TY - GEN
T1 - LINE Chatbot for Recording Elderly Cognition to Screen Cognitive Impairment
AU - Li, Zi Yi
AU - Tjandra, Agatha Maisie
AU - Chen, Chien Hsu
N1 - Publisher Copyright:
© 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
PY - 2023
Y1 - 2023
N2 - The elderly population is growing, and with that the number of people suffering from dementia, which has become the seventh leading cause of death among all diseases. Early detection of symptoms is crucial for effective treatment of dementia. However, people with dementia often do not realize their symptoms in the early stage. To tackle this problem, a study aims to use the LINE chat platform to design a chatbot system for recognizing the early stages of dementia. The system is based on cognitive assessments in a conversational form, and the conversations between the elderly and the bot are recorded. This provides family members with an easy-to-use interface to track the records and receive recommendations about the elderly's dementia status. The study was conducted in two stages: user research and user testing. The first stage involved expert interviews and discussions with the elderly and their family members to understand their perspectives on dementia and their experience with the LINE and AD8 questionnaire. The second stage involved designing a chatbot-based cognitive assessment prototype and pilot implementation. The results showed that the interactive chatbot-based assessments were attractive to the elderly and enhanced their engagement. The long-term records of the elderly also made it easier for family members to understand the cognitive changes. The study has the potential to increase awareness of dementia by using chatbots to integrate with the elderly and family members to detect dementia early.
AB - The elderly population is growing, and with that the number of people suffering from dementia, which has become the seventh leading cause of death among all diseases. Early detection of symptoms is crucial for effective treatment of dementia. However, people with dementia often do not realize their symptoms in the early stage. To tackle this problem, a study aims to use the LINE chat platform to design a chatbot system for recognizing the early stages of dementia. The system is based on cognitive assessments in a conversational form, and the conversations between the elderly and the bot are recorded. This provides family members with an easy-to-use interface to track the records and receive recommendations about the elderly's dementia status. The study was conducted in two stages: user research and user testing. The first stage involved expert interviews and discussions with the elderly and their family members to understand their perspectives on dementia and their experience with the LINE and AD8 questionnaire. The second stage involved designing a chatbot-based cognitive assessment prototype and pilot implementation. The results showed that the interactive chatbot-based assessments were attractive to the elderly and enhanced their engagement. The long-term records of the elderly also made it easier for family members to understand the cognitive changes. The study has the potential to increase awareness of dementia by using chatbots to integrate with the elderly and family members to detect dementia early.
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U2 - 10.1007/978-3-031-34866-2_26
DO - 10.1007/978-3-031-34866-2_26
M3 - Conference contribution
AN - SCOPUS:85171424067
SN - 9783031348655
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 366
EP - 375
BT - Human Aspects of IT for the Aged Population - 9th International Conference, ITAP 2023, Held as Part of the 25th HCI International Conference, HCII 2023, Proceedings
A2 - Gao, Qin
A2 - Zhou, Jia
PB - Springer Science and Business Media Deutschland GmbH
T2 - 9th International Conference on Human Aspects of IT for the Aged Population, ITAP 2023, held as part of the 25th International Conference on Human-Computer Interaction, HCII 2023
Y2 - 23 July 2023 through 28 July 2023
ER -