Computer Science ›› 2016, Vol. 43 ›› Issue (Z11): 151-155.doi: 10.11896/j.issn.1002-137X.2016.11A.033

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Method of Human Activity Recognition Based on Feature Enhancement and Decision Fusion

HUAN Ruo-hong and CHEN Yue   

  • Online:2018-12-01 Published:2018-12-01

Abstract: Activity recognition via tri-axial accelerometer has been a research focus in the fields of sensor data proces-sing and pattern recognition.In some cases,it is difficult to distinguish the similar acceleration data,especially the data of walking,ascending stairs and descending stairs,which makes it difficult to recognize those three activities correctly.In this paper,a method of activity recognition based on feature enhancement and decision fusion was proposed for recognizing similar activities such as walking,ascending stairs and descending stairs,which is implemented by enhancing a part of features and decision fusing several classification results.Experimental results show that the method can overcome the situations of low correct recognition rate and high recognition error due to the similarity of acceleration data,and effectively improve the correct recognition rate of human activity and distinguish human activities in actual applications in real time.

Key words: Tri-axial accelerometer,Activity recognition,Feature enhancement,Decision fusion

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