ArticleSensors (Basel, Switzerland)2016
Wearable Sensors for eLearning of Manual Tasks: Using Forearm EMG in Hand Hygiene Training.
Article in Sensors (Basel, Switzerland), 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 10 papers, 1 of them a synthesis that pooled 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.
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.
Who cites it
10 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
- Dynamic graph convolutional network for assembly behavior recognition based on attention mechanism and multi-scale feature fusion.Scientific reports · 2022Article
- Interrater reliability in the assessment of physiotherapy students.BMC medical education · 2022Article
- How does innovative technology impact nursing in infectious diseases and infection control? A scoping review.Nursing open · 2021Article
- Powdered Activated Charcoal Tracing in Hand Hygiene Training and Compliance Assessment During the COVID-19 Pandemic.Risk management and healthcare policy · 2021Article
- Deployment of a Smart Handwashing Station in a School Setting During the COVID-19 Pandemic: Field Study.JMIR public health and surveillance · 2020Article
- Accurate Measurement of Handwash Quality Using Sensor Armbands: Instrument Validation Study.JMIR mHealth and uHealth · 2020Article
- Correction: Kutafina, E.; Laukamp, D.; Bettermann, R.; Schroeder, U.; Jonas, S.M. Wearable Sensors for eLearning of Manual Tasks: Using Forearm EMG in Hand Hygiene Training.Sensors (Basel, Switzerland) · 2019Article
- Sensor-based machine learning for workflow detection and as key to detect expert level in laparoscopic suturing and knot-tying.Surgical endoscopy · 2019Article
Corrections and comments
- Erratum issued
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In this paper, we propose a novel approach to eLearning that makes use of smart wearable sensors. Traditional eLearning supports the remote and mobile learning of mostly theoretical knowledge. Here we discuss the possibilities of eLearning to support the training of manual skills. We employ forearm armbands with inertial measurement units and surface electromyography sensors to detect and analyse the user's hand motions and evaluate their performance. Hand hygiene is chosen as the example activity, as it is a highly standardized manual task that is often not properly executed. The World Health Organization guidelines on hand hygiene are taken as a model of the optimal hygiene procedure, due to their algorithmic structure. Gesture recognition procedures based on artificial neural networks and hidden Markov modeling were developed, achieving recognition rates of 98 . 30 % ( ± 1 . 26 % ) for individual gestures. Our approach is shown to be promising for further research and application in the mobile eLearning of manual skills.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.