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Shima Lab
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The lab researches ways to support people using biosignals and artificial intelligence.
AboutAbout the lab
Supporting people by combining human body mechanisms and intelligent robots
The Shima Lab combines the mechanisms of the human body with artificial intelligence, aiming to support people effectively in a wide range of situations.
The lab believes that people can be supported by properly measuring, evaluating, and using biosignals generated by human activity, such as electromyography, electroencephalography, and vital signs.
Its research is built on four pillars: artificial intelligence models, human-machine interfaces, elucidation of movement mechanisms, and evaluation of motor function and training methods.
Lab visits are accepted at any time.
Key terms
- Biosignals
- Signals generated by human activity, such as electromyography, mechanomyography, electroencephalography, and vital signs.
- Pattern classification
- Determining which of a set of predefined categories a given piece of data belongs to.
- Myoelectric prosthetic hand
- A prosthetic hand that reads the electrical signals generated when muscles move and is driven by those signals.
NewsLab news
Received the Outstanding Presentation Award at SI2025
Paper on an index for assessing cold sensitivity in young women published in BMC Women's Health
Paper on a system for evaluating lower limb function in the workplace published in IEEE Access
ResearchResearch themes
Humans are extremely complex and sophisticated information processing systems whose mechanisms are still not fully understood, and they may hold hints for supporting people efficiently. The lab aims to support people in a variety of settings by elucidating the principles behind skillful human movement and by applying intelligent robot technology equipped with artificial intelligence that thinks and makes decisions flexibly.
*Illustrative imageHigh-speed, high-accuracy pattern classification AI
Aiming at applications in medicine, welfare, and industry, the lab studies pattern recognition models, including new neural networks that incorporate probabilistic models. To put neural networks and similar models onto a single chip, it also works on hardware implementation using FPGAs.
*Illustrative imageInterfaces that operate devices with biosignals
The lab is developing new interfaces that estimate a person's movements and intentions from biosignals and can control prosthetic hands, everyday devices, and robots. Applications include five-finger myoelectric prosthetic hands and brain-machine interfaces.
*Illustrative imageElucidating movement mechanisms and mathematical models
The lab measures and analyzes body movement using bioelectrical signals such as electromyography (EMG), mechanomyography (MMG), and electroencephalography (EEG), as well as accelerometers and magnetic sensors. To clarify what biosignals reflect and how humans move, it is building human models that represent sensation, neural function, and the workings of the musculoskeletal system.
*Illustrative imageTechnologies supporting the evaluation and training of motor function
The lab applies biosignal analysis to medicine, developing systems that support physicians' diagnoses and therapists' rehabilitation, and aiming to make new discoveries about diseases and functional impairments. Examples include a fall prevention method using virtual walls and Parkinson's disease evaluation based on finger-tapping analysis.
MembersFaculty
The members of the Shima Lab consist of faculty members, project faculty members, JSPS Research Fellows, PhD, master's, and undergraduate students, and administrative assistants.As of 2026
- ProfessorKeisuke Shima
- Project Associate ProfessorNaoki Kuzuya
- Specially Appointed Faculty (Assistant Professor)Takayuki Mukaida
- Specially Appointed Faculty (Assistant Professor)Tianyi Wang
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Report an errorAbout the images
The top and research theme images are illustrative and were not taken at the lab. They are cropped from Wikimedia Commons images. Cropped CC BY-SA images are provided under the same CC BY-SA license as the original (version shown on each line).
- Top image: “EMG - SIMI” D. Gordon E. Robertson / CC BY-SA 3.0 (cropped)
- High-speed, high-accuracy pattern classification AI: “Face Recognition Field Test at Südkreuz 12” This image is a work by Wikipedia and Wikimedia Commons user C.Suthorn. When reusing, credit me as described in the Licensing information below. I would appreciate being notified (wikimail, talk page, , Social Media) if you use my work outside Wikimedia. Do not copy this image illegally by ignoring the terms of the license below, as it is not in the public domain. If you would like special permission to use, license, or purchase the image please contact me to negotiate terms. More of my work can be found in my personal gallery or at my Peertube channel. A prepared attribution especially for use in Social Media and Print (newspapers, flyers, books, murals, mousepads, mugs, posters, t-shirts) can be copied here / CC BY-SA 4.0 (cropped)
- Interfaces that operate devices with biosignals: “Brain-computer interface experiment” Laurens R. Krol / CC BY 4.0 (cropped)
- Elucidating movement mechanisms and mathematical models: “Biomechanics human model in MOCAP system” El gato Tito / CC BY 4.0 (cropped)
- Technologies supporting the evaluation and training of motor function: “A Vietnamese doctor examines a patient at the Rehabilitation and Vocational Training Center at Qui Nhon” SP5 Roy Tronnes / Public domain (cropped)
- Related lab (Otsuka Lab (Multimodal Information Processing Lab)): “Eye-tracking setup” Naomi Nota / CC BY-SA 2.0 (cropped)
- Related lab (Shirakawa Lab): “UPS Power Management Module, racks with network cabling in NERSC data center” Derrick Coetzee from Berkeley, CA, USA / CC0 (cropped)
- Related lab (Yoshioka-Sasaki Lab): “Network-cables-1” HenryNewman12 / CC BY-SA 4.0 (cropped)
- Related lab (Nakata Lab): “Island population model of an evolutionary algorithm” Studi90 / CC BY-SA 4.0 (cropped)
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