Multimodal Sensors
Multimodal Sensors - Related Videos
09:14
Glovebox and Impurity Sensors
0 Views •
2023
Source: Tamara M. Powers, Department of Chemistry, Texas A&M University The glovebox provides a straightforward means to handle air- and moisture-sensitive solids and liquids. The glovebox is what it sounds like: a box with gloves attached to one or more sides, which allows the user to perform manipulations within the glovebox under an inert atmosphere. For manipulations under inert atmospheres, chemists can choose between Schlenk or high-vacuum techniques and a glovebox. Schlenk and...
19:32
Preterm EEG: A Multimodal Neurophysiological Protocol
0 Views •
Cited by 39 •
2012
This video explains the background theory of the neonatal EEG activity and the sensory responses, followed by a live demonstration of their recording in neonatal intensive care unit.
09:30
Bacterial Detection & Identification Using Electrochemical Sensors
0 Views •
Cited by 6 •
2013
We describe an electrochemical sensor assay method for rapid bacterial detection and identification. The assay involves a sensor array functionalized with DNA oligonucleotide capture probes for ribosomal RNA (rRNA) species-specific sequences. Sandwich hybridization of target rRNA with the capture probe and a horseradish peroxidase-linked DNA oligonucleotide detector probe produces a measurable amperometric current.
10:23
Glutamine Flux Imaging Using Genetically Encoded Sensors
0 Views •
Cited by 7 •
2014
This article will demonstrate how to monitor glutamine dynamics in live cells using FRET. Genetically encoded sensors allow real-time monitoring of biological molecules at a subcellular resolution. Experimental design, technical details of the experimental settings, and considerations for post-experimental analyses will be discussed for genetically encoded glutamine sensors.
05:15
An Aptamer-based Sensor for Unchelated Gadolinium(III)
0 Views •
2017
The use of polydeoxynucleotide (44-mer aptamer) molecules for sensing unchelated gadolinium(III) ion in an aqueous solution is described. The presence of the ion is detected via an increase in the fluorescence emission of the sensor.
FAQs
Signal fusion combines outputs from different sensing elements so a system can interpret several dimensions of the same physiological or physical event. For example, pressure, temperature, motion, and electrical activity may provide complementary information that one measurement cannot capture alone. Data analysis then supports a more complete assessment and may help reveal health changes earlier.
Different modalities respond to different properties of tissues, devices, or surrounding conditions. Electrodes can provide information about electrical activity, while optical components, pressure detectors, and temperature-sensitive materials address other signal types. Combining these outputs allows bioengineers to relate biological activity to motion, pressure, or temperature, improving physiological monitoring and system interpretation.
Component selection depends on the signals that must be measured and the intended bioengineering application. A design may integrate electrodes, optical components, pressure detectors, or temperature-sensitive materials when those measurements are relevant to the system. The resulting outputs must then be processed together so the sensor produces useful information rather than isolated readings.
A typical workflow begins by identifying the biological or physical signals of interest, followed by selecting sensing elements that can detect them. The system collects the outputs together and applies signal fusion or data analysis to interpret their relationships. Researchers can then use the combined measurements for physiological monitoring, health-change detection, or personalized biomedical investigation.
These systems can support monitoring in wearable devices and implantable systems by combining measurements such as biomarkers, motion, pressure, temperature, and electrical activity. The choice of signals depends on the monitoring goal. Integrating them can provide a broader picture of physiological status than relying on a single measurement, supporting more responsive assessment of health changes.
In responsive prosthetics, combined measurements can connect information about movement or pressure with relevant biological signals. This broader input can help the system interpret conditions affecting prosthetic use and respond more appropriately. The overview identifies responsive prosthetics as a bioengineering application in which integrated sensing may improve interaction between physiological activity and an assistive device.
Multimodal measurements can capture several aspects of an individual’s physiological state at the same time, including biomarkers, motion, pressure, temperature, or electrical activity. This broader dataset supports personalized biomedical research by allowing investigators to examine health changes in relation to multiple signals rather than a single variable, improving the context available for individualized analysis.