How can a CEO ascertain that all of his or her members are working with their full capacity?
Are you sure that your brain is not too overloaded with the everyday working condition?
Now with the help of the combined use of electroencephalogram (EEG) and Virtual Reality (VR), you can find out the mental workload and stress level of you and other co-workers. Adopting this combined tool will lead to much more efficient operational decisions that achieve a fair distribution of workload and responsibility among various workers.
What affects job performance?
In fact, a multiple of variables, from workplace culture to the size of work equipment, hinder our ability from thoroughly assessing any situation, which ultimately affects job performance. Mainly, fatigue and stress are critical human factors that should not be taken lightly. EHS Today reported that about a half of US workers suffer from fatigue; this is not only the story of them, but the world workforce population complains of tiredness. The most critical problem in stress at work is that excessive workload and corresponding stress would directly lead to safety issues or sometimes severe injuries. In other words, tiredness affects our judgment and might put our health at risk, and thus, the perceived level of mental stress and workload for workers should be continuously monitored and evaluated so as to secure them from various industrial accidents. Though it sounds like something costly for managers to keep their eyes on, the action is imperative in a sense that managing workers’ stress level would contribute to their overall enhanced work effectiveness.
Bio-signals would help you check your mental workload
Yet, how can we assess one’s workload? There are mainly three types of workload assessment methodologies: subjective measures, performance measures, and physiological measures. Conventionally, people had to rely on the worker’s subjective assessment where the user determines and assesses how much he or she is mentally overloaded by themselves. As a matter of fact, a few versions of Subjective Workload Assessment Techniques (SWAT) have been developed. Nonetheless, such method cannot escape from its fundamental fail point that is it not sensitive enough to catch subtle mental workloads, which if accumulated, can, in turn, lead to chronic fatigue. The performance measures, which record performance scores and use these as an indicator of task demand, or difficulty, is way more objective but they are hard to be widely used due to their intrusiveness to various work settings.
The best and the most straightforward way to make a diagnosis of our physical state is to look at bio-signals. Apart from the conventional methods such as statistical analysis of special events or keeping track of the worker’s complaints, physiological information can be considered to evaluate human factors. In addition, among many other bio-signals, electroencephalogram (EEG) is well-known for high time-resolution, possibility to continuously monitor brain stress with the adequate accuracy, and most importantly, the recognition of human emotion, stress, vigilance, etc. That is, EEG can be utilized to monitor mental workload, emotion, and stress of the workers when they perform any task. Still, some of you might worry about the way to collect EEG signals from the real working environment, as it is hard to be simulated physically. However, now that the virtual reality (VR) technology has been fairly well advanced, simulating your working condition in a virtual environment is not a matter.
Measurement of stress recognition of crew members by EEG in a Virtual Environment
This week’s research review illustrates the measurement of mental workload through EEG in a virtually simulated environment — EEG-based Mental Workload and Stress Recognition of Crew Members in Maritime Virtual Simulator: A case study. The research team has focused their study on the maritime industry where human factors are considered to be one of the leading causes of accidents, attributing to nearly 96% of the entire maritime accidents. Even though the industry has achieved a notable improvement of ship equipment and the overall system, human factors have not been considered enough to enhance the whole safety level. Therefore, the research aimed to study cause and effect of human errors of crew members by monitoring mental workload, emotion and stress level of the maritime trainees.
To be more specific, in order to study the relationship between maritime trainees’ mental workload, stress levels, and task performance, the research team conducted the experiment with four maritime trainees forming the crew. Consisted of an officer on watch (OOW), a steersman, a captain, and a pilot with each assigned with duty corresponding to that of the real crew member, the crew had to navigate the vessel to the destination within SMA’s Integrated Simulation Centre (ISC) where a highly realistic environment was simulated. During their voyage, each of the subject’s emotion level (positive, neutral, negative), workload (no, minimal, moderate, high), and stress (low, medium low, moderate low, medium, medium high, moderate high, high, very high) had been observed and were further analyzed after the experiment.
The following describes the result of the analysis. The OOW, who always had to maintain watch-keeping was in the most negative emotional state; the captain, who was required to give our orders to the crew and assigned with the most significant responsibility showed the highest workload; the captain and the pilot, who had relatively higher responsibility than OOW and steersman were recorded with higher stress level as well.
Though the experiment is still in a preliminary stage of studying human factors, the success in monitoring emotion, mental workload, and stress implies that the proposed approach can be applied far beyond the maritime domain. The EEG-based human factors evaluation tools can be used for any industry that involves a multiple of people working together. In addition, it is anticipated that such mechanism can broaden the research that studies the human-machine interaction.
LooxidVR: The All-in-one device with VR compatible EEG sensor and eye tracking camera
Then what should be the next step? In order to achieve a more accurate measurement of human factors in a far more immersing environment, the data-collecting sensor and the environment which is being simulated should be correlated as closely as possible. LooxidVR, the winning product of CES 2018 Best of Innovation Award, is now here for you to provide a robust data acquisition of the user’s brain activity and even eye movement in VR environment. Made by Looxid Labs, Looxid VR is the world first mobile VR headset to provide an interface for both the eyes and the brain. Looxid Labs is ready to provide the integrated solution to many of those who are interested in exploring user’s mind. It will be especially helpful for researchers who are interested in recognizing diverse emotion state of the user such as stress, mental workload, and preference.
LooxidVR has begun pre-order from 1st, Feb. For more information, visit our website www.looxidlabs.com and do not miss the pre-order opportunity to enrich your current research and study.
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- EEG-based Mental Workload and Stress Recognition of Crew Members in Maritime Virtual Simulator: A Case Study | http://ieeexplore.ieee.org/document/8120300/
- Human Factors In Safety: How do stress and fatigue affect work? | https://www.pro-sapien.com/blog/2017/10/human-factors-safety-how-stress-fatigue-affect-work/
- Workload Assessment | https://www.ergonomicsblog.uk/workload-assessment/