensitivity.

Tailoring Classical Conditioning Behavior in TiO2 Nanowires: ZnO QDs-Based Optoelectronic Memristors for Neuromorphic Hardware.

Neuromorphic hardware equipped with associative learning capabilities presents fascinating applications in the next generation of artificial intelligence. However, research into synaptic devices exhibiting complex associative learning behaviors is still nascent. Here, an optoelectronic memristor based on Ag/TiO2 Nanowires: ZnO Quantum dots/FTO was proposed and constructed to emulate the biological associative learning behaviors. Effective implementation of synaptic behaviors, including long and short-term plasticity, and learning-forgetting-relearning behaviors, were achieved in the device through the application of light and electrical stimuli. Leveraging the optoelectronic co-modulated characteristics, a simulation of neuromorphic computing was conducted, resulting in a handwriting digit recognition accuracy of 88.9%. Furthermore, a 3 × 7 memristor array was constructed, confirming its application in artificial visual memory. Most importantly, complex biological associative learning behaviors were emulated by mapping the light and electrical stimuli into conditioned and unconditioned stimuli, respectively. After training through associative pairs, reflexes could be triggered solely using light stimuli. Comprehensively, under specific optoelectronic signal applications, the four features of classical conditioning, namely acquisition, extinction, recovery, and generalization, were elegantly emulated. This work provides an optoelectronic memristor with associative behavior capabilities, offering a pathway for advancing brain-machine interfaces, autonomous robots, and machine self-learning in the future.

Micropyramid Array Bimodal Electronic Skin for Intelligent Material and Surface Shape Perception Based on Capacitive Sensing.

Developing electronic skins (e-skins) that are comparable to or even beyond human tactile perception holds significant importance in advancing the process of intellectualization. In this context, a machine-learning-motivated micropyramid array bimodal (MAB) e-skin based on capacitive sensing is reported, which enables spatial mapping applications based on bimodal sensing (proximity and pressure) implemented via fringing and iontronic effects, such as contactless measurement of 3D objects and contact recognition of Braille letters. Benefiting from the iontronic effect and single-micropyramid structure, the MAB e-skin in pressure mode yields impressive features: a maximum sensitivity of 655.3 kPa-1 (below 0.5 kPa), a linear sensitivity of 327.9 kPa-1 (0.5-15 kPa), and an ultralow limit of detection of 0.2 Pa. With the assistance of multilayer perceptron and convolutional neural network, the MAB e-skin can accurately perceive 6 materials and 10 surface shapes based on the training and learning using the collected datasets from proximity and pressure modes, thus allowing it to achieve the precise perception of different objects within one proximity-pressure cycle. The development of this MAB e-skin opens a new avenue for robotic skin and the expansion of advanced applications.

Intuition-and-Tactile Bimodal Sensing Based on Artificial-Intelligence-Motivated All-Fabric Bionic Electronic Skin for Intelligent Material Perception.

Developing electronic skins (e-skins) with extraordinary perception through bionic strategies has far-reaching significance for the intellectualization of robot skins. Here, an artificial intelligence (AI)-motivated all-fabric bionic (AFB) e-skin is proposed, where the overall structure is inspired by the interlocked bionics of the epidermis-dermis interface inside the skin, while the structural design inspiration of the dielectric layer derives from the branch-needle structure of conifers. More importantly, AFB e-skin achieves intuition sensing in proximity mode and tactile sensing in pressure mode based on the fringing and iontronic effects, respectively, and is simulated and verified through COMSOL finite element analysis. The proposed AFB e-skin in pressure mode exhibits maximum sensitivity of 15.06 kPa-1 (<50 kPa), linear sensitivity of 6.06 kPa-1 (50-200 kPa), and fast response/recovery time of 5.6 ms (40 kPa). By integrating AFB e-skin with AI algorithm, and with the support of material inference mechanisms based on dielectric constant and softness/hardness, an intelligent material perception system capable of recognizing nine materials with indistinguishable surfaces within one proximity-pressure cycle is established, demonstrating abilities that surpass human perception.

Genome-Wide Association Study to Identify QTL for Carcass Traits in Korean Hanwoo Cattle.

This study aimed to identify genetic associations with carcass traits in Hanwoo cattle using a genome-wide association study. A total of 9302 phenotypes were analyzed, and all animals were genotyped using the Illumina Bovine 50K v.3 SNP chip. Heritabilities for carcass weight (CWT), eye muscle area (EMA), backfat thickness (BF), and marbling score (MS) were estimated as 0.42, 0.36, 0.36, and 0.47, respectively, using the GBLUP model, and 0.47, 0.37, 0.36, and 0.42, respectively, using the Bayes B model. We identified 129 common SNPs using DGEBV and 118 common SNPs using GEBV on BTA6, BTA13, and BTA14, suggesting their potential association with the traits of interest. No common SNPs were found between the GBLUP and Bayes B methods when using residuals as a response variable in GWAS. The most promising candidate genes for CWT included SLIT2, PACRGL, KCNIP4, RP1, XKR4, LYN, RPS20, MOS, FAM110B, UBXN2B, CYP7A1, SDCBP, NSMAF, TOX, CA8, LAP3, FAM184B, and NCAPG. For EMA, the genes IBSP, LAP3, FAM184B, LCORL, NCAPG, SLC30A9, and BEND4 demonstrated significance. Similarly, CYP7B1, ARMC1, PDE7A, and CRH were associated with BF, while CTSZ, GNAS, VAPB, and RAB22A were associated with MS. This finding offers valuable insights into genomic regions and molecular mechanisms influencing Hanwoo carcass traits, aiding efficient breeding strategies.

High-Definition Transcranial Direct Current Stimulation in the Right Ventrolateral Prefrontal Cortex Lengthens Sustained Attention in Virtual Reality.

Due to the current limitations of three-dimensional (3D) simulation graphics technology, mind wandering commonly occurs in virtual reality tasks, which has impeded it being applied more extensively. The right ventrolateral prefrontal cortex (rVLPFC) plays a vital role in executing continuous two-dimensional (2D) mental paradigms, and transcranial direct current stimulation (tDCS) over this cortical region has been shown to successfully modulate sustained 2D attention. Accordingly, we further explored the effects of electrical activation of the rVLPFC on 3D attentional tasks using anodal high-definition (HD)-tDCS. A 3D Go/No-go (GNG) task was developed to compare the after effects of real and sham brain stimulation. Specifically, GNG tasks were periodically interrupted to assess the subjective perception of attentional level, behavioral reactions were tracked and decomposed into an underlying decision cognition process, and electroencephalography data were recorded to calculate event-related potentials (ERPs) in rVLPFC. The p-values statistically indicated that HD-tDCS improved the subjective mentality, led to more cautious decisions, and enhanced neuronal discharging in rVLPFC. Additionally, the neurophysiological P300 ERP component and stimulation being active or sham could effectively predict several objective outcomes. These findings indicate that the comprehensive approach including brain stimulation, 3D mental paradigm, and cross-examined performance could significantly lengthen and robustly compare sustained 3D attention.

High-Performance Graphene-Modified Sensing Chip for SARS-CoV-2 Detection.

This sensing prototype model involves the development of a reusable, twofold graphene oxide (GrO)-glazed double inter-digitated capacitive (DIDC) detecting chip for detecting severe acute respiratory syndrome coronavirus 2 virus (SARS-CoV-2) specifically and rapidly. The fabricated DIDC comprises a Ti/Pt-containing glass substrate glazed with graphene oxide (GrO), which is further chemically modified with EDC-NHS to immobilize antibodies (Abs) hostile to SARS-CoV-2 based on the spike (S1) protein of the virus. The results of insightful investigations showed that GrO gave an ideal engineered surface for Ab immobilization and enhanced the capacitance to allow higher sensitivity and low sensing limits. These tunable elements helped accomplish a wide sensing range (1.0 mg/mL to 1.0 fg/mL), a minimum sensing limit of 1 fg/mL, high responsiveness and good linearity of 18.56 nF/g, and a fast reaction time of 3 s. Besides, in terms of developing financially viable point-of-care (POC) testing frameworks, the reusability of the GrO-DIDC biochip in this study is good. Significantly, the biochip is specific against blood-borne antigens and is stable for up to 10 days at 5 °C. Due to its compactness, this scaled-down biosensor has the potential for POC diagnostics of COVID-19 infection. This system can also detect other severe viral diseases, although an approval step utilizing other virus examples is under development.

Ultrahigh-sensitivity multi-parameter tacrolimus solution detection based on an anchor planar millifluidic microwave biosensor.

To detect drug concentration in tacrolimus solution, an anchor planar millifluidic microwave (APMM) biosensor is proposed. The millifluidic system integrated with the sensor enables accurate and efficient detection while eliminating interference caused by the fluidity of the tacrolimus sample. Different concentrations (10-500 ng mL-1) of the tacrolimus analyte were introduced into the millifluidic channel, where it completely interacts with the radio frequency patch electromagnetic field, thereby effectively and sensitively modifying the resonant frequency and amplitude of the transmission coefficient. Experimental results indicate that the sensor has an extremely low limit of detection (LoD) of 0.12 pg mL-1 and a frequency detection resolution (FDR) of 1.59 (MHz (ng mL-1)). The greater the FDR and the lower the LoD, the more the feasibility of a label-free biosensing method. Regression analysis revealed a strong linear correlation (R2 = 0.992) between the concentration of tacrolimus and the frequency difference of the two resonant peaks of APMM. In addition, the difference in the reflection coefficient between the two formants was measured and calculated, and a strong linear correlation (R2 = 0.998) was found between the difference and tacrolimus concentration. Five measurements were performed on each individual sample of tacrolimus to validate the biosensor's high repeatability. Consequently, the proposed biosensor is a potential candidate for the early detection of tacrolimus drug concentration levels in organ transplant recipients. This study presents a simple method for constructing microwave biosensors with high sensitivity and rapid response.

Genomic Predictions in Korean Hanwoo Cows: A Comparative Analysis of Genomic BLUP and Bayesian Methods for Reproductive Traits.

This study aimed to predict the accuracy of genomic estimated breeding values (GEBVs) for reproductive traits in Hanwoo cows using the GBLUP, BayesB, BayesLASSO, and BayesR methods. Accuracy estimates of GEBVs for reproductive traits were derived through fivefold cross-validation, analyzing a dataset comprising 11,348 animals and employing an Illumina Bovine 50K SNP chip. GBLUP showed an accuracy of 0.26 for AFC, while BayesB, BayesLASSO, and BayesR demonstrated values of 0.28, 0.29, and 0.29, respectively. For CI, GBLUP attained an accuracy of 0.19, whereas BayesB, BayesLASSO, and BayesR scored 0.21, 0.24, and 0.25, respectively. The accuracy for GL was uniform across GBLUP, BayesB, and BayesR at 0.31, whereas BayesLASSO showed a slightly higher accuracy of 0.33. For NAIPC, GBLUP showed an accuracy of 0.24, while BayesB, BayesLASSO, and BayesR recorded 0.22, 0.27, and 0.30, respectively. The variation in genomic prediction accuracy among methods indicated Bayesian approaches slightly outperformed GBLUP. The findings suggest that Bayesian methods, notably BayesLASSO and BayesR, offer improved predictive capabilities for reproductive traits. Future research may explore more advanced genomic approaches to enhance predictive accuracy and genetic gains in Hanwoo cattle breeding programs.

Evaluating the Alterations Induced by Virtual Reality in Cerebral Small-World Networks Using Graph Theory Analysis with Electroencephalography.

Virtual reality (VR), a rapidly evolving technology that simulates three-dimensional virtual environments for users, has been proven to activate brain functions. However, the continuous alteration pattern of the functional small-world network in response to comprehensive three-dimensional stimulation rather than realistic two-dimensional media stimuli requires further exploration. Here, we aimed to validate the effect of VR on the pathways and network parameters of a small-world organization and interpret its mechanism of action. Fourteen healthy volunteers were selected to complete missions in an immersive VR game. The changes in the functional network in six different frequency categories were analyzed using graph theory with electroencephalography data measured during the pre-, VR, and post-VR stages. The mutual information matrix revealed that interactions between the frontal and posterior areas and those within the frontal and occipital lobes were strengthened. Subsequently, the betweenness centrality (BC) analysis indicated more robust and extensive pathways among hubs. Furthermore, a specific lateralized channel (O1 or O2) increment in the BC was observed. Moreover, the network parameters improved simultaneously in local segregation, global segregation, and global integration. The overall topological improvements of small-world organizations were in high-frequency bands and exhibited some degree of sustainability.

Identification of Copy Number Variations in Four Horse Breed Populations in South Korea.

In this study, genome-wide CNVs were identified using a total of 469 horses from four horse populations (Jeju horses, Thoroughbreds, Jeju riding horses, and Hanla horses). We detected a total of 843 CNVRs throughout all autosomes: 281, 30, 301, and 310 CNVRs for Jeju horses, Thoroughbreds, Jeju riding horses, and Hanla horses, respectively. Of the total CNVRs, copy number losses were found to be the most abundant (48.99%), while gains and mixed CNVRs accounted for 41.04% and 9.96% of the total CNVRs, respectively. The length of the CNVRs ranged from 0.39 kb to 2.8 Mb, while approximately 7.2% of the reference horse genome assembly was covered by the total CNVRs. By comparing the CNVRs among the populations, we found a significant portion of the CNVRs (30.13%) overlapped; the highest number of shared CNVRs was between Hanla horses and Jeju riding horses. When compared with the horse CNVRs of previous studies, 26.8% of CNVRs were found to be uniquely detected in this study. The CNVRs were not randomly distributed throughout the genome; in particular, the Equus caballus autosome (ECA) 7 comprised the largest proportion of its genome (16.3%), while ECA 24 comprised the smallest (0.7%). Furthermore, functional analysis was applied to CNVRs that overlapped with genes (genic-CNVRs); these overlapping areas may be potentially associated with the olfactory pathway and nervous system. A racing performance QTL was detected in a CNVR of Thoroughbreds, Jeju riding horses, and Hanla horses, and the CNVR value was mixed for three breeds.

Enhancement of Fungal Enzyme Production by Radio-Frequency Electromagnetic Fields.

Enzyme production by microorganisms on an industrial scale has demonstrated technical bottlenecks, such as low efficiency in enzyme expression and extracellular secretion. In this study, as a potential tool for overcoming these technical limits, radio-frequency electromagnetic field (RF-EMF) exposure was examined for its possibility to enhance production of an enzyme, α-amylase, in a filamentous fungus, Aspergillus oryzae. The RF-EMF perfectly resonated at 2 GHz with directivity radiation pattern and peak gain of 0.5 dB (0.01 Watt). Total protein concentration and activity of α-amylase measured in media were about 1.5-3-fold higher in the RF-EMF exposed (10 min) sample than control (no RF-EMF) during incubation (the highest increase after 16 h). The level of α-amylase mRNA in cells was approximately 2-8-fold increased 16 and 24 h after RF-EMF exposure for 10 min. An increase in vesicle accumulation within fungal hyphae and the transcription of some genes involved in protein cellular trafficking was observed in RF-EMF-exposed samples. Membrane potential was not changed, but the intracellular Ca2+ level was elevated after RF-EMF exposure. Our results suggest that RF-EMF can increase the extracellular level of fungal total proteins and α-amylase activity and the intracellular level of Ca2+.

Microfluidic microwave biosensor based on biomimetic materials for the quantitative detection of glucose.

This paper presents a microwave microfluidic biosensor for monitoring blood glucose levels. The glucose sensor is a triple ring microstrip patch antenna integrated with a biomimetic microfluidic device capable of measuring a fixed volume of glucose solution. The sensor was utilized to detect 50-500 mg/dL glucose solutions. The interaction of the glucose solution with the electromagnetic field on the patch's surface influences both the resonance frequency and the magnitude of reflection coefficient. The results indicate that the microfluidic device can reduce experimental error and enhance the correlation between glucose concentration, resonant frequency, and reflection coefficient. Finally, the microfluidic sensor had a sensitivity of 0.25 MHz/(mg/dL), a detection limit as low as 7.7 mg/dL, and correlation coefficients of resonance frequency and reflection coefficient with a glucose concentration of 0.996 and 0.984, respectively. The experiment on the sensor's stability verifies the sensor's excellent stability and rapid response (~ 150 ms). Consequently, the device can be used to differentiate the concentration of glucose solutions, as well as to detect blood glucose levels at an early stage.

NaCl Ionization-Based Moisture Sensor Prepared by Aerosol Deposition for Monitoring Respiratory Patterns.

A highly polarizable moisture sensor with multimodal sensing capabilities has great advantages for healthcare applications such as human respiration monitoring. We introduce an ionically polarizable moisture sensor based on NaCl/BaTiO3 composite films fabricated using a facile aerosol deposition (AD) process. The proposed sensing model operates based on an enormous NaCl ionization effect in addition to natural moisture polarization, whereas all previous sensors are based only on the latter. We obtained an optimal sensing performance in a 0.5 µm-thick layer containing NaCl-37.5 wt% by manipulating the sensing layer thickness and weight fraction of NaCl. The NaCl/BaTiO3 sensing layer exhibits outstanding sensitivity over a wide humidity range and a fast response/recovery time of 2/2 s; these results were obtained by performing the one-step AD process at room temperature without using any auxiliary methods. Further, we present a human respiration monitoring system using a sensing device that provides favorable and stable electrical signals under diverse respiratory scenarios.

Ultrasensitive probeless capacitive biosensor for amyloid beta (Aß1-42) detection in human plasma using interdigitated electrodes.

Progressive aggregation and protein misfolding are the initial fundamental indicators of neurodegenerative disorders such as Alzheimer's disease (AD). In this study, a highly sensitive and novel method to detect amyloid beta (Aß) biomarkers, which are a hallmark of AD, using an immunoassay platform-based interdigitated capacitive biosensor, has been explored. For several decades, aptamers have classified as a novel class of molecular recognition probes comprising single-stranded complementary DNA sequences that bind to their identified targets with high specificity and affinity by an in vitro technique called SELEX (systematic evolution of exponential and enrichment). Aptamers, often referred to as "chemical antibodies", possess several highly obvious features for clinical use. The proposed sensing bio-device was fabricated and glazed with oligomeric Aß (oAß) aptamer and anti-oAß antibody, functionalized onto a Pt/Ti-featured SiO2 substrate. Subsequently, analytical studies were conducted to confirm that the specificity, sensitivity, and selective detection of the oAß-based bioengineered surfaces facilitate a label-free approach. The bionic capacitive sensor achieved real-time detection within 5 s (faster response than ELISA) under the femto-molar range concentrations of oAß peptide in plasma using anti-oAß antibody and oAß aptamer with ultra-high affinity. Furthermore, the prepared capacitive biochip was selective against plasma-borne antigens and standby for 100 days at 4 °C. The developed biosensor is suitable for point-of-care (POC) diagnostic applications owing to its portability and scalability. Furthermore, the superior efficacy of oAß in identifying AD has huge potential for biomedical applications.