We aim to identify the neural/mechanical interventions and underlying mechanisms for improving motor skills and facilitating motor learning/rehabilitation through integrative approaches. We examine neural activity, motor output (e.g., neural excitability, muscle activity, and limb/hand movement), and memory with various interventions in young and old individuals, including clinical populations (e.g., amputees, stroke survivors).
Keywords: Neuroscience, Neural Engineering, Human Augmentation, Human-Robot Interaction, Rehabilitation, Sports Science, Sports Medicine, Motor Control, Motor Learning
Open to students who are interested in conducting research for multiple semesters. Students with computational skills (coding) are preferred. Sorry, no high school students or foreign undergraduate students.
Neuromechanical Mechanisms for Motor Skills
- Autonomic nervous system and neuromotor activity
- Modulations of neuromotor oscillations
- Human-Robot interaction
Neural Plasticity with Practice
- Facilitation of motor learning and rehabilitation
- Improvement of human-machine interaction
- Wearable robot
- Shinohara is recognized as a Star Reviewer for the Journal of Applied Physiology by the American Physiological Society (December 2022)
- McCamish Blue Sky Research Grant awarded to develop a novel rehabilitation strategy for Parkinson’s disease (July 2022)
- Shinohara has been re-elected as a Council member (secretary) of the International Society of Electrophysiology & Kinesiology (June 2022)
- Georgia Tech Research News: Robotically Enhanced Mental Practice May Improve Post-Stroke Rehab (October 2021)
- NIH/NINDS grant awarded to study robotically-augmented mental practice (July 2021)
- Tutorial Lecture for Japanese Society of Physical Fitness and Sports Medicine, Kitakyushu, Japan (June 2021)
- Collaboration grant on sports medicine registry awarded from Shriners Hospitals for Children (March 2021)
- Collaborative study on human augmentation robot starts, funded by Army Research Lab (March 2021)
- Collaboration on the assessment of low back muscle health starts, funded by Defense Health Agency (November, 2020)
- IEN Center for Human-Centric Interfaces and Engineering (Center for HCIE) established, funded by Georgia Tech Institute for Electronics and Nanotechnology (October 2020)
- Nayef’s study on anti-phase cocontraction practice published in Experimental Brain Research (January 2020) https://twitter.com/ExpBrainRes/status/1204264043264872448
- Keynote Speaker at Japan Society of Mechanical Engineering: Sports Engineering and Human Dynamics, Japan (October 2019)
- Vasiliy’s study on brain excitability published in Experimental Brain Research (May 2019).
- Workshop Speaker on Human Neuromuscular Augmentation at International Symposium on Medical Robotics (April 2019).
- NIH/NINDS grant awarded to study transcutaneous vagus nerve stimulation (August 2018)
- Symposium Speaker on Ultrasound Elastgoraphy at International Society of Electrophysiology and Kinesiology (July 2018).
- Collaborative study with engineers on ultrasound-based prosthetic finger control featured in Georgia Tech News, interviewed by IEEE Spectrum, and listed as one of the Best Medical Technologies of 2017 by Medgadjet (December 2017). See YouTube Video.
- Shino’s invited commentary “Active Voice: Fight Between Your Muscles – Beat Common Drive for Steady Cocontraction” was published in Sports Medicine Bulletin of the American College of Sports Medicine (October 2017).
- Nayef’s study featured as “Mind Over Muscles: How the Brain Hinders Individual Muscle Control” in Georgia Tech News (June 2017)
- Ahmar NE, Ueda J, Shinohara M. Anti-phase cocontraction practice attenuates in-phase low-frequency oscillations between antagonistic muscles as assessed with phase coherence. Experimental Brain Research 238: 63-72, 2020.
- Buharin VE & Shinohara M. Corticospinal excitability for flexor carpi radialis decreases with baroreceptor unloading during intentional co-contraction with opposing forearm muscles. Experimental Brain Research 237:1947-195, 2019.
- Brown E, Yoshitake Y, Shinohara M, Ueda J. Automatic analysis of ultrasound shear-wave elastography in skeletal muscle without non-contractile tissue contamination. International Journal of Intelligent Robotics and Applications 2: 209-225, 2018.
- Yoshitake Y, Ikeda A, Shinohara M. Robotic finger perturbation training improves finger postural steadiness and hand dexterity. Journal of Electromyography and Kinesiology 38:208-214, 2018.
- Ahmar NE & Shinohara M. Slow intermuscular oscillations are associated with cocontraction steadiness. Medicine & Science in Sports & Exercise, 49: 1955–1964, 2017.
- Kim E, Kovalenko I, Lacey I, Shinohara M, Ueda J. Timing analysis of robotic neuromodulatory rehabilitation system for paired associative stimulation. IEEE Robotics and Automation Letters 1 : 1028-1035, 2016.