{"type":"ScholarlyArticle","title":"Cross-People Mobile-Phone Based Activity Recognition","authors":[{"name":"Zhongtang Zhao","slug":"zhongtang-zhao","given":"Zhongtang","family":"Zhao","affiliation":""},{"name":"Yiqiang Chen","slug":"yiqiang-chen","given":"Yiqiang","family":"Chen","affiliation":""},{"name":"Junfa Liu","slug":"junfa-liu","given":"Junfa","family":"Liu","affiliation":""},{"name":"Zhiqi Shen","slug":"zhiqi-shen","given":"Zhiqi","family":"Shen","affiliation":""},{"name":"Mingjie Liu","slug":"mingjie-liu","given":"Mingjie","family":"Liu","affiliation":""}],"abstract":"Activity recognition using mobile phones has great potential in many applications including mobile healthcare. In order to let a person easily know whether he is in strict compliance with the doctor's exercise prescription and adjust his exercise amount accordingly, we can use a smart-phone based activity reporting system to accurately recognize a range of daily activities and report the duration of each activity. A triaxial accelerometer embedded in the smart phone is used for the classification of several activities, such as staying still, walking, running, and going upstairs and downstairs. The model learnt from a specific person often cannot yield accurate results when used on a different person. To solve the cross-people activity recognition problem, we propose an algorithm known as TransEMDT (Transfer learning EMbedded Decision Tree) that integrates a decision tree and the k-means clustering algorithm for personalized activity-recognition model adaptation. Tested on a real-world data set, the results show that our algorithm outperforms several traditional baseline algorithms.","doi":"10.5591/978-1-57735-516-8/IJCAI11-423","url":"https://ijcai.org/proceedings/2011/423","pdf":"https://ijcai.org/proceedings/2011/0423.pdf","markdown":"https://ijcai.org/proceedings/2011/423.md","bibtex":"https://ijcai.org/proceedings/2011/bibtex/423","volume":{"slug":"2011","title":"Proceedings of the Twenty-Second International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2011","url":"https://ijcai.org/proceedings/2011/","year":2011,"location":"Barcelona, Catalonia, Spain","dates":"16–22 July 2011","editors":"Toby Walsh","isbn":"978-1-57735-512-0; 978-1-57735-513-7; 978-1-57735-514-4; 978-1-57735-515-1; 978-1-57735-516-8","publisher":"AAAI Press/International Joint Conferences on Artificial Intelligence","doi_prefix":""},"section":null,"track":"","number":423,"pages":{"first":2545,"last":2549},"keywords":[],"videos":[],"references":[],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}