It has been claimed that wearable devices are useful for healthcare applications by providing functionalities such as idle alerts, pedometer, heart-rate measurement, and calorie calculation. However, these functionalities have the limitations of providing only passive assistance. In order to prompt users to do physical activities, we developed a prototype application for active assistance, which works on smartwatch devices. It guides users to stretch their arms periodically during their daily lives. For effective guidance, we integrated motion recognition and gamification elements. We performed a user study to confirm the usefulness of our approach.
|Title of host publication||Entertainment Computing - 15th IFIP TC 14 International Conference, ICEC 2016, Proceedings|
|Editors||Rainer Malaka, Günter Wallner, Hyun-Seung Yang, Helmut Hlavacs, Simone Kriglstein, Artur Lugmayr|
|Number of pages||6|
|Publication status||Published - 2016|
|Event||15th IFIP TC 14 International Conference on Entertainment Computing, ICEC 2016 - Vienna, Austria|
Duration: 2016 Sept 28 → 2016 Sept 30
|Name||Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)|
|Other||15th IFIP TC 14 International Conference on Entertainment Computing, ICEC 2016|
|Period||16/9/28 → 16/9/30|
Bibliographical noteFunding Information:
This work was supported by Institute for Information & Communications Technology Promotion (IITP) grant funded by the Korea government (MSIP) (No. R0115-15-1011) and the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIP) (No. NRF-2016R1A2B3014319).
© IFIP International Federation for Information Processing 2016.
- Hidden Markov Model
- Motion recognition
- Physical activity
ASJC Scopus subject areas
- Theoretical Computer Science
- Computer Science(all)