Papers - Mitsukura, Yasue

Advanced Sensors for Mechatronics

Naoki Oda, Toshiaki Tsuji, Yasue Mitsukura, Takahiro Ishikawa, Yuta Tawaki, Toshiyuki Murakami, Satoshi Suzuki, Yasutaka Fujimoto

Mechatronics and Robotics (CRC Press)  1st Edition   33 - 50 2020

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Sensors and actuators are key technologies to develop industrial products and to achieve social innovation. In particular, intelligent sensor applications are important to improve system reliability and safety. To achieve the sophisticated and advanced system, because the compromise among the information processing and the regulating system of each node through the network of sensors and actuators becomes so important, it is necessary to develop a new and emerging research area of sensors and actuators technology. The key issues are summarized as: advanced vision-based control application, advanced tactile sensing, advanced electroencephalography, advanced human motion sensing, and advanced approaches for human motion detection. The chapter describes the techniques for tactile sensors. It describes the classification of tactile sensing techniques followed by descriptions of techniques in each classification. The chapter illustrates human preference detection by simple electroencephalography.

Special issue on brain machine/computer interface and its application

Shoichiro Fujisawa, Minoru Fukumi, Jianting Cao, Yasue Mitsukura, and Shin-ichi Ito

Journal of Robotics and Mechatronics ( Fuji Technology Press Ltd. )  Vol. 32 ( Issue 4 ) 723 2020

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Brain machine/computer interface (BMI/BCI) technologies are based on analyzing brain activity to control machines and support the communication of commands and messages. To sense brain activities, a functional NIRS and electroencephalogram (EEG) that has been developed for that purpose is often employed. Analysis techniques and algorithms for the NIRS and EEG signals have also been created, and human support systems in the form of BMI/BCI applications have been developed. In the field of rehabilitation, BMI/BCI is used to control environment control systems and electric wheelchairs. In medicine, BMI/BCI is used to assist in communications for patient support. In industry, BMI/BCI is used to analyze sensibility and develop novel games.

This special issue on Brain Machine/Computer Interface and its Application includes six interesting papers that cover the following topics: an EEG analysis method for human-wants detection, cognitive function using EEG analysis, auditory P300 detection, a wheelchair control BCI using SSVEP, a drone control BMI based on SSVEP that uses deep learning, and an improved CMAC model.

We thank all authors and reviewers of the papers and the Editorial Board of Journal of Robotics and Mechatronics for its help with this special issue.

センシングとモニタリングによる QoL 維持のための行動効果検証

満倉靖恵

O plus E: Optics+ electronics Vol.42 ( No.3 ) 368 - 373 2020

KANSEI Detection and Its Application Using the EEG: Widespread of KANSEI Research in Society

満倉靖恵

IEICE ESS Fundamentals Review (一般社団法人 電子情報通信学会)  13 ( 3 ) 180 - 186 2020

Brain Visualization: Evaluate the Effect of Lipid Intake on Stress by Quantitative Evaluation Using Brain Function and Electrocardiographic Measurement

満倉靖恵

Oleoscience (公益社団法人 日本油化学会)  20 ( 11 ) 499 - 505 2020

How Users of a Smartphone Weather Application Are Influenced by Animated Announcements Conveying Rainfall Intensity and Electronic Gifts Promoting Rain Evacuation

Nakajima Hiroko, Shimazaki Kan, Ishigaki Yang, Miyajima Akiko, Kuriyama Akira, Iwanami Koyuru, Mitsukura Yasue

Journal of Disaster Research (Fuji Technology Press Ltd.)  14 ( 9 ) 1236 - 1244 2019.12

Accepted,  ISSN  18812473

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<p>In this study, we assumed that animated announcements that conveyed rainfall intensity of localized heavy rain and the distribution of electronic gifts to encourage rain evacuation would promote evacuation actions. If evacuation actions could be promoted through these methods, then the transmission of weather information could be improved. Therefore, we modified the features of a weather information application for smartphones, which was already widely used, and conducted a demonstrative experiment with application users who agreed to participate in order to check the validity. We analyzed users’ behaviors by transmitting information regarding the predicted start time of rain and recording the Global Positioning System coordinates of the users’ smartphones. In addition, a questionnaire survey was administered to the users after the experiment to collect data on their conception of rainfall intensity. The participants were also interviewed. The results of the experiment showed a significant difference in user conception of rainfall intensity depending on whether they had viewed the animation. However, a behavior analysis based on location data showed no statistical bias in the relationship between the animation and rain evacuation behavior.</p>

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Elucidating effects of short wavelength light on the body using biological signals

Miyazawa R., Sasai K., Ayaki M., Mitsukura Y.

IECON Proceedings (Industrial Electronics Conference) (IECON Proceedings (Industrial Electronics Conference))  2019-October   5376 - 53814 2019.10

Accepted,  ISSN  9781728148786

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© 2019 IEEE. This study aimed to clarify the influence on the body caused by the light stimulation of short wavelength light being transmitted to the hypothalamus in the brain through the retinal hypothalamic tract. And the brain waves of the prefrontal cortex reflecting the function of the hypothalamus and melatonin secretion are compared at the time of receiving short wavelength light and at the time of blocking short wavelength light. Short wavelength light refers to light of blue component with a wavelength of 380-495 nm. This component is often contained in the light from the screen of the electronic device and the light of the LED lighting. In recent years, the opportunity for exposure to short wavelength light has increased due to the increase in usage time of electronic devices and the spread of LED lighting. However, it is said that short wavelength light affects the control of the biological rhythm of the day. This is because the absorption band of photoreceptors involved in the biological clock is equal to the wavelength band of short wavelength light. The nighttime light response of this photoreceptor has been confirmed to suppress the secretion of the sleepiness hormone melatonin and the accompanying decrease in sleepiness, but the light response during time zones other than nighttime and the effect on the brain other than sleepiness due to it is unknown. We compared brain wave and the amount of melatonin secretion in the case of receiving light from tablet terminal which contains a lot of short wavelength light components directly and receiving light through glasses which shields short wavelength light. And We elucidated the effects of short wavelength light on the body by detecting differences. As a result of electroencephalogram analysis, it was revealed that the power spectrum of \boldsymbol{\beta} and \boldsymbol{\beta}/\boldsymbol{\alpha} bands in the morning and \boldsymbol{\delta} band in the night decreased by the reception of short wavelength light. In addition, the results of melatonin secretion suggested that the short wavelength light suppressed melatonin production, so that morning light reception reduced stress and night light reception decreased sleepiness.

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Analysis of the Influence of Lung Function Decline on Brain Function using Brain Healthcare Quotient

Watanabe H., Fukunaga K., Ikaga T., Mitsukura Y.

IECON Proceedings (Industrial Electronics Conference) (IECON Proceedings (Industrial Electronics Conference))  2019-October   5353 - 5357 2019.10

Accepted,  ISSN  9781728148786

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© 2019 IEEE. In this paper, we used Brain Healthcare Quotient (BHQ) to analyze the influence of lung function on brain function. A large-scale survey was conducted for the purpose. In the measurement survey, magnetic resonance images were acquired, and BHQ was calculated and used as brain function. As lung function, we measured forced vital capacity (FVC) and calculated forced expiratory volume 1.0 sec (FEV1.0%). As a result of analysis, it became clear that the decrease in FEV1.0% affects GM BHQ and that the decrease in lung function also affects brain function by using BHQ.

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A Robust Table Detection Method for Distortion in Image Acquired from Camera

Nakaigawa T., Mashiyama Y., Mitsukura Y., Hamada N.

IECON Proceedings (Industrial Electronics Conference) (IECON Proceedings (Industrial Electronics Conference))  2019-October   5347 - 5352 2019.10

Accepted,  ISSN  9781728148786

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© 2019 IEEE. In this paper, the robust table detection method for distortion is proposed in image acquired by camera. Images acquired by the camera contain distortion due to the curvature of the paper and it makes difficult to detect the table in images. In order to address this issue, a method of dividing the frame line of the table in the vertical direction and the horizontal direction and detecting the frame lines by curve approximation in each direction is proposed. Dividing the frame lines in each direction, it is possible to simplify the multiple curve detection. As a result, the lines detection accuracy in the curved surface image was 99.4%. In addition, similar results were obtained for curved images rotated by 90°. This method can cope with distortion in both the vertical and horizontal directions. From these results, it was confirmed the effectiveness of the proposed method.

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Facial Landmark Activity Features for Depression Screening

Sumali B., Mitsukura Y., Tazawa Y., Kishimoto T.

2019 58th Annual Conference of the Society of Instrument and Control Engineers of Japan, SICE 2019 (2019 58th Annual Conference of the Society of Instrument and Control Engineers of Japan, SICE 2019)     1376 - 1381 2019.09

Accepted,  ISSN  9784907764678

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© 2019 The Society of Instrument and Control Engineers - SICE. Depression is the most common mood disorder in the world which is also the leading cause of suicide. Depression might be diagnosed using varying modalities, as it affects many aspects of the patient, not only the patient will appear melancholic, but the patient's sleep quality and life quality might also be disrupted. In this study, we aim to extract facial landmark features unique to depression patients and build a machine learning model to classify the depression severity. The facial landmark activities considered in this study include: speed statistics of the landmarks, the standard deviation of eye pupils, and statistical features of mouth area. We found several facial landmark activity features with significant differences between healthy volunteers and depressed patients. We also successfully built machine learning models for automatic depression severity prediction.

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Analysis of Prefrontal Single-Channel EEG Data for Portable Auditory ERP-Based Brain–Computer Interfaces

Ogino M., Kanoga S., Muto M., Mitsukura Y.

Frontiers in Human Neuroscience (Frontiers in Human Neuroscience)  13   250 2019.07

Accepted,  ISSN  1662-5161

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© Copyright © 2019 Ogino, Kanoga, Muto and Mitsukura. An electroencephalogram (EEG)-based brain-computer interface (BCI) is a tool to non-invasively control computers by translating the electrical activity of the brain. This technology has the potential to provide patients who have severe generalized myopathy, such as those suffering from amyotrophic lateral sclerosis (ALS), with the ability to communicate. Recently, auditory oddball paradigms have been developed to implement more practical event-related potential (ERP)-based BCIs because they can operate without ocular activities. These paradigms generally make use of clinical (over 16-channel) EEG devices and natural sound stimuli to maintain the user's motivation during the BCI operation; however, most ALS patients who have taken part in auditory ERP-based BCIs tend to complain about the following factors: (i) total device cost and (ii) setup time. The development of a portable auditory ERP-based BCI could overcome considerable obstacles that prevent the use of this technology in communication in everyday life. To address this issue, we analyzed prefrontal single-channel EEG data acquired from a consumer-grade single-channel EEG device using a natural sound-based auditory oddball paradigm. In our experiments, EEG data was gathered from nine healthy subjects and one ALS patient. The performance of auditory ERP-based BCI was quantified under an offline condition and two online conditions. The offline analysis indicated that our paradigm maintained a high level of detection accuracy (%) and ITR (bits/min) across all subjects through a cross-validation procedure (for five commands: 70.0 ± 16.1 and 1.29 ± 0.93, for four commands: 73.8 ± 14.2 and 1.16 ± 0.78, for three commands: 78.7 ± 11.8 and 0.95 ± 0.61, and for two commands: 85.7 ± 8.6 and 0.63 ± 0.38). Furthermore, the first online analysis demonstrated that our paradigm also achieved high performance for new data in an online data acquisition stream (for three commands: 80.0 ± 19.4 and 1.16 ± 0.83). The second online analysis measured online performances on the different day of offline and first online analyses on a different day (for three commands: 62.5 ± 14.3 and 0.43 ± 0.36). These results indicate that prefrontal single-channel EEGs have the potential to contribute to the development of a user-friendly portable auditory ERP-based BCI.

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Simple Stress Quantitative Evalution for Healthcare Using Daily KANSEI Detection with EEG Device - Relation between Stress and Healthcare

Yasue Mitsukura, Brian Sumali, Yuuki Tazawa, Taishiro, Kishimoto, and Masaru Mimura

Modern Environmental Science and Engineering  2019.07

Research paper (scientific journal), Joint Work

脳波測定器を用いた上下振動に対する不快度の定量評価に関する研究 その1 脳波測定の基礎実験

三輪田吾郎，石川理都子，山中昌之，江村勝，中塚光一，満倉靖恵

環境工学 I 2019   483 - 484 2019.07

冬季の室内温熱環境が脳健康指標に及ぼす影響に関する横断調査及び縦断調査 住環境が脳機能に及ぼす影響に関する実測調査 (その8)

松本実紗，伊香賀俊治，山川義徳，内田泰史，村上周三，安藤真太朗，満倉靖恵

環境工学 I 2019   169 - 170 2019.07

脳波測定器を用いた上下振動に対する不快度の定量評価に関する研究 その2 アンケート分析結果

石川理都子，三輪田吾郎，山中昌之，柏俣明子，下田亮太，満倉靖恵

環境工学 I    485 - 486 2019.07

簡易脳波計測を用いた住宅の寒暖とストレスの関係調査 住環境が脳機能に及ぼす影響に関する実測調査 その10

渡邉秀斗，満倉靖恵，伊香賀俊治，山川義徳，安藤真太朗

環境工学 I    173 - 174 2019.07

住宅内温熱環境が脳機能・呼吸機能に与える影響および相互解析 住環境が脳機能に及ぼす影響に関する実測調査 その9

満倉靖恵，渡邉秀斗，伊香賀俊治，山川義徳，内田泰史，安藤真太朗，福永興壱

環境工学 I    171 - 172 2019.07

Sleep Stage Detection Using only Heart Rate

Yasue Mitsukura, Koichi Fukunaga, Masato Yasui, and Masaru Mimura

Health Informatics Journal (Health Informatics Journal)  26 ( 1 ) 376 - 387 2019.02

Research paper (scientific journal), Joint Work, Accepted,  ISSN  14604582

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© The Author(s) 2019. Getting enough quality sleep plays a vital role in protecting our mental health, physical health, and quality of life. Sleep deprivation can make it difficult to concentrate on daily activities, and lower sleep quality is associated with hypertension, hyperglycemia, and hyperlipidemia. The amount of sleep we get is important, but in recent years, quality sleep has also been deemed significant. Polysomnography, which has been the gold standard in assessing sleep quality based on stages, requires that the subject be attached to electrodes, which can disrupt sleep. An easier method to objectively measure sleep is therefore needed. The aim of this study was to construct an easy and objective sleep stage monitoring method. A cross-sectional study for healthy subjects has been done in our research. A new easy model for monitoring the sleep stages is built on only heart rate calculated by the electrocardiogram. This enabled us to easily assess the sleep quality based on five stages. This experiment included a total of 50 subjects. The overall accuracy in determining the five sleep stages was 66.0 percent. Four stages for sleep are identified accurately compared with other conventional methods. Despite there are no five sleep stage separation method using only heart rate, our method achieved the five separation for sleep with a relatively good accuracy. This study represents a great contribution to the field of sleep science. Because sleep stages can be recognized by the heart rate alone, sleep can be noninvasively assessed with any heart rate meter. This method will make it easier to determine sleep stages and diagnose sleep disorders.

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Actigraphy for Evaluation of Mood Disorders: A Systematic Review and Meta-Analysis

Yuuki Tazawa, Masataka Wada, Yasue Mitsukura, Akihiro Takamiya, Momoko Kitazawa, Michitaka Yoshimura, Masaru Mimura, and Taishiro Kishimoto

Journal of Affective Disorders (Journal of Affective Disorders)  253   257 - 269 2019.01

Research paper (scientific journal), Joint Work, Accepted,  ISSN  01650327

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© 2019 Background: Actigraphy has enabled consecutive observation of individual health conditions such as sleep or daily activity. This study aimed to examine the usefulness of actigraphy in evaluating depressive and/or bipolar disorder symptoms. Method: A systematic review and meta-analysis was conducted. We selected studies that used actigraphy to compare either patients vs. healthy controls, or pre- vs. post-treatment data from the same patient group. Common actigraphy measurements, namely daily activity and sleep-related data, were extracted and synthesized. Results: Thirty-eight studies (n = 3,758) were included in the analysis. Compared with healthy controls, depressive patients were less active (standardized mean difference; SMD=1.27, 95%CI=[0.97, 1.57], P<0.001) and had longer wake after sleep onset (SMD= − 0.729, 95%CI=[− 1.20, − 0.25], p = 0.003). Total sleep time (SMD= − 0.33, 95%CI=[− 0.55, − 0.11], P = 0.004), sleep latency (SMD= − 0.22, 95%CI=[− 0.42, − 0.02], P = 0.032), and wake after sleep onset (SMD= − 0.22, 95%CI=[− 0.39, − 0.04], P = 0.015) were longer in euthymic/remitted patients compared to healthy controls. In pre- and post-treatment comparisons, sleep latency (SMD=− 0.85, 95%CI=[− 1.53, − 0.17], P = 0.015), wake after sleep onset (SMD= − 0.65, 95%CI=[− 1.20, − 0.10], P = 0.022), and sleep efficiency (SMD=0.77, 95%CI=[0.29, 1.24], P = 0.002) showed significant improvement. Limitation: The sample sizes for each outcome were small. The type of actigraphy devices and patients’ illness severity differed across studies. It is possible that hospitalizations and medication influenced the outcomes. Conclusion: We found significant differences between healthy controls and mood disorders patients for some actigraphy-measured modalities. Specific measurement patterns characterizing each mood disorder/status were also found. Additional actigraphy data linked to severity and/or treatment could enhance the clinical utility of actigraphy.

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耳鳴・聴覚過敏の他覚的検査法 脳波検査

MITSUKURA YASUE

JOHNS 35 ( 1 ) 31 - 36 2019

Research paper (scientific journal), Joint Work, Accepted