Figure - available from: Computational and Mathematical Methods in Medicine
This content is subject to copyright. Terms and conditions apply.
Source publication
In today’s society, people with poor mental ability are prone to neuropsychiatric diseases such as anxiety, ADHD, and depression due to long-term negative emotions. Although conventional Western medicine has certain curative effect, these drugs have significant anticholinergic side effects central toxicity as well as cardiovascular and gastrointest...
Similar publications
Background : There is a significant gender difference in the prevalence of depression. Recent studies have shown that estrogen plays a crucial role in depression. Therefore, studying the specific mechanism of estrogen’s role in depression can provide new ideas to address the treatment of depression. Chaigui granule has been shown to have exact anti...
Citations
... Music affects functional brain connectivity and is effective in the treatment of neurological disorders. Mengru Sun proposed that music with different emotions can treat depression patients [5]. MER is not only applicable to music track navigation, search, and recommendation but is also widely used in the field of music therapy [6]. ...
As a key field in music information retrieval, music emotion recognition is indeed a challenging task. To enhance the accuracy of music emotion classification and recognition, this paper uses the idea of inception structure to use different receptive fields to extract features of different dimensions and perform compression, expansion, and recompression operations to mine more effective features and connect the timing signals in the residual network to the GRU module to extract timing features. A one-dimensional (1D) residual Convolutional Neural Network (CNN) with an improved Inception module and Gate Recurrent Unit (GRU) was presented and tested on the Soundtrack dataset. Fast Fourier Transform (FFT) was used to process the samples experimentally and determine their spectral characteristics. Compared with the shallow learning methods such as support vector machine and random forest and the deep learning method based on Visual Geometry Group (VGG) CNN proposed by Sarkar et al., the proposed deep learning method of the 1D CNN with the Inception-GRU residual structure demonstrated better performance in music emotion recognition and classification tasks, achieving an accuracy of 84%.
