• ASIFALI SALAUDDIN JAMADAR
• MANSOOR BASHIR LADKHAN
• VISHWANATH BALAGOUDA PATIL
• APPAJI GOPAL TUKKANATTI
• VIVEKANAND SADASHIV CHOURI

In the contemporary digital era, the information technology (IT) sector has emerged as one of the most dynamic and demanding professional environments. The constant pressure to meet deadlines, handle complex technical challenges, and maintain prolonged focus on computer screens has led to increasing levels of occupational stress among IT professionals. Chronic stress not only impairs cognitive performance and creativity but also contributes to serious psychological and physiological disorders. Consequently, the need for intelligent, non-intrusive stress monitoring systems has become a critical area of research in both computer science and mental health domains. Traditional methods of stress assessment such as psychological questionnaires and physiological measurements are often intrusive, time-consuming, and unsuitable for real-time monitoring. Recent advancements in artificial intelligence (AI) and machine learning have opened new possibilities for emotion and stress detection through the analysis of behavioral and biometric signals. Facial expressions and speech patterns are two highly informative modalities that reflect an individual’s emotional state. Integrating these cues enables the development of robust multimodal systems capable of assessing stress levels with higher precision.

Stress detection, emotion recognition, image processing, speech recognition, multimodal analysis

"STRESS DETECTION IN IT PROFESSIONALS BY IMAGE PROCESSING AND SPEECH ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 11, page no.d148-d153, November-2025, Available :http://www.jetir.org/papers/JETIR2511320.pdf

"STRESS DETECTION IN IT PROFESSIONALS BY IMAGE PROCESSING AND SPEECH ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 11, page no. ppd148-d153, November-2025, Available at : http://www.jetir.org/papers/JETIR2511320.pdf