Digital Assessment
Digital Assessment - Related Videos
07:38
Multimodal Quantitative Phase Imaging with Digital Holographic Microscopy Accurately Assesses Intestinal Inflammation and Epithelial Wound Healing
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Cited by 18 •
2016
Accurate assessment of anti-inflammatory effects is of utmost importance for the evaluation of potential new drugs for the treatment of inflammatory bowel disease. Digital holographic microscopy provides assessment of inflammation in murine and human colonic tissue samples as well as automated multimodal evaluation of epithelial wound healing in vitro.
07:56
Digital Planimetry for Assessing Wound Closure Kinetics in a Mouse Model
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Cited by 2 •
2025
Wounds represent a global health challenge. This study developed a standardized photo booth utilizing digital planimetry to minimize wound measurement variability. Monitoring wounds in mice over 14 days revealed an initial increase in wound area and perimeter, followed by gradual closure. This methodology may aid in evaluating wound closure kinetics in pre-clinical models.
08:07
Traditional Trail Making Test Modified into Brand-new Assessment Tools: Digital and Walking Trail Making Test
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Cited by 10 •
2019
Here, we present a protocol to show how to perform two types of cognitive assessment tools derived from the paper-pencil version of the Trail Making Test.
14:02
Measuring Engagement of Spectators of Social Digital Games
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2021
We propose a methodology that enables measuring engagement of spectators in a social digital game combining physiological and self-reported data. As this digital game involves a group of freely moving people, the experience is filmed using a synchronizing technique that links physiological data with events in the game.
08:06
Use of a Low-flow Digital Anesthesia System for Mice and Rats
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Cited by 4 •
2016
Here, we present a protocol to more safely and efficiently administer anesthetic gas to mice using a digital, low flow anesthesia system utilizing a syringe-driven direct injection vaporizer.
FAQs
Validation determines whether a digital assessment measures the intended health, ability, or progress-related information consistently enough for clinical use. Developers and clinicians must examine how structured questionnaires, digital measurements, imaging, sensor data, and observations are collected and interpreted. Without appropriate validation, standardized software outputs may appear precise while providing weak support for screening, diagnosis, treatment planning, or follow-up.
Data quality affects every stage of interpretation. Missing entries, inconsistent measurements, poorly captured images, or unreliable sensor readings can limit the usefulness of an otherwise well-designed system. Combining several data types may provide a broader clinical picture, but the information still requires organized review so that software-supported results remain connected to the patient’s actual condition and clinical progress.
Privacy protection and equitable access are core conditions for responsible implementation. Health information collected through digital tools must be handled in ways that protect the person while still allowing relevant results to be communicated. Access also matters: if patients cannot use the technology or obtain the required measurements, the resulting assessment may not represent their health fairly or support consistent clinical decisions.
A typical clinical workflow begins by selecting an appropriate questionnaire, measurement, imaging source, sensor, or observation for the evaluation goal. Information is then captured electronically, organized by software, and reviewed to support interpretation. Results can be communicated to the clinical team and compared across follow-up encounters, provided the data remain sufficiently complete, consistent, and appropriately protected.
Digital assessment can support several points in care rather than a single clinical task. Structured results may contribute to screening and diagnosis, while repeated measurements or symptom reports can help monitor progress. Clinicians may also use the organized information for treatment planning and follow-up, making the approach relevant when patient status needs to be captured and reviewed over time.
In clinical research and practice, the main outcomes are more organized information, standardized evaluation, and clearer review of change over time. Continued advances may strengthen remote care by enabling information to be collected outside traditional encounters, while combining patient-specific data could support more personalized clinical decision-making. These benefits remain dependent on validation, data quality, privacy, and equitable access.