ArticleSensors (Basel, Switzerland)2021
Can EEG Be Adopted as a Neuroscience Reference for Assessing Software Programmers' Cognitive Load?
Article in Sensors (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- Optimal frequency bands for pupillography for maximal correlation with HRV.Scientific reports · 2025Article
- From neurotechnology to the classroom: the promise of brain-computer interfaces for training systems engineers.Frontiers in human neuroscience · 2025Article
- EEG as a potential ground truth for the assessment of cognitive state in software development activities: A multimodal imaging study.PloS one · 2024Article
- A High-Density EEG Study Investigating the Neural Correlates of Continuity Editing Theory in VR Films.Sensors (Basel, Switzerland) · 2023Article
- Remote collection of electrophysiological data with brain wearables: opportunities and challenges.Bioelectronic medicine · 2023Review
- A scoping review of eye-tracking metrics as an indicator of negative mental health-related outcomes and its possible applicability in remote work situations.Environmental and occupational health practice · 2023Review
- On the accuracy of code complexity metrics: A neuroscience-based guideline for improvement.Frontiers in neuroscience · 2022Article
- Software Bug Detection Causes a Shift From Bottom-Up to Top-Down Effective Connectivity Involving the Insula Within the Error-Monitoring Network.Frontiers in human neuroscience · 2022Article
- A High-Density EEG Study Investigating VR Film Editing and Cognitive Event Segmentation Theory.Sensors (Basel, Switzerland) · 2021Article
Corrections and comments
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Authors and funding
10 authors.
Funding
Abstract
An emergent research area in software engineering and software reliability is the use of wearable biosensors to monitor the cognitive state of software developers during software development tasks. The goal is to gather physiologic manifestations that can be linked to error-prone scenarios related to programmers' cognitive states. In this paper we investigate whether electroencephalography (EEG) can be applied to accurately identify programmers' cognitive load associated with the comprehension of code with different complexity levels. Therefore, a controlled experiment involving 26 programmers was carried. We found that features related to Theta, Alpha, and Beta brain waves have the highest discriminative power, allowing the identification of code lines and demanding higher mental effort. The EEG results reveal evidence of mental effort saturation as code complexity increases. Conversely, the classic software complexity metrics do not accurately represent the mental effort involved in code comprehension. Finally, EEG is proposed as a reference, in particular, the combination of EEG with eye tracking information allows for an accurate identification of code lines that correspond to peaks of cognitive load, providing a reference to help in the future evaluation of the space and time accuracy of programmers' cognitive state monitored using wearable devices compatible with software development activities.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.