# NeuroTaskManager: Using BCI to improve Worker's Health

Emile Savalle, Marc J.-M. Macé, Léa Pillette, Ferran Argelaguet, Anatole Lécuyer, Thorsten O Zander, Marius Klug

► To cite this version:

Emile Savalle, Marc J.-M. Macé, Léa Pillette, Ferran Argelaguet, Anatole Lécuyer, et al. Neuro-TaskManager: Using BCI to improve Worker's Health. CORTICO 2025 - 7e édition des Journées CORTICO (COllectif pour la Recherche Transdisciplinaire sur les Interfaces Cerveau-Ordinateur), May 2025, Lyon, France. pp.1-2, 2025. hal-05428558

HAL Id: hal-05428558

https://hal.science/hal-05428558v1

Submitted on 22 Dec 2025

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Distributed under a Creative Commons Attribution 4.0 International License
# NeuroTask Manager
Leveraging BCI and VR to improve workers' mental health

Emile Savalle¹, Marc J-M Macé¹, Léa Pillette¹, Ferran Argelaguet²,
Anatole Lécuyer², Thorsten O.Zander³ and Marius Klug³

¹Univ. Rennes, Inria, CNRS, IRISA ²Inria, Univ. Rennes, IRISA, CNRS ³BTU Cottbus-Senftenberg

## Issue

An inadequate job can lead to

* Boredom & alienation: when tasks are too easy

* Stress & fatigue: when task are too demanding
  ⇒ Due to task assignments based solely on performance

**Improving task assignments could improve mental health**

## Research questions

A mismanaged cognitive workload negatively impacts health

➤ (H1) Can we use pBCI-based workload measurement to assign jobs or tasks?

Executive functions can explain the variability in tasks' affinities and performances

➤ (H2) Does executive functions elicit measurable and usable differences in the brain activity ?

## Paradigm

### Simulated workplace

* Immersive virtual environment

* Conveyor belt delivering objects

* Controller triggers to solve tasks

<figure><img src="image_2.png" /></figure>

### Tasks

Tasks designed to elicit executive functions [1]

1. **Inhibition**
   Go/NoGo task: Suppressing automatic responses

2. **Updating**
   N-Back task: Refreshing working memory

3. **Shifting**
   Color-Shape task: Switching between task or rules

3 levels of difficulty

### User models

Understanding the relationship with tasks

1. **Performance**
   * Goal: Find tasks with best performance

* Metrics: Accuracy, mistakes

2. **Workload**
   * Goal: Finding best fit for participant

* Target: average level of workload

* Metrics: EEG measure of workload [2]

**Output**: Selection of a subset of 3 tasks

## Experimental plan

<table><thead><tr><th colspan="4">Calibration</th></tr><tr><th>Difficulty</th><th>Task 1</th><th>Task 2</th><th>Task 3</th></tr></thead><tbody><tr><td>Low</td><td>Inhibition</td><td>Shifting</td><td>Updating</td></tr><tr><td>Medium</td><td>Shifting</td><td>Updating</td><td>Inhibition</td></tr><tr><td>High</td><td>Updating</td><td>Inhibition</td><td>Shifting</td></tr></tbody></table>

* 3mn each

* Order of task randomized

<figure><img src="image_3.png" /></figure>

* 10mn each

* Order of difficulty and model counterbalanced

## Recorded metrics

Calibration:

* NASA-TLX

* pBCI workload

* Performance

Validation:

* Performance

* Fatigue

* Model comparison

* Preference, stress,...

## Results

### H1 – Assigning tasks with pBCI

<figure><img src="image_4.png" /></figure>

**Workload model mitigate fatigue while conserving performance**

**However!**

Issues with pBCI workload classifier:

* No correlation with difficulty or NASA-TLX

**=> Future experiments are required to validate the results**

### H2 – Observing executive functions

1. **Power frequency analysis**
   ⇒ Strong impact of task on EEG

* Ex: Frontal theta

2. **Correlation between tasks**
   Significant correlation between executive functions

⇒ Similar as theoretical framework [1]

3. **Classification**
   Riemannian geometry

* Calibration data to train validation to test

⇒ Within subject: 42%

⇒ Between subject: 44%

⇒ Random estimated at 38%

<figure><img src="image_5.png" /><figcaption>Theoretical framework[1]</figcaption></figure>

<figure><img src="image_6.png" /><figcaption>Frontal activity</figcaption></figure>

<figure><img src="image_7.png" /></figure>

## Conclusion

1. Assigning tasks using a pBCI based workload measure could help worker's mental health

2. Eliciting different executive functions is reflected in brain activity

* Correlation confirming A. Miyake framework[1]

* Differences sufficient for above chance level classification

## References

1. Miyake, Akira, et al. 2000

2. Zhang, X., Krol, L. R., & Zander, T. O. 2018

<figure><img src="image_8.png" /></figure>

<figure><img src="image_9.png" /></figure>

IRISA

<figure><img src="image_10.png" /></figure>

cnrs

<figure><img src="image_11.png" /></figure>

Université
de Rennes

<figure><img src="image_12.png" /></figure>

Brandenburg
University of Technology
Cottbus - Senftenberg