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Cited by 22Dermatology and Skin DiseasesContext-Aware Activity Recognition SystemsContact Dermatitis and Allergies

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

Use of technology for the objective evaluation of scratching behavior: A systematic review

Open access
Yang, Albert F., Nguyen, Morgan, Li, Alvin W., Lee, Brad, Chun, Keum San, Wu, Ellen, Fishbein, Anna B., Paller, Amy S., Xu, Shuai·2021·JAAD International
DOI 10.1016/j.jdin.2021.06.005PMC PMC8593746
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Abstract

Introduction Pruritus is a common symptom across various dermatologic conditions, with a negative impact on quality of life. Devices to quantify itch objectively primarily use scratch as a proxy. This review compares and evaluates the performance of technologies aimed at objectively measuring scratch behavior. Methods Articles identified from literature searches performed in October 2020 were reviewed and those that did not report a primary statistical performance measure (eg, sensitivity, specificity) were excluded. The articles were independently reviewed by 2 authors. Results The literature search resulted in 6231 articles, of which 24 met eligibility criteria. Studies were categorized by technology, with actigraphy being the most studied (n = 21). Wrist actigraphy's performance is poorer in pruritic patients and inherently limited in finger-dominant scratch detection. It has moderate correlations with objective measures (Eczema and Area Severity Index/Investigator's Global Assessment: r s (ρ) = 0.70-0.76), but correlations with subjective measures are poor (r 2 = 0.06, r s (ρ) = 0.18-0.40 for itch measured using a visual analog scale). This may be due to varied subjective perception of itch or actigraphy's underestimation of scratch. Conclusion Actigraphy's large variability in performance and limited understanding of its specificity for scratch merits larger studies looking at validation of data analysis algorithms and device performance, particularly within target patient populations.

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  • A meta-analysis evaluating the performance of image-based AI models for skin disease severity assessment has not been reported.

    “Notably, a meta-analysis evaluating the performance of image-based AI models for skin disease severity assessment has not been reported.15,16”

    From Assessing the performance of artificial intelligence models in evaluating inflammatory skin disease severity: a systematic review and meta-analysis (2025) · cites this paper as [16]

    The Results section reviews technologies for detecting scratching, and the Discussion addresses performance of scratch-monitoring algorithms. Neither states whether a meta-analysis of image-based AI models for skin disease severity assessment has been reported; searches for that topic found no such passage in our copy. Page numbers were not available. (LLM, conf=0.76)

    Experimental — accuracy not yet measured

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Research works printed but not linked: 38

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Metadata

Authors
Yang, A. F., Nguyen, M., Li, A. W., Lee, B., Chun, K. S., Wu, E., Fishbein, A. B., Paller, A. S., & Xu, S.
Affiliations
  • Northwestern University (US)
  • The University of Texas at Austin (US)
  • Lurie Children's Hospital (US)
Corresponding author
Xu, Shuai
ORCID
Venue
JAAD International
Publisher
Elsevier BV
Published
2021-12
Volume
5
Pages
19-32
ISSN
2666-3287 (ISSN-L)
DOI
10.1016/j.jdin.2021.06.005
PMC
PMC8593746
OpenAlex
W3195751850
Cited by
22
References
1
Citations by year
2026: 3 · 2025: 8 · 2024: 3 · 2023: 6 · 2022: 2
FWCI
0.49
Type
journal article
Language
en
Open access
Licence
Locations
  • JAAD International (publishedVersion, cc-by-nc-nd)
  • PubMed Central (publishedVersion, cc-by-nc-nd)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Funders
Food and Drug Administration
Topics
  • Health Sciences › Medicine › Dermatology › Dermatology and Skin Diseases
  • Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Context-Aware Activity Recognition Systems
  • Health Sciences › Medicine › Dermatology › Contact Dermatitis and Allergies
Keywords
pruritus, scratching behavior, actigraphy, wrist actigraphy, Investigator's Global Assessment, visual analogue scale, device validation, data analysis algorithms

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