What is she best known for?
The fields of study she is best known for:
- Artificial intelligence
- Quantum mechanics
- Control theory
Her scientific interests lie mostly in Control theory, Body movement, Kinematics, Motor control and Movement.
Her study in the field of Sensitivity also crosses realms of Gait kinematics.
In her study, Trajectory, Statistical physics, Topological conjugacy and Racket is strongly linked to Nonlinear system, which falls under the umbrella field of Kinematics.
The concepts of her Motor control study are interwoven with issues in Machine learning, Feature and Set.
Her research in Movement intersects with topics in Duration, Rhythm, Biological neural network, Contrast and Functional neuroimaging.
Her biological study spans a wide range of topics, including Neurophysiology, Communication, Cognitive science, Taxonomy and Sequence.
Her most cited work include:
- Local Dynamic Stability Versus Kinematic Variability of Continuous Overground and Treadmill Walking (485 citations)
- Rhythmic arm movement is not discrete. (301 citations)
- Role of Hyperactive Cerebellum and Motor Cortex in Parkinson’s Disease (291 citations)
What are the main themes of her work throughout her whole career to date?
Dagmar Sternad mainly investigates Control theory, Rhythm, Communication, Motor control and Motor skill.
Her Control theory study integrates concerns from other disciplines, such as Bouncing ball dynamics, Robot, Kinematics and Racket.
In Rhythm, Dagmar Sternad works on issues like Movement, which are connected to Duration, Metronome and Contrast.
In her works, Dagmar Sternad conducts interdisciplinary research on Communication and Body movement.
Her Motor control research is multidisciplinary, relying on both Statistics, Cognitive science and Artificial intelligence.
Her research integrates issues of Cognitive psychology, Social psychology, Physical medicine and rehabilitation and Motor learning in her study of Motor skill.
She most often published in these fields:
- Control theory (28.24%)
- Rhythm (24.12%)
- Communication (16.47%)
What were the highlights of her more recent work (between 2017-2021)?
- Control theory (28.24%)
- Robot (8.24%)
- Motor skill (15.29%)
In recent papers she was focusing on the following fields of study:
Dagmar Sternad mostly deals with Control theory, Robot, Motor skill, Nonlinear system and Underactuation.
Her Control theory research is multidisciplinary, incorporating perspectives in Neural control, Mechanical impedance and Complex dynamics.
Her research investigates the connection with Complex dynamics and areas like Rendering which intersect with concerns in Kinematics.
Her Motor skill research includes elements of Sensitivity, Sequence, Generalization and Motor learning.
Throwing is closely connected to Rhythm in her research, which is encompassed under the umbrella topic of Ball release.
Dagmar Sternad combines subjects such as Movement and Artificial intelligence with her study of Simulation.
Between 2017 and 2021, her most popular works were:
- It's Not (Only) the Mean that Matters: Variability, Noise and Exploration in Skill Learning. (61 citations)
- Learning and transfer of complex motor skills in virtual reality: a perspective review (28 citations)
- Predictability, force, and (anti)resonance in complex object control. (17 citations)
In her most recent research, the most cited papers focused on:
- Artificial intelligence
- Quantum mechanics
- Neuroscience
Her primary areas of study are Motor skill, Motor learning, Movement, Artificial intelligence and Human–computer interaction.
Her Motor skill research is multidisciplinary, incorporating elements of Cognitive psychology, Generalization, Sensitivity, Noise and Sequence.
Dagmar Sternad has included themes like Stability, Degree, Speech recognition, Rhythm and Series in her Motor learning study.
Her Movement research incorporates elements of Motor activity, Neonatal intensive care unit and Physical medicine and rehabilitation.
Her Artificial intelligence research includes themes of Electrical impedance and Computer vision.
Her work on Virtual reality as part of general Human–computer interaction study is frequently linked to Dreyfus model of skill acquisition, bridging the gap between disciplines.
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