Detection of emotional and behavioural changes after traumatic brain injury: A comprehensive survey

IF 1.2 Q4 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Neha Vutakuri
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Abstract

Traumatic brain injury (TBI) can affect normal brain function and may be caused by a vehicle accident, falling, and so on. The purpose of this survey is to provide clear knowledge of TBI, the causes of TBI, the impacts of TBI, and the role of family members and friends in recovery. TBI affects the daily life of the patients, both physically and mentally. After TBI, the patients may experience many emotional and behavioural changes because of a lack of certain brain functions. These changes affect their personal and social relationships. On the other hand, these changes depend on the severity of the TBI (i.e. mild, moderate, or severe), which is measured using the Glasgow coma score. Generally, three processes are used for emotion recognition: preprocessing, feature extraction, and emotion recognition. Preprocessing is performed for landmark detection and pose normalisation, which improves the performance of emotion detection. Feature extraction and emotion recognition are performed by various deep learning techniques, such as convolution neural networks and long short-term memory. These techniques recognise the behavioural and emotional changes (depression, anxiety, anger, personality changes etc.) of TBI patients using facial expressions. Family members and friends play an important role in TBI patients' recovery, the extent of which is based on the severity of the TBI. The care of family members and friends leads to quick recovery and rehabilitation of patients from TBI. Finally, testing is performed using Computed Tomography images, Magnetic Resonance Imaging images, Electroencephalography signals, and patient demographics, which together show that the deep learning methods achieve better performance in terms of accuracy, precision, recall, and F-measure in recognising emotional and behavioural changes after TBI. The authors conclude with a summary of the future of emotional and behavioural change prediction methods for TBI patients.

Abstract Image

创伤性脑损伤后情绪和行为变化的检测:一项综合调查
创伤性脑损伤(TBI)会影响正常的大脑功能,可能是由车祸、跌倒等引起的。本调查的目的是提供有关TBI、TBI的原因、TBI影响以及家人和朋友在康复中的作用的明确知识。TBI影响患者的日常生活,包括身体和精神。TBI后,由于缺乏某些大脑功能,患者可能会经历许多情绪和行为变化。这些变化会影响他们的个人和社会关系。另一方面,这些变化取决于TBI的严重程度(即轻度、中度或重度),这是使用格拉斯哥昏迷评分来测量的。情绪识别通常采用三个过程:预处理、特征提取和情绪识别。对地标检测和姿态归一化进行预处理,提高了情绪检测的性能。特征提取和情绪识别是通过各种深度学习技术进行的,如卷积神经网络和长短期记忆。这些技术通过面部表情识别TBI患者的行为和情绪变化(抑郁、焦虑、愤怒、性格变化等)。家人和朋友在TBI患者的康复中起着重要作用,康复程度取决于TBI的严重程度。家人和朋友的照顾使TBI患者快速康复。最后,使用计算机断层扫描图像、磁共振成像图像、脑电图信号和患者人口统计数据进行测试,这些数据共同表明,深度学习方法在识别TBI后的情绪和行为变化方面,在准确性、准确性、回忆力和F测量方面取得了更好的性能。作者总结了TBI患者情绪和行为变化预测方法的未来。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Cognitive Computation and Systems
Cognitive Computation and Systems Computer Science-Computer Science Applications
CiteScore
2.50
自引率
0.00%
发文量
39
审稿时长
10 weeks
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