What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Neuroscience
- Control theory
Ferdinando A. Mussa-Ivaldi focuses on Motor control, Neuroscience, Artificial intelligence, Control theory and Communication.
His studies in Motor control integrate themes in fields like Degrees of freedom problem, Inverse dynamics, Anatomy and Set.
In the subject of general Neuroscience, his work in Central nervous system, Spinal cord, Motor cortex and Neurophysiology is often linked to Modular design, thereby combining diverse domains of study.
His research integrates issues of Basis function, Biomechanical Phenomena, Vector field and Computer vision in his study of Artificial intelligence.
Ferdinando A. Mussa-Ivaldi combines subjects such as Applied mathematics and Motor learning with his study of Control theory.
Ferdinando A. Mussa-Ivaldi works mostly in the field of Communication, limiting it down to topics relating to Horizontal plane and, in certain cases, Orientation.
His most cited work include:
- Adaptive representation of dynamics during learning of a motor task (2107 citations)
- Neural, mechanical, and geometric factors subserving arm posture in humans (913 citations)
- Computations underlying the execution of movement: a biological perspective (571 citations)
What are the main themes of his work throughout his whole career to date?
His primary areas of study are Artificial intelligence, Control theory, Motor control, Motor learning and Physical medicine and rehabilitation.
His research investigates the connection with Artificial intelligence and areas like Computer vision which intersect with concerns in Proprioception and Representation.
His work is dedicated to discovering how Control theory, Simulation are connected with Kalman filter and Motion control and other disciplines.
Motor control is a primary field of his research addressed under Neuroscience.
In his study, Hand movements and Visual feedback is inextricably linked to Communication, which falls within the broad field of Motor learning.
The Physical medicine and rehabilitation study combines topics in areas such as Rehabilitation, Cursor, Spinal cord injury and Motor skill.
He most often published in these fields:
- Artificial intelligence (29.09%)
- Control theory (23.64%)
- Motor control (23.18%)
What were the highlights of his more recent work (between 2017-2021)?
- Physical medicine and rehabilitation (24.09%)
- Perception (11.36%)
- Rehabilitation (10.00%)
In recent papers he was focusing on the following fields of study:
His main research concerns Physical medicine and rehabilitation, Perception, Rehabilitation, Adaptation and Artificial intelligence.
The concepts of his Physical medicine and rehabilitation study are interwoven with issues in Spinal cord injury and Model predictive control.
His Adaptation research also works with subjects such as
- Hemispatial neglect, which have a strong connection to Visual perception,
- Workspace together with Motor control, Manipulator, Actuator and Control system.
His Motor control study deals with the bigger picture of Control theory.
Ferdinando A. Mussa-Ivaldi has included themes like Dimension, Computer vision and Motor learning in his Artificial intelligence study.
Ferdinando A. Mussa-Ivaldi has researched Motor learning in several fields, including Sequence and State.
Between 2017 and 2021, his most popular works were:
- Development of an EMG-Controlled Serious Game for Rehabilitation (12 citations)
- Stretching the skin immediately enhances perceived stiffness and gradually enhances the predictive control of grip force. (7 citations)
- Stretching the skin immediately enhances perceived stiffness and gradually enhances the predictive control of grip force. (7 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Neuroscience
- Control theory
Ferdinando A. Mussa-Ivaldi mainly focuses on Artificial intelligence, Physical medicine and rehabilitation, Motor learning, Electromyography and Model predictive control.
His Artificial intelligence research is multidisciplinary, relying on both Dimension and Computer vision.
His study in Physical medicine and rehabilitation is interdisciplinary in nature, drawing from both Pathological and Activities of daily living.
His Motor learning study combines topics in areas such as Sequence and State.
His research in Electromyography intersects with topics in Rehabilitation, Motor control and Set.
His Model predictive control research incorporates elements of Perception, Grip force, Sensory processing, Anticipation and Illusion.
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