Using fNIRS and ECG to Measure Cognitive Workload and Emotion as Passive Input.
Jenkins, Andrew M.
2014
- Abstract: This study examines the potential use of functional nearinfrared spectroscopy (fNIRS), a measure of brain activity, and electrocardiogram (ECG), a measure of heart rate, as physiological sensors that can determine a user’s cognitive workload and emotional valence. Eight participants wore both sensors simultaneously, and completed two tasks. In one task, they performed a working memory ... read moretask known as nback, which can be used to manipulate cognitive workload. In the other task, they viewed a series of images from the International Affective Picture System (IAPS), which are documented as evoking known emotional responses. Using the support vector machine (SVM) machine learning algorithm, a classifier was generated for each subject for each condition and was evaluated using 10fold cross validation. Results show that the fNIRS classifiers performed significantly better on the workload data than the ECG classifiers. For the emotion data, one of the ECG classifiers performed slightly better than the fNIRS classifiers. Both devices could be used as passive input sources for creating adaptive computer interfaces. Although each device was evaluated separately, the two could be used in conjunction to better classify a user’s state.read less
- ID:
- rn301c170
- Component ID:
- tufts:sd.0000134
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