What is he best known for?
The fields of study he is best known for:
- Internal medicine
- Artificial intelligence
- Surgery
His scientific interests lie mostly in Electroencephalography, Neuroscience, Somatosensory evoked potential, Artificial intelligence and Spinal cord.
Yong Hu has included themes like Signal-to-noise ratio, Alpha and Motor skill in his Electroencephalography study.
His Signal-to-noise ratio study combines topics in areas such as Amplitude, Speech recognition and Latency.
The Neuroscience study combines topics in areas such as Pain perception and Plasticity.
His Artificial intelligence study frequently draws connections to adjacent fields such as Pattern recognition.
His study looks at the intersection of Spinal cord and topics like Scoliosis surgery with Rachis and Biomedical engineering.
His most cited work include:
- A novel approach for enhancing the signal-to-noise ratio and detecting automatically event-related potentials (ERPs) in single trials (123 citations)
- Biomechanical and electromyographic evaluation of ankle foot orthosis and dynamic ankle foot orthosis in spastic cerebral palsy. (92 citations)
- The primary somatosensory cortex largely contributes to the early part of the cortical response elicited by nociceptive stimuli (90 citations)
What are the main themes of his work throughout his whole career to date?
His scientific interests lie mostly in Somatosensory evoked potential, Artificial intelligence, Neuroscience, Spinal cord and Physical medicine and rehabilitation.
His studies deal with areas such as Spinal cord injury, Latency, Biomedical engineering and Time–frequency analysis as well as Somatosensory evoked potential.
His biological study spans a wide range of topics, including Brain–computer interface, Electroencephalography, Speech recognition, Computer vision and Pattern recognition.
The study incorporates disciplines such as Alpha, Cognition and Audiology in addition to Electroencephalography.
His Spinal cord course of study focuses on Diffusion MRI and Myelopathy.
His biological study deals with issues like Low back pain, which deal with fields such as Electromyography.
He most often published in these fields:
- Somatosensory evoked potential (19.21%)
- Artificial intelligence (18.10%)
- Neuroscience (18.32%)
What were the highlights of his more recent work (between 2015-2021)?
- Artificial intelligence (18.10%)
- Neuroscience (18.32%)
- Somatosensory evoked potential (19.21%)
In recent papers he was focusing on the following fields of study:
His primary areas of investigation include Artificial intelligence, Neuroscience, Somatosensory evoked potential, Electroencephalography and Pattern recognition.
His Artificial intelligence study combines topics from a wide range of disciplines, such as Machine learning and Computer vision.
His study on Somatosensory evoked potential also encompasses disciplines like
- Spinal cord injury which connect with Anesthesia,
- Single trial which is related to area like Latency and Spinal cord demyelination.
Yong Hu interconnects Alpha, Primary motor cortex, Audiology and Phase synchronization in the investigation of issues within Electroencephalography.
His Pattern recognition study incorporates themes from Brain–computer interface and Data set.
Yong Hu focuses mostly in the field of Spinal cord, narrowing it down to matters related to Diffusion MRI and, in some cases, Nuclear magnetic resonance.
Between 2015 and 2021, his most popular works were:
- Nonadiabatic Holonomic Quantum Computation with Dressed-State Qubits (57 citations)
- A soft stretchable bending sensor and data glove applications (43 citations)
- A novel stimulation method for multi-class SSVEP-BCI using intermodulation frequencies. (25 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Internal medicine
- Surgery
Yong Hu spends much of his time researching Artificial intelligence, Spinal cord injury, Pattern recognition, Neuroscience and Electroencephalography.
His work deals with themes such as Machine learning and Flicker, which intersect with Artificial intelligence.
His Spinal cord injury research incorporates elements of Osteotomy, Somatosensory evoked potential, Intraoperative neurophysiological monitoring and Physical medicine and rehabilitation.
His study on Somatosensory evoked potential is covered under Anesthesia.
He combines subjects such as Modulation, Telecommunications, Brain–computer interface and Data set with his study of Pattern recognition.
His research in the fields of Rehabilitation, Beta Rhythm and Cognition overlaps with other disciplines such as Degenerated intervertebral disc.
This overview was generated by a machine learning system which analysed the scientist’s
body of work. If you have any feedback, you can
contact us
here.
