Automatic ADL classification using 3-axial accelerometers and RFID sensor

This paper presents a new method for recognizing the activities of daily living (ADL) based on the state-dependent motion analysis using three accelerometers and a glove type RFID reader. Two accelerometers are used for the classification of five body states based on the decision tree. Classification of the instrumental activities is performed based on the hand interaction with an object ID using an accelerometer and a RFID reader. Hand movements when using objects are classified into five classes in advance and final decision combines the body state and the instrumental activities. Experiment shows that the suggested hierarchical motion analysis provides accuracy rate of over 90% for all 20 ADLs.