---
title: "Graph-Regularized Deep Learning for EEG-Based Emotion Recognition with Psychologically-Grounded Label Structure — Stuff That Spins"
description: "arXiv:2607.07773v1 Announce Type: new Abstract: EEG-based emotion recognition is critical for mental health monitoring and affective brain-computer interfaces,…"
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date: "2026-07-10T04:00:00+00:00"
modified: "2026-07-10T06:05:07.397199+00:00"
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# Graph-Regularized Deep Learning for EEG-Based Emotion Recognition with Psychologically-Grounded Label Structure

**Source:** Unknown  
**Published:** July 10, 2026  
**Original:** https://arxiv.org/abs/2607.07773  

## On this page

- [Overview](#overview)

<a id="overview"></a>

## Overview

arXiv:2607.07773v1 Announce Type: new Abstract: EEG-based emotion recognition is critical for mental health monitoring and affective brain-computer interfaces, yet existing deep learning approaches often treat emotion classes as isolated labels, ignoring their psychological interdependencies. We propose a graph-regularized learning framework that conceptualizes emotions as nodes in a graph where edges encode proximity based on dimensional emotion theories. We adapt three complementary regulariza

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