An emotionally intelligent haptic system - An efficient solution for anxiety detection and mitigation.

BACKGROUND

Anxiety is a psycho-physiological condition associated with an individual's mental state. Long-term anxiety persistence can lead to anxiety disorder, which is the underlying cause of many mental health problems. As such, it is critical to precisely identify anxiety by automated, effective, and user-bias-free ways.

OBJECTIVE

The objective of this study is to develop an innovative emotionally intelligent Haptic system for anxiety detection, which can be used to track and manage people's anxiety.

METHOD

The suggested approach incorporates a haptic feedback mechanism that is based on EEG data and is analysed by machine learning algorithms. This allows users to effectively control their emotional well-being by receiving timely feedback and assessments of their anxiety levels. First, the authors use publicly accessible data to present an experimental study for the categorization of human anxiety.

RESULTS

The ensemble model used for the classification produces results with a 97 % accuracy rate, 0.98 recall, 0.99 precision, and a 0.99 F1 score. Furthermore, self-curated data is subjected to an advanced spike analysis algorithm that identifies signal spikes and then quantifies the level of anxiety.

CONCLUSION

The results obtained demonstrate that haptic stimuli are produced smoothly, offering a comprehensive and innovative method of managing anxiety.