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Object-based Activity Recognition with Heterogeneous Sensors on Wrist

EasyChair Preprint no. 341

8 pagesDate: July 14, 2018


Recent development of wearable technology has opened great opportunities for human performance evaluation applications in various domains. In order to measure the physical activities of an individual, wrist-worn sensors embedded in smart-watches, tness bands, and clip-on devices can be used to collect various types of data while the subject performs regular daily activities.In this paper we are going to explain how to achieve activities of daily living(ADLs) using a sensor device attached to a users wrist. This device contains a camera, a microphone and an accelerometer. In this experience we will collect the data from the sensors in our device and try to analyse it, in order to recognise the type of the activity. In this way we will be able to recognize ADLs that contain manual use of objects such as making a drink or cooking. Finally, we will be able to say, that the camera plays the major rule in this experience and without it would be dicult to achieve our goal. We will also suggest a method that will protect the privacy of the user, as the camera and the microphone can records part of the users private life.

Keyphrases: activity recognition, Sensors on hand, wearable sensors

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
  author = {Mohammad Albaida},
  title = {Object-based Activity Recognition with Heterogeneous Sensors on Wrist},
  howpublished = {EasyChair Preprint no. 341},

  year = {EasyChair, 2018}}
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