Anum Saher¹, Ghulam Gilanie^1,*, Sana Cheema¹, Akkasha Latif¹, Syeda Naila Batool¹, Hafeez Ullah²

Intelligent Automation & Soft Computing, Vol.39, No.6, pp. 1053-1071, 2024, DOI:10.32604/iasc.2024.057047 - 30 December 2024

Abstract Schizophrenia is a severe mental illness responsible for many of the world’s disabilities. It significantly impacts human society; thus, rapid, and efficient identification is required. This research aims to diagnose schizophrenia directly from a high-resolution camera, which can capture the subtle micro facial expressions that are difficult to spot with the help of the naked eye. In a clinical study by a team of experts at Bahawal Victoria Hospital (BVH), Bahawalpur, Pakistan, there were 300 people with schizophrenia and 299 healthy subjects. Videos of these participants have been captured and converted into their frames using… More >

Ghulam Gilanie^1,*, Sana Cheema¹, Akkasha Latif¹, Anum Saher¹, Muhammad Ahsan¹, Hafeez Ullah², Diya Oommen³

Intelligent Automation & Soft Computing, Vol.39, No.1, pp. 57-71, 2024, DOI:10.32604/iasc.2024.041535 - 29 March 2024

Abstract Bipolar disorder is a serious mental condition that may be caused by any kind of stress or emotional upset experienced by the patient. It affects a large percentage of people globally, who fluctuate between depression and mania, or vice versa. A pleasant or unpleasant mood is more than a reflection of a state of mind. Normally, it is a difficult task to analyze through physical examination due to a large patient-psychiatrist ratio, so automated procedures are the best options to diagnose and verify the severity of bipolar. In this research work, facial micro-expressions have been… More >

Ghulam Gilanie¹, Mahmood ul Hassan², Mutyyba Asghar¹, Ali Mustafa Qamar^3,*, Hafeez Ullah⁴, Rehan Ullah Khan⁵, Nida Aslam⁶, Irfan Ullah Khan⁶

CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 2513-2528, 2022, DOI:10.32604/cmc.2022.028229 - 16 June 2022

Abstract Depression is a mental psychological disorder that may cause a physical disorder or lead to death. It is highly impactful on the social-economical life of a person; therefore, its effective and timely detection is needful. Despite speech and gait, facial expressions have valuable clues to depression. This study proposes a depression detection system based on facial expression analysis. Facial features have been used for depression detection using Support Vector Machine (SVM) and Convolutional Neural Network (CNN). We extracted micro-expressions using Facial Action Coding System (FACS) as Action Units (AUs) correlated with the sad, disgust, and More >