The automation of spaces has become a recurrent theme in current affairs due to the need to improve comfort, quality of life and facilitate work for the human being. Thus, this article proposes an intelligent system that allows controlling devices wirelessly in a domestic environment in a simple and safe way. Our system is based on the recognition of different gestures that user makes with his arm, using the bracelet MYO of the company Thalmic Labs. The bracelet consists of 8 electrodes, an accelerometer and a gyroscope. The implementation of the system is done through a wireless data collection classification module. The communication system is made up with ZigBee modules, which control the electrical and electronic devices in the home. In order to perform the recognizing and classification of electromyography (EMG) signals, an artificial neural network model based on supervised learning has used. This work specifies the procedure that we have followed to extract the characteristics of received signals, the training phase of learning system, and an explanation of used algorithms.
|Title of host publication||Advances in Human Factors and Ergonomics in Healthcare and Medical Devices - Proceedings of the AHFE 2017 International Conferences on Human Factors and Ergonomics in Healthcare and Medical Devices, 2017|
|Editors||Vincent Duffy, Nancy Lightner|
|Number of pages||9|
|State||Published - 1 Jan 2018|
|Event||AHFE 2017 International Conferences on Human Factors and Ergonomics in Healthcare and Medical Devices, 2017 - Los Angeles, United States|
Duration: 17 Jul 2017 → 21 Jul 2017
|Name||Advances in Intelligent Systems and Computing|
|Conference||AHFE 2017 International Conferences on Human Factors and Ergonomics in Healthcare and Medical Devices, 2017|
|Period||17/07/17 → 21/07/17|
Bibliographical notePublisher Copyright:
© Springer International Publishing AG 2018.
- Artificial neural networks
- EMG signals
- MYO devices
- Wireless communication