S. Shinohara

发表

Evaluation of emotional arousal level and depression severity using the centripetal force derived from voice

S. Tokuno, A. Yoshino, Mitsuteru Nakamura, 2020, medRxiv.

Effectiveness of a Voice-Based Mental Health Evaluation System for Mobile Devices: Prospective Study

S. Tokuno, Mitsuteru Nakamura, S. Shinohara, 2020, JMIR formative research.

Accuracy Evaluation for Mental Health Indicator Based on Vocal Analysis in Noisy Environments

S. Tokuno, Mitsuteru Nakamura, S. Shinohara, 2018 .

Evaluation of turn alternation in pill bugs using omnidirectional motion compensator ANTAM

Yusaku Ogai, S. Shinohara, Toru Moriyama, 2022, Artificial Life and Robotics.

Connecting the free energy principle with quantum cognition

Y. Gunji, V. Basios, S. Shinohara, 2022, Frontiers in Neurorobotics.

Detectionof Major Depressive Disorder Based on a Combination of Voice Features: An Exploratory Approach

S. Tokuno, H. Toda, Mitsuteru Nakamura, 2022, International journal of environmental research and public health.

Mental Health Assessment Method Based on Emotion Level Derived from Voice

S. Tokuno, A. Yoshino, H. Toda, 2020 .

The Influence of the Voice Acquisition Method to the Mental Health State Estimation Based on Vocal Analysis

S. Tokuno, S. Shinohara, Yasuhiro Omiya, 2018, IFMBE Proceedings.

Mental status assessment of disaster relief personnel by vocal affect display based on voice emotion recognition

S. Tokuno, S. Shinohara, Yasuhiro Omiya, 2017, Disaster and Military Medicine.

Correlation between self-administered psychological test and emotion measured by voice analysis

S. Tokuno, S. Shinohara, Yasuhiro Omiya, 2016 .

Validity of mental health check by voice compared to psychological test ( General Health Questionnaire 30 )

S. Tokuno, S. Shinohara, Yasuhiro Omiya, 2015 .

Evaluation of the Severity of Major Depression Using a Voice Index for Emotional Arousal

S. Tokuno, A. Yoshino, Mirai So, 2020, Sensors.

A Loosely Symmetric Model of Cognition

Tatsuji Takahashi, Shuji Shinohara, Kuratomo Oyo, 2009, European Conference on Artificial Life.

Study on Depression Evaluation Indicator in the Elderly using Sensibility Technology

Yasuhiro Omiya, Naoki Hagiwara, Shuji Shinohara, 2017, ICT4AgeingWell.

Inverse Bayesian inference as a key of consciousness featuring a macroscopic quantum logical structure

Vasileios Basios, Yukio-Pegio Gunji, Shuji Shinohara, 2017, Biosyst..

Self-incremental learning vector quantization with human cognitive biases

Ung-il Chung, Tatsuji Takahashi, Yu Chen, 2021, Scientific Reports.

Efficient Learning of Word Meanings by Agents Using Biases Observed in Language Development of Children

Kouichi Katsurada, Yurie Iribe, Shuji Shinohara, 2007 .

On Autonomous Coordination of Learning Biases by an Agent with a Vocabulary Learning Mechanism

Tsuneo Nitta, Kouichi Katsurada, Takashi Hashimoto, 2007 .

Implementation of Biases Observed in Children's Language Development into Agents

Tsuneo Nitta, Kouichi Katsurada, Shuji Shinohara, 2006, EELC.

Simulation of foraging behavior using a decision-making agent with Bayesian and inverse Bayesian inference: Temporal correlations and power laws in displacement patterns

Y. Nakajima, Ung-il Chung, S. Shinohara, 2021, bioRxiv.

Linguistic representation of vowels in speech imagery EEG

R. Taguchi, Y. Iribe, J. Horikawa, 2023, Frontiers in Human Neuroscience.

Development of an automatic turntable-type multiple T-maze device and observation of pill bug behavior.

Kazuyuki Morioka, Nobuhito Manome, Toru Moriyama, 2020, The Review of scientific instruments.

An Attempt to Estimate Depressive Status from Voice

Yasuhiro Omiya, Takeshi Takano, Shuji Shinohara, 2019, MindCare.

Difference in Speech Analysis Results by Coding

Yasuhiro Omiya, Naoki Hagiwara, Takeshi Takano, 2018 .

Validity of mind monitoring system as a mental health indicator using voice

Masakazu Higuchi, Yasuhiro Omiya, Naoki Hagiwara, 2017 .

Lévy Walk in Swarm Models Based on Bayesian and Inverse Bayesian Inference

Yukio-Pegio Gunji, Hisashi Murakami, Takeshi Kawai, 2020, Computational and structural biotechnology journal.

CLASSIFICATION OF BIPOLAR DISORDER, MAJOR DEPRESSIVE DISORDER, AND HEALTHY STATE USING VOICE

Masakazu Higuchi, Yasuhiro Omiya, Naoki Hagiwara, 2018, Asian Journal of Pharmaceutical and Clinical Research.

Depressive Mood Assessment Method Based on Emotion Level Derived from Voice: Comparison of Voice Features of Individuals with Major Depressive Disorders and Healthy Controls

S. Tokuno, A. Yoshino, H. Toda, 2021, International journal of environmental research and public health.

Simple Modification of the Upper Confidence Bound Algorithm by Generalized Weighted Averages

Ung-il Chung, S. Shinohara, Nobuhito Manome, 2023, ArXiv.

Extended Bayesian inference incorporating symmetry bias

Tatsuji Takahashi, Yoshihiro Nakajima, Kouta Suzuki, 2019, bioRxiv.

Inverse square Levy walk emerging universally in goal-oriented tasks

Ung-il Chung, Y. Gunji, S. Shinohara, 2023, ArXiv.

A new method of Bayesian causal inference in non-stationary environments

Hiroshi Okamoto, Tatsuji Takahashi, Yoshihiro Nakajima, 2019, bioRxiv.

Emergence and collapse of money through reciprocity

Yukio-Pegio Gunji, Shuji Shinohara, Y. Gunji, 2001, Appl. Math. Comput..

Testing the power-law hypothesis of the interconflict interval

Budrul Ahsan, S. Shinohara, Iku Yoshimoto, 2023, Scientific reports.

Feasibility Study for Estimation of Depression Severity using Voice Analysis

Yasuhiro Omiya, Takeshi Takano, Shuji Shinohara, 2018, 2018 IEEE International Conference on Bioinformatics and Biomedicine (BIBM).

Machine Translation from Japanese to Robot Language for Human-Friendly Communication

Kouta Suzuki, Shuji Shinohara, Shunji Mitsuyoshi, 2020, HCI.