ArticleJMIR mHealth and uHealth2020
Accurate Measurement of Handwash Quality Using Sensor Armbands: Instrument Validation Study.
Article in JMIR mHealth and uHealth, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.
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Who cites it
8 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Electronic Monitoring Systems for Hand Hygiene: Systematic Review of Technology.Journal of medical Internet research · 2021Pooled it
- A Real-World Dataset for detecting Handwashing in daily Life using Wrist Motion Data from Wearables.Scientific data · 2026Article
- A System for Computational Assessment of Hand Hygiene Techniques.Journal of medical systems · 2022Article
- A New Performance Metric to Estimate the Risk of Exposure to Infection in a Health Care Setting: Descriptive Study.JMIR formative research · 2022Article
- Detecting hand washing activity among activities of daily living and classification of WHO hand washing techniques using wearable devices and machine learning algorithms.Healthcare technology letters · 2021Article
- iWash: A smartwatch handwashing quality assessment and reminder system with real-time feedback in the context of infectious disease.Smart health (Amsterdam, Netherlands) · 2021Article
- Deployment of a Smart Handwashing Station in a School Setting During the COVID-19 Pandemic: Field Study.JMIR public health and surveillance · 2020Article
- Digital Health Strategies to Fight COVID-19 Worldwide: Challenges, Recommendations, and a Call for Papers.Journal of medical Internet research · 2020Article
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundHand hygiene is a crucial and cost-effective method to prevent health care-associated infections, and in 2009, the World Health Organization (WHO) issued guidelines to encourage and standardize hand hygiene procedures. However, a common challenge in health care settings is low adherence, leading to low handwashing quality. Recent advances in machine learning and wearable sensing have made it possible to accurately measure handwashing quality for the purposes of training, feedback, or accreditation.
objectiveWe measured the accuracy of a sensor armband (Myo armband) in detecting the steps and duration of the WHO procedures for handwashing and handrubbing.
methodsWe recruited 20 participants (10 females; mean age 26.5 years, SD 3.3). In a semistructured environment, we collected armband data (acceleration, gyroscope, orientation, and surface electromyography data) and video data from each participant during 15 handrub and 15 handwash sessions. We evaluated the detection accuracy for different armband placements, sensor configurations, user-dependent vs user-independent models, and the use of bootstrapping.
resultsUsing a single armband, the accuracy was 96% (SD 0.01) for the user-dependent model and 82% (SD 0.08) for the user-independent model. This increased when using two armbands to 97% (SD 0.01) and 91% (SD 0.04), respectively. Performance increased when the armband was placed on the forearm (user dependent: 97%, SD 0.01; and user independent: 91%, SD 0.04) and decreased when placed on the arm (user dependent: 96%, SD 0.01; and user independent: 80%, SD 0.06). In terms of bootstrapping, user-dependent models can achieve more than 80% accuracy after six training sessions and 90% with 16 sessions. Finally, we found that the combination of accelerometer and gyroscope minimizes power consumption and cost while maximizing performance.
conclusionsA sensor armband can be used to measure hand hygiene quality relatively accurately, in terms of both handwashing and handrubbing. The performance is acceptable using a single armband worn in the upper arm but can substantially improve by placing the armband on the forearm or by using two armbands.
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