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Автор: Parkka Juha, Ermes Miikka, Korpipaa Miikka, Mantyjarvi Jani, Peltola Johannes, Korhonen Ilkka
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Ключові слова:
сенсори, сенсоры ; поняття, понятия, concepts ; класифікація, классификация, classification
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Анотація:
Automatic classification of everyday activities can be used for promotion of health-enhancing physical activities and a healthier lifestyle. In this paper, methods used for classification of everyday activities like walking, running, and cycling are described. The aim of the study was to find out how to recognize activities, which sensors are useful and what kind of signal processing and classification is required. A large and realistic data library of sensor data was collected. Sixteen test persons took part in the data collection, resulting in approximately 31 h of annotated, 35-channel data recorded in an everyday environment. The test persons carried a set of wearable sensors while performing several activities during the 2-h measurement session. Classification results of three classifiers are shown: custom decision tree, automatically generated decision tree, and artificial neural network. The classification accuracies using leaveone- subject-out cross validation range from 58 to 97% for custom d
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