First steps in adaptation of an evidential network for data fusion in the framework of medical remote monitoring.
This paper presents a medical remote monitoring application which aims at detecting falls. The detection system is based on three modalities: a wearable sensor, infrared sensors and a sound analysis module. The sound analysis is presented briefly. The multimodal fusion is made using the Dempster Schaffer theory through Evidential Network. A first evaluation of the use of data mining techniques in order to extract blindly data representatives is proposed. These representatives are used to continuously increase the system performances. The system is evaluated on a local recorded data base.
TSP, Evry. paulo.cavalcante@it-sudparis.eu
P A
PA
Cavalcante
M A
MA
Sehili
M
M
Herbin
D
D
Istrate
F
F
Blanchard
J
J
Boudy
B
B
Dorizzi
D000058:Accidental Falls / Q000517:prevention & control* / Q000706:statistics & numerical data; D056044:Actigraphy / Q000379:methods*; D000465:Algorithms; D001185:Artificial Intelligence; D057225:Data Mining / Q000379:methods*; D020000:Decision Support Systems, Clinical; D006801:Humans; D018670:Monitoring, Ambulatory / Q000379:methods*; D017216:Telemedicine / Q000379:methods*