TY - JOUR
T1 - SlimMe, a Chatbot With Artificial Empathy for Personal Weight Management
T2 - System Design and Finding
AU - Rahmanti, Annisa Ristya
AU - Yang, Hsuan Chia
AU - Bintoro, Bagas Suryo
AU - Nursetyo, Aldilas Achmad
AU - Muhtar, Muhammad Solihuddin
AU - Syed-Abdul, Shabbir
AU - Li, Yu Chuan Jack
N1 - Funding Information:
This study was financially supported by Beasiswa Unggulan Scholarship funded by the Ministry of Education and Culture, Republic of Indonesia, Ministry of Education (MOE), ROC Taiwan (grant number DP2-111-21121-01-A-02), and the Ministry of Science and Technology, ROC Taiwan (grant numbers: MOST 110-2320-B- 1222 038 -029 -MY3, 110-2221-E-038 -002 -MY2, and 110-2622-E-038 1223 -003 -CC1).
Funding Information:
The authors would like to thank all SlimMe TMU-MIT Hackathon team members Hanas Subakti, Emily, Yang, and Firdani Rianda Putra. We would also like to express our gratitude to all mentors from TMU-MIT (Sana) Hackathon 2017.
Publisher Copyright:
Copyright © 2022 Rahmanti, Yang, Bintoro, Nursetyo, Muhtar, Syed-Abdul and Li.
PY - 2022/6/23
Y1 - 2022/6/23
N2 - As the obesity rate continues to increase persistently, there is an urgent need to develop an effective weight loss management strategy. Nowadays, the development of artificial intelligence (AI) and cognitive technologies coupled with the rapid spread of messaging platforms and mobile technology with easier access to internet technology offers professional dietitians an opportunity to provide extensive monitoring support to their clients through a chatbot with artificial empathy. This study aimed to design a chatbot with artificial empathic motivational support for weight loss called “SlimMe” and investigate how people react to a diet bot. The SlimMe infrastructure was built using Dialogflow as the natural language processing (NLP) platform and LINE mobile messenger as the messaging platform. We proposed a text-based emotion analysis to simulate artificial empathy responses to recognize the user's emotion. A preliminary evaluation was performed to investigate the early-stage user experience after a 7-day simulation trial. The result revealed that having an artificially empathic diet bot for weight loss management is a fun and exciting experience. The use of emoticons, stickers, and GIF images makes the chatbot response more interactive. Moreover, the motivational support and persuasive messaging features enable the bot to express more empathic and engaging responses to the user. In total, there were 1,007 bot responses from 892 user input messages. Of these, 67.38% (601/1,007) of the chatbot-generated responses were accurate to a relevant user request, 21.19% (189/1,007) inaccurate responses to a relevant request, and 10.31% (92/1,007) accurate responses to an irrelevant request. Only 1.12% (10/1,007) of the chatbot does not answer. We present the design of an artificially empathic diet bot as a friendly assistant to help users estimate their calorie intake and calories burned in a more interactive and engaging way. To our knowledge, this is the first chatbot designed with artificial empathy features, and it looks very promising in promoting long-term weight management. More user interactions and further data training and validation enhancement will improve the bot's in-built knowledge base and emotional intelligence base.
AB - As the obesity rate continues to increase persistently, there is an urgent need to develop an effective weight loss management strategy. Nowadays, the development of artificial intelligence (AI) and cognitive technologies coupled with the rapid spread of messaging platforms and mobile technology with easier access to internet technology offers professional dietitians an opportunity to provide extensive monitoring support to their clients through a chatbot with artificial empathy. This study aimed to design a chatbot with artificial empathic motivational support for weight loss called “SlimMe” and investigate how people react to a diet bot. The SlimMe infrastructure was built using Dialogflow as the natural language processing (NLP) platform and LINE mobile messenger as the messaging platform. We proposed a text-based emotion analysis to simulate artificial empathy responses to recognize the user's emotion. A preliminary evaluation was performed to investigate the early-stage user experience after a 7-day simulation trial. The result revealed that having an artificially empathic diet bot for weight loss management is a fun and exciting experience. The use of emoticons, stickers, and GIF images makes the chatbot response more interactive. Moreover, the motivational support and persuasive messaging features enable the bot to express more empathic and engaging responses to the user. In total, there were 1,007 bot responses from 892 user input messages. Of these, 67.38% (601/1,007) of the chatbot-generated responses were accurate to a relevant user request, 21.19% (189/1,007) inaccurate responses to a relevant request, and 10.31% (92/1,007) accurate responses to an irrelevant request. Only 1.12% (10/1,007) of the chatbot does not answer. We present the design of an artificially empathic diet bot as a friendly assistant to help users estimate their calorie intake and calories burned in a more interactive and engaging way. To our knowledge, this is the first chatbot designed with artificial empathy features, and it looks very promising in promoting long-term weight management. More user interactions and further data training and validation enhancement will improve the bot's in-built knowledge base and emotional intelligence base.
KW - artificial empathy
KW - artificial intelligence
KW - chatbot
KW - diet bot
KW - virtual diet assistant
KW - weight loss management
UR - http://www.scopus.com/inward/record.url?scp=85134007209&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85134007209&partnerID=8YFLogxK
U2 - 10.3389/fnut.2022.870775
DO - 10.3389/fnut.2022.870775
M3 - Article
AN - SCOPUS:85134007209
SN - 2296-861X
VL - 9
JO - Frontiers in Nutrition
JF - Frontiers in Nutrition
M1 - 870775
ER -