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Researchers at the Indian Institute of Technology (IIT) in Madras have found a way to determine whether a worker has the mental ability to cope with a crisis in a factory or other high-stress jobs by using an electroencephalogram (EEG ) measures.

According to a study published in the Journal of Computers and Computer Engineering, researchers found that the EEG, a technique used to measure brain activity, can measure the cognitive workload of human operators in a chemical plant control room.

With the EEG, sensors are placed on the subject’s scalp and brainwave activity is measured. IIT research found that measuring brain waves can help gauge a person’s ability to respond to an emergency in real time, which in turn could prevent accidents and breakdowns.

According to the team, research has shown the EEG’s potential to assess the cognitive workload of human operators in a chemical plant control room. Cognitive workload is the amount of measurable mental effort a person expends to complete a task. Because of the high cognitive workload on workers, they are prone to errors that can lead to accidents.

“Human errors are the cause of almost 70 percent of work accidents worldwide. Human errors, whether in the planning or execution phase, depend not only on the skills of the worker, but also on his mental state and sharpness at the time. Everyone’s performance becomes prone to error when the requirements of the task they are responsible for and their ability to complete it mismatch, ”said Rajagopalan Srinivasan, professor in the Department of Chemical Engineering at IIT Madras.

“Such a mismatch creates a high cognitive workload on human operators, which is often a precursor to poor performance. All of our thoughts and activities are powered by electrical signals between the cells in our brain called brain waves, which occur at different frequencies and are known as alpha, beta, gamma, theta, and delta. The relative sizes of these waves along with their variation are a signature of our thinking process and our current mental state, ”he added.

The research team attached sensors to the heads of six participants and had them each perform eight tasks.

“The task was to monitor a typical industrial sector for faults which, if not controlled by the participant within a certain period of time, can lead to accidents. Due to the nature of the job, they therefore had to understand the behavior of the plant (industrial department) and take appropriate decisions and actions if a malfunction occurred. The disorder increased their cognitive workload, and only when the right decision was made did their cognitive workload decrease.

“Their results showed that the amount of theta waves can detect a mismatch between the mental model of the worker of the process and the actual plant behavior in abnormal situations. This makes sense because it was believed that the “theta band” of brain waves is responsible for the control process of working memory functions, ”he said.

The institute plans to investigate the potential of these EEG methods to improve human performance in various high-risk industries, thereby opening up a new paradigm for occupational safety and its relationship to the real-time mental state of the worker.

“The EEG-based approach can provide information about the cognitive workload of operators during training, which in turn can be used to fine-tune the training process itself. There can also be targeted cues as you study to improve the overall effectiveness of the training, ”said Srinivasan.

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JEE Main 2020 Paper 2 (B.Arch) Exam Analysis: Shift 1, September 1st

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