New technologies being developed to detect and predict cognitive stress that can result in failure of military Missions

Rajesh Uppal October 27, 2017 BioScience, Soldier Comments Off on New technologies being developed to detect and predict cognitive stress that can result in failure of military Missions 803 Views

Soldiers often have to perform complex tasks in extreme conditions, sometimes approaching or exceeding the limits of their capabilities. Some of the missions the soldiers perform can take weeks, away from in difficult terrain like deserts and mountains which requires maintaining an incredibly high level of physical fitness. Around the world, armies are recognizing the importance of maximizing the effectiveness of Soldiers physically, perceptually, and cognitively.

A decrease in cognitive performance can have great impact and it is therefore important to gain more insight into influencing factors of cognitive performance. Preventive action and early recognizing of decrements in cognitive performance are important to optimize the employment of Defence staff.

Natick Soldier Research, Development and Engineering Center (NSRDEC) in Massachusetts is focused on developing capabilities that increase warfighter capacity to fight and win on the future battlefield. Some of the areas it is researching are effects of frustration, mental workload, stress, fear and fatigue on both cognitive and physical performance.

In 2017, the United States Department of Defense will launch the Tactical Assault Light Operator Suit (Talos), a futuristic piece of military hardware that encloses soldiers within a bullet-bouncing, internally cooled, computerised exoskeleton. Wearable Biosensors are being developed that measure EEG, ECG, and EMG (electroencephalograms, electrocardiograms, and electromyography, tests which monitor brain, heart, and muscle activity).

The Office of Naval Research awarded a $150,000 grant to Titus and the tech firm Sentience Science to develop tools that could monitor an individual’s stress levels in combat and automatically generate alerts when they reach dangerous levels.

Cognitive Overload

Cognitive load is commonly used to refer to the load that performing a particular task imposes on the person’s cognitive system. Cognitive workload is determined by the ratio between the required and the available processing capacity of the task executor (Gaillard, 1996, as cited in Veltman & Neerincx, 2003). Influential aspects of cognitive workload are the task demands and the momentary processing capacity. High cognitive workload appears when task demands are approaching the limits of the processing capacity, which is called overload (Veltman & Neerincx, 2003). Mental effort is required to fulfill the task demands. Physiological reactions to this process are an increase in heart rate frequency, an increase in respiratory rate and a reduction in eye blinking.

Several physiological signals have been used for cognitive load measurement: signals from heart, eye, brain and skin. Galvanic skin response (GSR), which is electrical conductance of skin, is a low-cost, easily-captured, robust physiological signal. In contrast with some eye based features (such as pupil dilation) which can only be gathered through an expensive eye tracker, eye blink can be obtained with an acceptable accuracy through a conventional camera.

Galvanic skin response (GSR) and eye blinks are cognitive load measures which can be captured conveniently and at low cost. The study done by Nargess Nourbakhsh, Yang Wang, Fang Chen has assessed multiple features of these two signals in classification of cognitive workload level. The experiment included arithmetic tasks with four difficulty levels and two types of machine learning algorithms have been applied for classification. Obtained results show that the studied features of blink and GSR can reasonably discriminate workload levels and combining features of the two modalities improves the accuracy of cognitive load classification. They have achieved around 75% for binary classification and more than 50% for four-class classification.

DARPA awards contract for detection of Acute Cognitive Strain (ACS)

Quantum Applied Science & Research (QUASAR), Inc., a San Diego-based high-tech company, has just been awarded a research contract from the Defense Advanced Research Projects Agency (DARPA) to develop a wearable detector of extreme mental stress, referred to as acute cognitive strain (ACS).

Under this funding, QUASAR will collaborate with the Florida Institute for Human and Machine Cognition (IHMC) to develop and test a wearable and comfortable Nonintrusive Detector of Acute Cognitive Strain (DACS) for U.S. warfighters. The $150K award is the first of two planned phases of a Small Business Technology Transfer (STTR) research effort whose total funding could exceed $1M. In October 2016, QUASAR and IHMC also received a $2M award from the U.S. Air Force to monitor cognitive effort, stress, and fatigue.

ACS is the psychological state that results from excessively high mental demands. It can cause loss of productivity, situational awareness, and self-control, in addition to breakdowns in team cooperation. This can worsen job performance and satisfaction, and in certain environments lead to team failure and catastrophic consequences.

“In today’s world, almost everyone is stressed out. ACS is the extreme end of the stress spectrum, when tempers are lost and grown-ups melt down into tantrums,” explained Dr. Walid Soussou, CEO of QUASAR, who is leading this project along with Dr. Anil Raj from IHMC.

The detection of ACS is important for many stressful professional environments, including high-stakes trading in the financial sector, emergency medical staff, or even competitive sports. For both military and non-military environments, the detection of ACS is important to rapidly mitigate stressful situations, especially in mission- or safety-critical environments such as command center operation, emergency response teams, air traffic control, and plant management.

Many consumer-grade wearable stress monitors have recently started appearing on the market, like Thync, Wellbe, or Spire, and there are even apps for the Apple Watch. QUASAR and IHMC aim to develop a military-grade wearable DACS sensor suite to measure ACS-related physiological changes, including increased blood pressure, heart rate, sweatiness, muscle and voice tension, and shortness of breath. These measurements would be used to detect ACS and alert management that the operator needs assistance, or fed back into the system itself so it could take appropriate action to address the situation.

Therefore, wearable DACS technology could be extended to a range of non-military applications, including anger management and specialized peak-performance training methods for maintaining athletic performance under high-stress situations.

Predicting Performance under Stressful Conditions Using Galvanic Skin Response

One proposed way to measure stress involves using what is known as galvanic skin response (GSR), which is the electrical conductance of the skin and depends on presecretory activity in the sweat glands. GSR was first shown to be correlated with stress in (Jung 1908) and many studies since have supported this relationship (Boucsein 2012, Picard 1997).

The recent ubiquity of wearable biosensors such as smart watches and wristbands has made GSR data much easier to collect and has facilitated a new body of experimental research which uses GSR for stress detection. It has been shown to be effective for distinguishing varying degrees of stress in both lab studies (Zhai 2005) and real-life settings, such as highway and city driving (Healey 2005) and financial trading (Lo and Repin 2002). Experiments have also shown that GSR can be used to infer the difficulty or cognitive load associated with a task.

A soldier can only experience the reality of combat on the battlefield. However, it is difficult to test a soldier’s performance under real-life conditions therefore airline pilots and soldiers are often tested in computer-generated simulations which is a low stress environment. “The performance of a worker in a simulator or in another low stress environment may not be a good predictor of his performance in a high stress situation because it is not obvious how he will respond to the additional stress,” write the authors. “Some workers may thrive in high stress environments, while others may suffer a large degradation in their performance. In this paper, we show that biological data, in particular galvanic skin response (GSR), can be used to predict performance under stress and potentially enhance conventional testing methods.”

Carter Mundell, Juan Pablo Vielma, and Tauhid Zaman in their paper, show that biological data, in particular galvanic skin response (GSR), can be used to predict performance under stress and potentially enhance conventional testing methods. They were able to accurately predict the good and bad performers using GSR. This suggests that by using wearable biosensors, one can evaluate the performance of workers under dangerous, high risk, high stress conditions using data from safer, low risk, low stress conditions.