Diagnostic Devices
Diagnostic Devices - Related Videos
10:21
Microfluidic Applications for Disposable Diagnostics
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Cited by 1 •
2008
In this interview, Dr. Klapperich discusses the fabrication of thermoplastic microfluidic devices and their application for development of new diagnostics.
08:28
Overview of BioMEM Devices
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2023
Bio-microelectromechanical systems, also called BioMEMs, are microscale devices that enable the use of small sample and reagent volumes for diagnostic devices in vivo and in vitro. These devices perform various functions such as filtration, sensing, or synthesis on the microscale, enabling cost savings and improved sensitivity. This video introduces BioMEMs, touches on their use in the bioengineering field, and presents some prominent methods used in fabrication. Additionally, this video...
08:29
Thermal Measurement Techniques in Analytical Microfluidic Devices
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Cited by 6 •
2015
Here, we present three protocols for thermal measurements in microfluidic devices.
07:42
Magnetic Levitation Coupled with Portable Imaging and Analysis for Disease Diagnostics
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Cited by 11 •
2017
We present a magnetic levitation technique coupled with automated imaging and analysis in both a smartphone-compatible device and a device with embedded imaging and processing. This is applied to measure the density distribution of cells with two demonstrated biomedical applications: sickle cell disease diagnosis and separating white and red blood cells.
07:12
Diagnostic Ultrasound Imaging of Mouse Diaphragm Function
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Cited by 7 •
2014
Diagnostic ultrasound imaging has proven to be effective in diagnosing various respiratory diseases in human and animal subjects. We demonstrate a comprehensive ultrasound protocol utilized by Dr. Zuo's lab to analyze diaphragm kinetics specifically in mouse models. This is also a non-invasive research technique which can provide quantitative information on mouse respiratory muscle function.
FAQs
They first recognize a biological target or signal, then translate that interaction into a readable output. Depending on the device, the signal may be processed through biochemical, optical, electrical, or imaging-based mechanisms. This conversion allows measurements such as pathogen detection, protein analysis, nucleic-acid assessment, cell identification, or physiological monitoring to support clinical interpretation.
Target selection determines what biological question the device can address. Nucleic acids can support genetic or infectious-disease analysis, proteins can indicate biological conditions, and cells or pathogens can provide direct information about disease-related material. Physiological signals instead reflect body function. Matching the target to the diagnostic goal influences the usefulness of the resulting measurement.
These mechanisms differ in how they transform biological information into an output. Biochemical systems rely on biological interactions, optical systems interpret changes involving light, electrical systems measure signal changes, and imaging systems produce visual or spatial information. The selected mechanism affects how a device analyzes targets or physiological function, as well as how its results can be interpreted.
A typical workflow begins by selecting the biological indicator relevant to the question, such as a nucleic acid, protein, cell, pathogen, or physiological signal. The device then detects, measures, or analyzes that indicator and converts the interaction into a readable result. That output can be used to identify disease, monitor health, or guide a clinical decision.
Their use depends on the setting and the information needed. Point-of-care screening benefits from devices that can support accessible testing near the patient, while laboratory testing can address biological measurements in a dedicated testing environment. Across both settings, diagnostic devices contribute to infectious disease detection, genetic analysis, health monitoring, and decisions about further care.
In biology, these tools help researchers examine disease processes by measuring relevant targets or physiological signals. They can also support the development of more accessible diagnostic approaches by revealing how speed, sensitivity, and portability affect testing. Their outputs may guide treatment selection, enable early disease identification, and connect biological measurements with clinical or experimental questions.