What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Internal medicine
- Electromyography
His primary areas of investigation include Electromyography, Motor unit, Anatomy, Signal and Physical medicine and rehabilitation.
His Electromyography study incorporates themes from Electrophysiology, Nerve conduction velocity, Muscle contraction and Isometric exercise.
His Motor unit research includes themes of Tibialis anterior muscle, Motor unit recruitment, Artificial intelligence and Pattern recognition.
His biological study spans a wide range of topics, including Average rectified value, Internal medicine, Biomedical engineering and Vastus medialis.
His Signal study combines topics from a wide range of disciplines, such as Acoustics, Sensitivity, Algorithm and Amplitude.
His Physical medicine and rehabilitation research incorporates elements of Rehabilitation, Physical therapy and Brain–computer interface.
His most cited work include:
- The extraction of neural strategies from the surface EMG (1105 citations)
- The Extraction of Neural Information from the Surface EMG for the Control of Upper-Limb Prostheses: Emerging Avenues and Challenges (450 citations)
- Rehabilitation of gait after stroke: a review towards a top-down approach. (324 citations)
What are the main themes of his work throughout his whole career to date?
Electromyography, Motor unit, Physical medicine and rehabilitation, Artificial intelligence and Neuroscience are his primary areas of study.
His work in Electromyography tackles topics such as Anatomy which are related to areas like Trapezius muscle.
His studies examine the connections between Motor unit and genetics, as well as such issues in Signal, with regards to Surface.
His research in Physical medicine and rehabilitation tackles topics such as Brain–computer interface which are related to areas like Movement.
His Artificial intelligence research is multidisciplinary, relying on both Electroencephalography, Speech recognition, Computer vision and Pattern recognition.
He does research in Neuroscience, focusing on Stimulation specifically.
He most often published in these fields:
- Electromyography (32.45%)
- Motor unit (26.43%)
- Physical medicine and rehabilitation (21.63%)
What were the highlights of his more recent work (between 2017-2021)?
- Electromyography (32.45%)
- Motor unit (26.43%)
- Physical medicine and rehabilitation (21.63%)
In recent papers he was focusing on the following fields of study:
His primary scientific interests are in Electromyography, Motor unit, Physical medicine and rehabilitation, Artificial intelligence and Neuroscience.
The Electromyography study combines topics in areas such as Spinal cord injury, Wearable computer, Decoding methods, Robustness and Biomedical engineering.
The Motor unit study combines topics in areas such as Isometric exercise, Cardiology, Nerve conduction velocity, Motor neuron and Tibialis anterior muscle.
His Physical medicine and rehabilitation research is multidisciplinary, incorporating elements of Rehabilitation, Bionics, Wrist, Sensory system and Neuroplasticity.
The study incorporates disciplines such as Sensitivity, Signal, Computer vision and Pattern recognition in addition to Artificial intelligence.
His Neuroscience research is multidisciplinary, relying on both Transmission and Plasticity.
Between 2017 and 2021, his most popular works were:
- You are as fast as your motor neurons: speed of recruitment and maximal discharge of motor neurons determine the maximal rate of force development in humans (69 citations)
- Simultaneous control of multiple functions of bionic hand prostheses: Performance and robustness in end users. (67 citations)
- Simultaneous control of multiple functions of bionic hand prostheses: Performance and robustness in end users. (67 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Internal medicine
- Statistics
His primary areas of study are Motor unit, Physical medicine and rehabilitation, Electromyography, Artificial intelligence and Pattern recognition.
His Motor unit research includes elements of Muscle force, Motor neuron, Nerve conduction velocity and Isometric exercise.
He interconnects Neuroplasticity, Chronic pain and Amputation, Phantom limb in the investigation of issues within Physical medicine and rehabilitation.
Dario Farina has included themes like Amplitude, Decoding methods, Neurorehabilitation and Motor control in his Electromyography study.
His studies in Artificial intelligence integrate themes in fields like Proportional myoelectric control, Kinematics and Time domain.
The concepts of his Pattern recognition study are interwoven with issues in Signal, Interfacing and Surface.
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