# Quantitative EEG for Predicting Upper Limb Motor Recovery in Chronic Stroke Robot-Assisted Rehabilitation

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/quantitative-eeg-for-predicting-upper-limb-motor-recovery-in-chronic-stroke/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Paula Trujillo,Alfonso Mastropietro,Alessandro Scano,Andrea Chiavenna,Simona Mrakic‐Sposta,Marco Caimmi,Franco Molteni,Giovanna Rizzo |
| Citations | 93 |
| DOI | 10.1109/tnsre.2017.2678161 |
| Fields | Medicine,Neuroscience |
| Open Access | false |
| OA Status | closed |
| OpenAlex ID | https://openalex.org/W2593234372 |
| PMID | 28278477 |
| Type | article |
| Year | 2017 |

## Paper authors

- [Alessandro Scano](https://scholariq.org/researchers/alessandro-scano/)

## Paper journal

- [IEEE Transactions on Neural Systems and Rehabilitation Engineering](https://scholariq.org/journals/ieee-transactions-on-neural-systems-and-rehabilitation-engineering/)

## Paper primary topic

- [EEG and Brain-Computer Interfaces](https://scholariq.org/topics/eeg-and-brain-computer-interfaces/)

## Paper topics

- [EEG and Brain-Computer Interfaces](https://scholariq.org/topics/eeg-and-brain-computer-interfaces/)
- [Stroke Rehabilitation and Recovery](https://scholariq.org/topics/stroke-rehabilitation-and-recovery/)
- [Neuroscience and Neural Engineering](https://scholariq.org/topics/neuroscience-and-neural-engineering/)

---
Source: ScholarIQ — public research metadata, principally OpenAlex. See https://scholariq.org/sources/ for provenance and https://scholariq.org/methodology/ for what these figures mean.