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From learning environments to battlefields to marketing teams, the desire to measure cognition and cognitive fatigue in real time has been a grand challenge in optimizing human performance. Near-infrared spectroscopy (NIRS) is an effective optical technique for measuring changes in subdermal hemodynamics, and it has been championed as a more practical method for monitoring brain function compared to MRI. This study reports on an innovative functional NIRS (fNIRS) sensor that integrates the entire system into a compact and wearable device, enabling long-term monitoring of patients. The device provides unrestricted mobility to the user with a Bluetooth connection for settings configuration and data transmission. A connected device, such as a smartphone or laptop equipped with the appropriate interface software, collects raw data, then stores and generates real-time analyses. Tests confirm the sensor is sensitive to oxy- and deoxy-hemoglobin changes on the forehead region, which indicate neuronal activity and provide information for brain activity monitoring studies. 

Networked control systems (NCSs) are designed to control and monitor large-scale and complex systems remotely. The communication connectivity in an NCS allows agents to quickly communicate with each other to respond to abrupt changes in the system quickly, thus reducing complexity and increasing efficiency. Despite all these advantages, NCSs are vulnerable to cyberattacks. Injecting cyberattacks, such as a time-delay switch (TDS) attack, into communication channels has the potential to make NCSs inefficient or even unstable. This paper presents a Lyapunov-based approach to detecting and estimating TDS attacks in real time. A secure control strategy is designed to mitigate the effects of TDS attacks in real time. The stability of the secure control system is investigated using the Lyapunov theory. The proposed TDS attack estimator’s performance and secure control strategy are evaluated in simulations and a hardware-in-the-loop environment.