# A machine learning approach to classify working memory load from optical neuroimaging data

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/a-machine-learning-approach-to-classify-working-memory-load-from-optical/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Manob Jyoti Saikia,Shiba Kuanar,Debanjan Borthakur,Maria Vinti,Thupten Tendhar |
| Citations | 14 |
| DOI | 10.1117/12.2578952 |
| Fields | Engineering,Medicine,Neuroscience |
| Open Access | false |
| OA Status | closed |
| OpenAlex ID | https://openalex.org/W3134014885 |
| Type | conference-paper |
| Year | 2021 |

## Paper authors

- [Maria Vinti](https://scholariq.org/researchers/maria-vinti/)

## 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/)
- [Optical Imaging and Spectroscopy Techniques](https://scholariq.org/topics/optical-imaging-and-spectroscopy-techniques/)
- [Non-Invasive Vital Sign Monitoring](https://scholariq.org/topics/non-invasive-vital-sign-monitoring/)

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