Using Hidden Markov Models to Build Behavioural Models to Detect the Onset of Dementia

Nidal AlBeiruti*, Khalid Al-Begain

*Awdur cyfatebol y gwaith hwn

Allbwn ymchwil: Pennod mewn Llyfr/Adroddiad/Trafodion CynhadleddCyfraniad i gynhadleddadolygiad gan gymheiriaid

Crynodeb

Innovative methodologies to provide care for the elderly people in their homes form an emerging and evolving field of research. Proactive care for Dementia is an important challenge that should be researched. Using Ambient Intelligence (AmI) solutions, different data modalities can be collected from home settings. Suggested solutions are concentrating on providing behaviour monitoring or telemonitoring solutions that are apt to support and help the clinicians' and carers' decision making in addition to helping family members to receive assurance about their relatives. We are using Hidden Markov Models in order to build a behavioural model based on raw sensor data. Although binary simple sensors are used, the resulting model can detect abnormalities, sudden and gradual, in elderly people's behaviour, which may be considered an indicator of dementia. The role of the suggested system is to raise an alarm whenever a behavioural change is detected and to leave decision making to the carer.

Iaith wreiddiolSaesneg
Teitl2014 SIXTH INTERNATIONAL CONFERENCE ON COMPUTATIONAL INTELLIGENCE, COMMUNICATION SYSTEMS AND NETWORKS (CICSYN)
CyhoeddwrInstitute of Electrical and Electronics Engineers
Tudalennau18-26
Nifer y tudalennau9
Dynodwyr Gwrthrych Digidol (DOIs)
StatwsCyhoeddwyd - 2014
DigwyddiadInternational Conference on Computational Intelligence, Communication Systems and Networks - Tetovo
Hyd: 27 May 201429 May 2014

Cynhadledd

CynhadleddInternational Conference on Computational Intelligence, Communication Systems and Networks
DinasTetovo
Cyfnod27/05/1429/05/14

Ôl bys

Gweld gwybodaeth am bynciau ymchwil 'Using Hidden Markov Models to Build Behavioural Models to Detect the Onset of Dementia'. Gyda’i gilydd, maen nhw’n ffurfio ôl bys unigryw.

Dyfynnu hyn