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2021 Fiscal Year Final Research Report

Deep Learning the Human Mind - Recognising and Augmenting Cognitive Performance Fluctuations

Research Project

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Project/Area Number 18H03278
Research Category

Grant-in-Aid for Scientific Research (B)

Allocation TypeSingle-year Grants
Section一般
Review Section Basic Section 61020:Human interface and interaction-related
Research InstitutionKeio University

Principal Investigator

Kunze Kai  慶應義塾大学, メディアデザイン研究科(日吉), 教授 (00648040)

Project Period (FY) 2018-04-01 – 2022-03-31
KeywordsCognitive Augmentation / Wearable Computing / Adaptable Interfaces / Cognitive Fluctuations
Outline of Final Research Achievements

This project provides tools to quantify and manage properties of our mind better using physiological sensing (from sleep, over cognitive load, towards problems related to motion/cyber-sickness and accessibility issues). In a first step, we implemented several methods to assess cognitive fluctuations using unobtrusive physiological sensing and deep learning/machine learning techniques. Highlights include the detection of sleep onset, sleep quality, alertness (while driving), and cognitive load changes. In a second step, we implemented interactions to improve or manage these cognitive fluctuations, highlights include a nap assistant, Increased situational awareness while driving, and a reduction in motion- cyber sickness.
We also developed two novel paradigms: Cognitive Augmentation and Human Computer Integration, for implementing systems that are more integrated with the human body. Overall, we present significant contributions to the human computer interaction and related fields.

Free Research Field

Human Computer Interaction

Academic Significance and Societal Importance of the Research Achievements

Our project introduces the novel paradigm of cognitive augmentation. We enable a tighter feedback loop taking the user’s real time cognition model into account. Making systems more accessible. Accessibility is a core concept emphasized in nearly all 17 of the UN’s SDGs.

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Published: 2023-01-30  

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