Wearable Sensors for eLearning of Manual Tasks: Using Forearm EMG in Hand Hygiene Training.
Sensors (Basel)
; 16(8)2016 Aug 03.
Article
em En
| MEDLINE
| ID: mdl-27527167
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.
Palavras-chave
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Eletromiografia
/
Higiene das Mãos
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Dispositivos Eletrônicos Vestíveis
Limite:
Humans
Idioma:
En
Ano de publicação:
2016
Tipo de documento:
Article