Evidence map›Paper›PMID 41644570›Full record

ArticleScientific data2026

A Real-World Dataset for detecting Handwashing in daily Life using Wrist Motion Data from Wearables.

Robin Burchard, Kristina Kirsten, Marcel Miché, Philipp Scholl, Bert Arnrich, Kristof Van Laerhoven, Roselind Lieb, Karina Wahl

Abstract readDataset
In one paragraph

Article in Scientific data, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Robin Burchard *University of Siegen, Siegen, Germany. robin.burchard@uni-siegen.de.ORCID http://orcid.org/0000-0002-4130-5287
Kristina Kirsten *Hasso Plattner Institute, Potsdam, Germany. kristina.kirsten@hpi.de.ORCID http://orcid.org/0000-0002-1284-8477
Marcel MichéUniversity of Basel, Basel, Switzerland.ORCID http://orcid.org/0000-0001-8838-1749
Philipp SchollUniversity of Freiburg, Freiburg, Germany.ORCID http://orcid.org/0000-0001-6941-0161
Bert ArnrichHasso Plattner Institute, Potsdam, Germany.ORCID http://orcid.org/0000-0001-8380-7667
Kristof Van LaerhovenUniversity of Siegen, Siegen, Germany.ORCID http://orcid.org/0000-0001-5296-5347
Roselind LiebUniversity of Basel, Basel, Switzerland.ORCID http://orcid.org/0000-0002-2039-2262
Karina WahlUniversity of Basel, Basel, Switzerland.ORCID http://orcid.org/0000-0002-9232-0911

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Handwashing detection is a relevant research topic with applications in healthcare and professional environments. While usually related to hygiene improvement, handwashing detection could also be used to support individuals with obsessive-compulsive disorder (OCD). For these individuals, compulsive, long, and frequent handwashing has a negative impact. An automated system could spot compulsive handwashing in real-time and augment the therapy process. No activity recognition datasets containing in-the-wild-recorded compulsive handwashing are available. With this work, we present the OCDetect Dataset, the first dataset with unscripted, compulsive handwashing. It contains recordings from inertial measurement units (IMUs) of 22 participants over 28 days, with 3000 recorded hand washes. For each hand wash, we supply its user-annotated kind (compulsive / routine). We provide an overview of related datasets and describe the recording, cleaning, labeling, and final features of our dataset. We reach a maximum F1 score of 0.77 (avg.: 0.33, chance level: 0.03) when spotting handwashing from all background activities on unseen participants. Our dataset and code for the reproduction of our results are publicly available.

Indexed as

Hand DisinfectionWearable Electronic DevicesWristHumans

Identifiers

PMID41644570
PMCPMC12881347

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.