sAIfer Lab's analyses of human behavior and biomedical signals in the biometric domain.

Behavioral analytics in the domain of biometrics involves the comprehensive study and analysis of human behavior and biomedical signals to identify, authenticate, and monitor individuals, as well as to detect patterns and anomalies. In this context, PraLab's experience is applied in three different application contexts: digital security applications, physical security applications and healthcare domain.

• In digital security applications, behavioral biometrics can provide an additional layer of verification by monitoring how a person types on a keyboard, uses a mouse, or navigates a mobile device. 

• In physical security applications, behavioral analytics is crucial for detecting anomalies in crowded scenes. Anomaly detection in crowded scenes involves identifying events that deviate from normal behavior in public spaces such as airports, train stations, stadiums, and large events. The challenge is distinguishing between benign unusual behavior and potential threats, which is critical for maintaining public safety and security.

• In the healthcare domain, the analysis of biomedical signals such as EEG and ECG (electrocardiogram) can provide insights into a person's mental and physical state. This is particularly useful for detecting conditions such as stress, fatigue, or drowsiness, which are not always apparent through observation alone. Behavioral analytics also extends to the detection of emotional states through both physiological signals and facial expressions.

Any deviation from the established pattern can trigger an alert, enhancing security measures. 

Goals and Target Users: the primary goal of our research is to develop practical solutions to real-world problems by leveraging behavioral analytics.

• For drowsiness detection, our target users include the automotive industry, transport operators, and workplace safety managers.

• For emotion detection, potential users are mental health professionals, customer service managers, and developers of human-computer interaction systems.

• For anomaly detection, the end users are public safety officials, event organizers, and security personnel in various public and private sectors.

Our solutions aim to enhance safety, improve response times, and ultimately save lives by providing reliable and actionable insights derived from biometric data.