Category: Technology
Objective: This study aimed to assess the feasibility and efficacy of using an artificial intelligence-based chatbot for smile and speech in Parkinson’s disease (PD). Further, we explored the potential predictive value of objective face and speech parameters for motor symptoms, cognition, and mood.
Background: Approaches for objectively measuring facial expressions and speech are essential to improve telemedicine, which is widely employed for PD.
Method: In this open-label randomized study, we collected a series of face data and conversational speech from 20 participants with PD in weekly teleconsultation sessions for 5 months. We investigated the effect of daily chatbot conversations on smile and speech features.
Results: For primary outcomes, a repeated-measures analysis of variance revealed that the chatbot conversations had a significant interaction effect on the mean and standard deviation of the smile index during smile sections (both P = .02), maximum duration of the initial rise of the smile index (P = .04), and frequency of filler words (P = .04).
Conclusion: An artificial intelligence-based chatbot may positively affect smile and speech in PD.
To cite this abstract in AMA style:
G. Oyama, M. Ogawa, K. Morito, M. Kobayashi, Y. Yamada, K. Shinkawa, H. Kamo, T. Hatano, N. Hattori. The use of artificial intelligence-based chatbot in Parkinson’s disease [abstract]. Mov Disord. 2022; 37 (suppl 2). https://www.mdsabstracts.org/abstract/the-use-of-artificial-intelligence-based-chatbot-in-parkinsons-disease/. Accessed June 15, 2025.« Back to 2022 International Congress
MDS Abstracts - https://www.mdsabstracts.org/abstract/the-use-of-artificial-intelligence-based-chatbot-in-parkinsons-disease/