Multi-Modal Measurements of Mental Load

06/25/2019
by   Ingo Keller, et al.
0

This position paper describes an experiment conducted to understand the relationships between different physiological measures including pupil Diameter, Blinking Rate, Heart Rate, and Heart Rate Variability in order to develop an estimation of users' mental load in real-time (see Sidebar 1). Our experiment involved performing a task to spot a correct or an incorrect word or sentence with different difficulties in order to induce mental load. We briefly present the analysis of task performance and response time for the items of the experiment task.

READ FULL TEXT
research
08/10/2022

What's on your mind? A Mental and Perceptual Load Estimation Framework towards Adaptive In-vehicle Interaction while Driving

Several researchers have focused on studying driver cognitive behavior a...
research
09/08/2022

The Users Aren't Alright: Dangerous Mental Illness Behaviors and Recommendations

In this paper, we argue that recommendation systems are in a unique posi...
research
10/14/2019

Wearables and location tracking technologies for mental-state sensing in outdoor environments

Advances in commercial wearable devices are increasingly facilitating th...
research
09/03/2019

Efficient Real-Time Camera Based Estimation of Heart Rate and Its Variability

Remote photo-plethysmography (rPPG) uses a remotely placed camera to est...
research
08/07/2022

Bias Reducing Multitask Learning on Mental Health Prediction

There has been an increase in research in developing machine learning mo...
research
02/20/2020

MODMA dataset: a Multi-modal Open Dataset for Mental-disorder Analysis

According to the World Health Organization, the number of mental disorde...
research
03/19/2022

PhysioMTL: Personalizing Physiological Patterns using Optimal Transport Multi-Task Regression

Heart rate variability (HRV) is a practical and noninvasive measure of a...

Please sign up or login with your details

Forgot password? Click here to reset