To be or not to be in flow at work: physiological classification of flow using machine learning

R Rissler, M Nadj, MX Li, N Loewe… - IEEE transactions on …, 2020 - ieeexplore.ieee.org
The focal role of flow in promoting desirable outcomes in companies, such as increased
employees' well-being and performance, led scholars to study flow in the context of work …

Are we in the zone? exploring the features and method of detecting simultaneous flow experiences based on eeg signals

B Zhang, X Li, Y Zhou, J Liu, C Zhou, W Liu… - Proceedings of the ACM …, 2024 - dl.acm.org
When executing interdependent personal tasks for the team's purpose, simultaneous
individual flow (simultaneous flow) is the antecedent condition of achieving shared team …

Flow in human-robot collaboration—multimodal analysis and perceived challenge detection in industrial scenarios

P Prajod, M Lavit Nicora, M Mondellini… - Frontiers in Robotics …, 2024 - frontiersin.org
Introduction: Flow state, the optimal experience resulting from the equilibrium between
perceived challenge and skill level, has been extensively studied in various domains …

Towards a Physiological Computing Infrastructure for Researching Students' Flow in Remote Learning: Preliminary Results from a Field Study

MX Li, M Nadj, A Maedche, D Ifenthaler… - … , Knowledge and Learning, 2022 - Springer
With the advent of physiological computing systems, new avenues are emerging for the field
of learning analytics related to the potential integration of physiological data. To this end, we …

[PDF][PDF] Using a General Prior Knowledge Graph to Improve Data-Driven Causal Network Learning.

M Sinha, SA Ramsey - AAAI spring symposium: combining machine …, 2021 - ceur-ws.org
We describe a method “Kg2Causal” for using a large-scale, general-purpose biomedical
knowledge graph as a prior for data-driven causal network structure learning. Given a set of …

Assessment of cognitive load from bio-potentials measured using wearable endosomatic device

D Jaiswal, M Moulick, D Chatterjee, R Ranjan… - Proceedings of the 6th …, 2020 - dl.acm.org
Cognitive load is the amount of mental resources required to execute a task.
Psychophysiological researches show variations in the electrodermal activity of the skin with …

Physiological states and body postures can tell your flow experience——application of BP neural networks

J Chen, Z Li, S Ma, Z Yang, H Li - Multimedia Tools and Applications, 2024 - Springer
Accurately evaluating flow level is critical for game designers. In order to identify and
analyze the real-time flow experience without any intrusion, we proposed to use body …

Voting-based integration algorithm improves causal network learning from interventional and observational data: An application to cell signaling network inference

M Sinha, P Tadepalli, SA Ramsey - Plos one, 2021 - journals.plos.org
In order to increase statistical power for learning a causal network, data are often pooled
from multiple observational and interventional experiments. However, if the direct effects of …

Detecting Flow Experiences in Cognitive Tasks-A Neurophysiological Approach

MT Knierim - 2020 - publikationen.bibliothek.kit.edu
Das Flow-Erlebnis beschreibt einen Zustand vollständiger Aufgabenvertiefung und
mühelosen Handelns, der mit Höchstleistungen, persönlichem Wachstum, sowie …

[BUKU][B] Classification of EEG signals of user states in gaming using machine learning

C Mallapragada - 2018 - search.proquest.com
In this research, brain activity of user states was analyzed using machine learning
algorithms. When a user interacts with a computer-based system including playing computer …