Emanuele Francesco Russo
Biographic Data
| ID | 7870673 |
|---|---|
| NAME | Emanuele Francesco Russo |
| GIVEN NAMES | Emanuele Francesco |
| FAMILY NAME | Russo |
| SIGNATURE | RUSSO E F |
| AFFILIATIONS | Padre Pio Foundation and Rehabilitation Centers, 71013 San Giovanni Rotondo, Italy |
| ORCID | 0009-0005-2958-602X |
| VERIFIED | Yes |
| TOTAL WORKS | 2 |
| TOTAL CITATIONS | 0 |
| AUTHOR COUNT | 2 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2022 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 0 |
Machine learning and deep learning applied to EEG and fNirs for early autism spectrum disorder diagnosis: A systematic review
The results demonstrated the potential of DL and ML algorithms applied to EEG and fNIRS signals for early ASD assessment, supporting the development of personalized intervention strategies grounded in robust neurophysiological evidence
Psychophysiological Assessment of Children with Cerebral Palsy during Robotic-Assisted Gait Training through Infrared Imaging
Cerebral palsy (CP) is a non-progressive neurologic pathology representing a leading cause of spasticity and concerning gait impairments in children. Robotic-assisted gait training (RAGT) is widely employed to treat this pathology to improve children's gait pattern. Importantly, the effectiveness of the therapy is strictly related to the engagement of the patient in the rehabilitation process, which depends on his/her psychophysiological state. T…
No prominent works on this page.
Psychophysiological Assessment of Children with Cerebral Palsy during Robotic-Assisted Gait Training through Infrared Imaging
Cerebral palsy (CP) is a non-progressive neurologic pathology representing a leading cause of spasticity and concerning gait impairments in children. Robotic-assisted gait training (RAGT) is widely employed to treat this pathology to improve children's gait pattern. Importantly, the effectiveness of the therapy is strictly related to the engagement of the patient in the rehabilitation process, which depends on his/her psychophysiological state. T…
Machine learning and deep learning applied to EEG and fNirs for early autism spectrum disorder diagnosis: A systematic review
The results demonstrated the potential of DL and ML algorithms applied to EEG and fNIRS signals for early ASD assessment, supporting the development of personalized intervention strategies grounded in robust neurophysiological evidence
Autism (1 works) · Autism spectrum disorder (1 works) · Autism Spectrum Disorder Research (1 works) · Cerebral palsy (1 works) · Deep learning (1 works) · Electroencephalography (1 works) · Electronic nose (1 works) · Functional Brain Connectivity Studies (1 works) · Gait (1 works) · Gait training (1 works)