Mami Noguchi

NTT (Japan)

Papers

1

Total Citations

14

H-Index

1

About

Mami Noguchi is a researcher at the forefront of ubiquitous computing and health monitoring, with a particular focus on early detection of cognitive decline. Her key research areas include human-robot interaction, ambient sensing, and the application of machine learning to behavioral data for healthcare. Noguchi’s most notable contribution is her pioneering work in automatically assessing dementia risk through non-intrusive, everyday interactions. In her highly cited 2019 paper, she proposed a novel method to predict high or low scores on a dementia scale by integrating two distinct data streams: a participant's interaction behavior with a humanoid robot and their indoor daily activity patterns. This approach, which has garnered 14 citations, demonstrates a significant step toward scalable, in-home cognitive health screening. By moving assessment from clinical settings to natural living environments, Noguchi’s work holds profound implications for aging populations, offering a path toward earlier intervention and improved quality of life through continuous, unobtrusive monitoring.

Research Focus

Key Achievements

1
H-Index
1
Papers
14
Total Citations
14
Avg Citations/Paper
🏆 Most Cited Paper
Dementia Scale Classification Based on Ubiquitous Daily Activity and Interaction Sensing
14 citations · 2019
📈 Most Prolific Year: 2019 (1 Papers)
🤝 Key Collaborators: 4
🏛 Institutions: NTT (Japan)

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 11 days ago