Knowledge management system in falling risk for physiotherapy care of elderly

Worasak Rueangsirarak, Nopasit Chakpitak, Komsak Meksamoot, Prapas Pothongsunun
2014 Signal and Information Processing Association Annual Summit and Conference (APSIPA), 2014 Asia-Pacific  
This paper describes the elderly healthcare research project affected by a fall. The decision support system is proposed as knowledge management method, including knowledge engineering to acquiring the expert's heuristically diagnostic knowledge and sharing this knowledge to the physiotherapist in the form of tool and application at the right time. This paper outlines a Knowledge Management System (KMS) to diagnose falling patterns in elderly people using Motion Capture Technology. The idea is
more » ... o integrate an appropriate procedure including case based reasoning and motion capture to provide a decision support system. The diagnosis information derived from the process of KMS helps support the physiotherapist to determine serious falling risks in the elderly and recommend guidelines for medical treatment. The evaluation result shows an efficient performance with 80.95% of precision when using the Assumption Attribute category criteria with K NNR =3. Furthermore, the result of KMS-EUCS shows a high satisfaction from the users with 97.50% of satisfaction in a community of practice scenario. This can confirm the successful of KMS approach within the falling risk screening procedure.
doi:10.1109/apsipa.2014.7041812 dblp:conf/apsipa/RueangsirarakCM14 fatcat:qlggu42qcnfb5cg7cngrmn5aiy