TY - GEN
T1 - Comparative analysis of artificial hydrocarbon networks and data-driven approaches for human activity recognition
AU - Ponce, Hiram
AU - de Lourdes Martínez-Villaseñor, María
AU - Miralles-Pechúan, Luis
N1 - Publisher Copyright:
© Springer International Publishing Switzerland 2015.
PY - 2015
Y1 - 2015
N2 - In recent years computing and sensing technologies advances contribute to develop effective human activity recognition systems. In contextaware and ambient assistive living applications, classification of body postures and movements, aids in the development of health systems that improve the quality of life of the disabled and the elderly. In this paper we describe a comparative analysis of data-driven activity recognition techniques against a novel supervised learning technique called artificial hydrocarbon networks (AHN). We prove that artificial hydrocarbon networks are suitable for efficient body postures and movements classification, providing a comparison between its performance and other well-known supervised learning methods.
AB - In recent years computing and sensing technologies advances contribute to develop effective human activity recognition systems. In contextaware and ambient assistive living applications, classification of body postures and movements, aids in the development of health systems that improve the quality of life of the disabled and the elderly. In this paper we describe a comparative analysis of data-driven activity recognition techniques against a novel supervised learning technique called artificial hydrocarbon networks (AHN). We prove that artificial hydrocarbon networks are suitable for efficient body postures and movements classification, providing a comparison between its performance and other well-known supervised learning methods.
KW - Artificial hydrocarbon networks
KW - Artificial organic networks
KW - Classification
KW - Human activity recognition
KW - Supervised learning
KW - Wearable sensors
UR - https://www.scopus.com/pages/publications/84952333273
U2 - 10.1007/978-3-319-26401-1_15
DO - 10.1007/978-3-319-26401-1_15
M3 - Conference contribution
AN - SCOPUS:84952333273
SN - 9783319264004
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 150
EP - 161
BT - Ubiquitous Computing and Ambient Intelligence
A2 - García-Chamizo, Juan M.
A2 - Fortino, Giancarlo
A2 - Ochoa, Sergio F.
PB - Springer Verlag
T2 - 9th International Conference on Ubiquitous Computing and Ambient Intelligence, UCAmI 2015
Y2 - 1 December 2015 through 4 December 2015
ER -
