Reconocimiento de actividad personal empleando sensores a bordo de dispositivos inteligentes.
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This book presents the use of information provided from an iPhone 7 and a Myo armband device in different acquisition schemes, assessing conventional supervised classifiers to recognize personal activity by an identification of seven classes. The classifiers were trained with a generated database from eight users and were evaluated in offline mode with other two generated databases: a database with three users in each activity and a continuous user's routine with different activities. The prediction experiments were qualified by using F1-score indicator and were compared with the native prediction from the cellphone. The obtained results presented a maximum F1-score of 100% for the first validation test and 80.7% for the second validation test. In addition, although the combined use of an arm device such as the Myo armband didn't present a significant improvement on the general F1-score, its use showed an important improvement on some specific classes.