Living organisms developed in nature through the evolution process are equipped with supremely skilled and sophisticated biological functions that cannot be realized with current engineering techniques. Analysis of these mechanisms may lead to not only elucidation of biological functions but also development of a wide variety of novel engineering systems.
From the viewpoint of a scientist approaching the secrets of living organisms and from that of an engineer developing machinery useful for human kind, the members of Biological Systems Engineering laboratory work on a wide variety of projects to analyze the characteristics of biological functions from theoretical and experimental approaches employing engineering techniques aiming to find new principles peculiar to biological systems, and develop novel medical/welfare apparatuses and industrial devices by applying the elucidated principles.
Through such research activities, the students can learn in-depth knowledge about biological systems based on electricity, electronics, systems and information engineering foundation allowing themselves to become creative engineers capable of seeking a new principle and expanding it into new fields.
Biweekly lab seminar
As of 2017, total of 42 senior undergraduate students, graduate students and doctoral students are working in the lab. The students are involved in either of the four research groups according to their research projects, which are ME group (Medical engineering group), Kansei brain group (Former A-life Group), EMG Group (Biological signal analysis group), and Human modeling group (Former Biological Motion Analysis Group). Since the group each consists of students from all grades, the student can acquire the necessary knowledge and skills required fora researcher and a member of societyas well throughthe lab. activities that the senior teaches the junior and the juniors help the seniors. Since the number of students is quite large compared to the usual laboratory, the lab. is managed as the followings.
Group seminars
Regarding education, we divide the students into four research groups corresponding to each research project, andconduct education and research activities on a group-by-group basis. We promote collaboration between graduate students and undergraduate students by organize each research group with students from all grades as much as possible. We alsoencourage the students to manage the group and teach each other by their own by assigning group leaders and sub leaders.In this way, we intend not only to increase autonomy of research activities but also to cultivate leadership mindset and skills enablingsupervision of their future community.
Specific education and research guidance is conducted throughout the all-member seminar (held once a week) participated by all members including facilities and students, the group seminars (held once a week) in each group, graduation theses and master thesis presentations (held twice a year),and the workshops for respective research projects. Especially, the workshops held on a regular basis, whichis a meeting that invites the collaborators from various department, universities, public research institutions and companies, can provide valuable chances for the students tocommunicate with researchers outside the laboratory.
Biweekly lab meeting
Students' rotating representatives participate to the staff meeting biweekly held for entire laboratory management so that they can have opportunities to acquire knowledge and experience about organization management.In addition, we always try to revitalize our laboratorythrough conducting research evaluation questionnaire between students, issue of e-mail magazine (once a week), management of lab. homepage, encouragement of presentation at academic conferences both in Japan and abroad, active participation in various exhibitions, and holding laboratory tours for visitors.
There are still a lot of unknown functions and mechanisms hidden in the biological system. If we can elucidate and utilize them from engineering standpoint,then there is a possibility of creating new technologies to carve out the future of the 21st century. The Biological Systems Engineering Laboratory categorizes the broad research field of biological systems into five major research themes in order to explore specific research projects under each theme, and further functionally coordinate and fuse each theme to create novel research fields.
We develop novel signal processing algorithms that enablethe interpretation of human motions, intentions, and physiological/psychological states contained in biological signals, such as myoelectric signals, electroencephalograms, and electrocardiograms, as well as create robotic interfaces and medical welfare equipment.
We model human sensory/motor functions from electrical and electronicperspectives based on experimentally measured data, and develop novel movement support systems and next-generation automobile control systems by incorporating modeled human characteristics.
We propose new machine learning algorithms and neural networks based on probabilistic statistical theory and applythese to the development oflearning and control technologiesfor robots, medical welfare equipment, and medical data classificationtechnology.
Focusing on functions such as locomotion generation, sensation, perception, learning, and judgment, we model brain functions from an engineering viewpoint using artificial neural networks. Ultimately, we aim to model and analyze higher brain functions, especially social brain functions that understand the minds of others and live harmoniously, and Kansei that involves nonverbal, unconscious, and intuitive sensibilities. We also develop artificial life form models based on biological knowledge using the constructed brain models.
We are engaged in the research and development of novel medical support systems and medical devices through medicine-engineering collaborations by utilizing electric and electronic systems and information engineering technologies, such as biomechanical analysis technology, biological signal analysis technology, machine learning technology, and biological simulation technology that were developed in the Biological Systems Engineering laboratory.
Adopting the latest engineering technology is requisite for the medical research of the 21st century. Medical engineering is a field in which medical and engineering are integrated, and medical engineering (ME) group has been engaged in biomechanical analysis technology, biological signal analysis technology, machine learning technology, biological simulation technology to develop novel medical support systems and medical devices by exploiting electric and electronic information system technology.
Focusing on functions such as locomotion, sensation, perception, learning and judgment of the brain, Kansei Brain group tries to model and simulate its function by artificial neural network models from the viewpoint of engineering. This group ultimately aims to model and clarify nonverbal, unconscious, and intuitive ""Kansei", as well as the social brain functions that enable us to understand and cooperate with others. Employing the constracted brain models, we also develop artificial life models based on biological insights.
In the human modeling group, through technologies that extend human exercise and sensation, we aim to realize an excellent human mechanical system. In order to enjoy the daily life even at the age, we think that it is important to maintain the feeling that I am moving my body freely by myself, and feel a sense of feeling various things by myself.
When trying to produce muscle force, electrical impulses are transmitted from the brain through nerves, and the muscles discharge electricity. The measured electrical signal is called an electromyogram (EMG). There are various bioelectric signals that can be measured from the human body, such as electroencephalograms and electrocardiograms. The biological signal analysis group is engaged in the development of proprietary signal processing algorithms to identify motion intentions and the physiological/psychological states of human beings contained in their measured bioelectric signals. In addition, we have proposed novel robot interfaces and medical welfare devices using biosignals as input.
Our research results have been published in scientific journals, books, conference proceedings, patent, etc.. The numbers of publications the lab produced are shown as follows
(as of November 21, 2024):
Akira Furui, Ryota Onishi, Tomoyuki Akiyama, and Toshio Tsuji
IEEE Access, Digital Object Identifier:10.1109/ACCESS.2024.3487637, Date of Publication: 29 October 2024 (Early Access, SCI, IF=3.4)
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Kouki Kubo, Seiji Hama, Akira Furui, Tomohiko Mizuguchi, Akiko Yanagawa, Akihiko Kandori, Hiroto Sakai, Yutaro Morisako, Yuki Orino, Maho Hamai, Kasumi Fujita, Shigeto Yamawaki, and Toshio Tsuji
Heliyon, Volume 10, Issue 13, e33135, pp.1-13, doi.org/10.1016/j.heliyon.2024.e33135, 14 June 2024. (SCI, IF=3.4)
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Farina Mohamad Yusoff, Masato Kajikawa, Takayuki Yamaji, Shinji Kishimoto, Tatsuya Maruhashi, Ayumu Nakashima, Toshio Tsuji, and Yukihito Higashi
Scientific Reports, volume 14, Article number: 13704, doi.org/10.1038/s41598-024-64118-0, Published online: 14 June 2024. (SCI, IF=4.6)
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Shumma Jomyo, Akira Furui, Tatsuhiko Matsumoto, Tomomi Tsunoda, and Toshio Tsuji
IEEE Sensors Journal, Volume: 24, Issue: 11, pp.17876 – 17884, doi: 10.1109/JSEN.2024.3386333, Date of Publication: 15 April 2024. (SCI, IF=4.3)
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Zu Soh, Saki Maruko, Manaru Fujita, Shin Wakitani, Masayuki Yoshida, and Toshio Tsuji
IEEE Transactions on Instrumentation and Measurement, vol. 73, pp. 1-9, 2024, Art no. 9509209, doi: 10.1109/TIM.2024.3387502. (SCI, IF=5.6)
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Correlation Analysis Between Echinocytosis Stages and Blood Viscosity During Oxygenator Perfusion: An In Vitro Study
Shigeyuki Okahara, Satoshi Miyamoto, Zu Soh, Masaru Yoshino, Hidenobu Takahashi, Hideshi Itoh, and Toshio Tsuji
ASAIO Journal, 70(11), pp.938-945, DOI: 10.1097/MAT.0000000000002214, November 2024. (SCI, IF=3.1)
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Ziqiang Xu, Zu Soh, Yuta Kurota, Yuya Kimura, Harutoyo Hirano, Takafumi Sasaoka, Atsuo Yoshino, and Toshio TsujiScientific Reports, volume 14, Article number: 3383, doi.org/10.1038/s41598-024-53921-4, Published online: 09 February 2024. (SCI, IF=4.6) URLPDF
Satoshi Miyamoto, Zu Soh, Shigeyuki Okahara, Akira Furui, Taiichi Takasaki, Keijiro Katayama, Shinya Takahashi, and Toshio TsujiIEEE Open Journal of Engineering in Medicine and Biology, Volume: 5, pp. 66-74, DOI: 10.1109/OJEMB.2024.3350922, Date of Publication: 08 January 2024. (ESCI, IF=5.8)
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Ziqiang Xu, Reiji Anai, Harutoyo Hirano, Zu Soh and Toshio Tsuji
Frontiers in Physiology (Computational Physiology and Medicine), 14:1294239, DOI: 10.3389/fphys.2023.1294239, PUBLISHED 08 January 2024. (SCI, IF=4.0)
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T. Tsuji, P. Morasso, K. Goto, and K. Ito
Biological Cybernetics, Vol.72, pp.475-485, 1995.
T. Tsuji, O. Fukuda, H. Ichinobe, and M. Kaneko
IEEE Transactions on Systems, Man, and Cybernetics-Part C: Applications and Reviews, Vol. 29, No. 1, pp. 60-72, February 1999.
T. Tsuji, N. Bu, M. Kaneko, and O. Fukuda
IEEE Transactions on Neural Networks, Vol.14, No.2, pp.304-316, March 2003.
O. Fukuda, T. Tsuji, M. Kaneko and A. Otsuka
IEEE Transactions on Robotics and Automation, Vol.19, No.2, pp.210-222, April 2003.
H. Matsubara, H. Hirano, H. Hirano, Z. Soh, R. Nakamura, N. Saeki, M. Kawamoto, M. Yoshizumi, A. Yoshino, T. Sasaoka, S. Yamawaki, and T. Tsuji
Scientific Reports, volume 8, Article number: 3091, doi:10.1038/s41598-018-21223-11, Published online: 15 February 2018.
S. Okahara, Z. Soh, S. Miyamoto, H. Takahashi, S. Takahashi, T. Sueda, and T. Tsuji
IEEE Transactions on Biomedical Engineering, Vol.64, No.7, pp. 1503-1512, DOI:10.1109/TBME.2016.2610968, JULY 2017.
H. Hirano, R. Takama, R. Matsumoto, H. Tanaka, H. Hirano, Z. Soh, T. Ukawa, T. Takayanagi, H. Morimoto, R. Nakamura, N. Saeki, H. Hashimoto, S. Matsui, S. Kishimoto, N. Oda, M. Kajikawa, T. Maruhashi, M. Kawamoto, M. Yoshizumi, Y. Higashi, and T. Tsuji
Scientific Reports, volume 8, Article number: 9263, doi:10.1038/s41598-018-27392-3, Published online: 18 June 2018.
Z. Soh, K. Sakamoto , M. Suzuki , Y. Iino, and T. Tsuji
Scientific Reports, volume 8, Article number: 17190, doi:10.1038/s41598-018-35157-1, Published online: 21 November 2018.
A. Furui, H. Hayashi, and T. Tsuji
IEEE Transactions on Biomedical Engineering, DOI: 10.1109/TBME.2019.2895683, Date of Publication: 28 January 2019.
A. Furui, S. Eto, K. Nakagaki, K. Shimada, G. Nakamura, A. Masuda, T. Chin, and T. Tsuji
Science Robotics, Vol. 4, Issue 31, eaaw6339, DOI: 10.1126/scirobotics.eaaw6339, 26 June 2019.
T. Tsuji, S. Nakashima, H. Hayashi, Z. Soh, A. Furui, T. Shibanoki, K. Shima, and K. Shimatani
Scientific Reports, volume 10, Article number: 1422, doi:10.1038/s41598-020-57580-z, Published online: 29 January 2020.
