A Multimodal Data-driven Framework for Anxiety Screening

Abstract--Early screening for anxiety and appropriate interventions are essential to reduce the incidence of self-harm and suicide in patients. Due to limited medical resources, traditional methods that overly rely on physician expertise and specialized equipment cannot simultaneously meet the needs for high accuracy and model interpretability . Multimodal data can provide more objective evidence for anxiety screening to improve the accuracy of models. The large amount of noise in multimodal data and the unbalanced nature of the data make the model prone to overfitting. However, it is a non-differentiable problem when high-dimensional and multimodal feature combinations are used as model inputs and incorporated into model training. This causes existing anxiety screening methods based on machine learning and deep learning to be inapplicable. Therefore, we propose a multimodal data-driven anxiety screening framework, namely MMD-AS, and conduct experiments on the collected health data of over 200 seafarers by smartphones. The proposed framework's feature extraction, dimension reduction, feature selection, and anxiety inference are jointly trained to improve the model's performance. In the feature selection step, a feature selection method based on the Improved Fireworks Algorithm is used to solve the non-differentiable problem of feature combination to remove redundant features and search for the ideal feature subset. The experimental results show that our framework outperforms the comparison methods. Furthermore, anxiety disorders are accompanied by immune disorders [2], and interfere with cognitive functions through memory and attention [3], thereby affecting normal life and work. Early anxiety assessment and appropriate interventions can greatly reduce the rate of self-harm and suicide in patients [4]. Psychological scales and routine health checks with professional medical equipment are traditional anxiety screening methods. The Self-rating Anxiety Scale (SAS) [5] and the Generalized Anxiety Disorder-7 (GAD-7) [6] are two psychological scales that are currently used for anxiety screening. Anxiety frequently results in a variety of symptoms or behavioral modifications, such as breathlessness [7], variations in blood pressure [8] and heart rate [9], perspiration, tense muscles, and dizziness [10]. These objective signs can also be used as an important basis for anxiety screening. However, due to the limitation of lacking of medical resources in remote areas and high cost, routine health examinations such as Magnetic Resonance Imaging (MRI) [11], Computed T omography (CT), electrocardiogram (ECG) [12], [13] and electroencephalogram (EEG) [9], [14], may not be available. Haimiao Mo and Shuai Ding are with the School of Management, Hefei University of T echnology, Anhui Hefei 23009, China, also with the Key Laboratory of Process Optimization and Intelligent Decision-Making, Ministry of Education, China.