Activity Recognition Using Wearable Sensors for Elder Care

We propose a novel method to recognize a user¿s activities of daily living with accelerometers and RFID sensor. Two wireless accelerometers are used for the classification of 5 human body states using decision tree, and detection of RFID tagged objects with hand movement provides additional object related hand motion information. To do this, we used Bluetooth based wireless triaxial accelerometers and iGrabber which is a glove type RFID reader. Our experiments show that our method can be applicable to a real environment with strong confidence.