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@article{184114,
        author = {P.S Anu Rakhi and Shree mugi M G and Rathi R and Shaniya Falist E},
        title = {Silent care AI: A 24*7 intelligent facial expression based assistant non-verbal for ICU patients},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {12},
        number = {4},
        pages = {246-249},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=184114},
        abstract = {Communication is a vital component of healthcare delivery, particularly in the Intensive Care Unit (ICU) where patients are critically ill and require constant observation. Unfortunately, many ICU patients lose their ability to speak due to intubation, sedation, neurological injury, or overall weakness. This communication barrier often results in delayed care, unaddressed discomfort, and increased psychological stress. SilentCare AI has been conceptualized as a round-the-clock intelligent system that utilizes artificial intelligence (AI) and facial expression recognition to interpret patient emotions and needs without verbal interaction. The system employs computer vision techniques, deep learning algorithms, and continuous monitoring to identify micro-expressions such as pain, fear, or distress, and subsequently deliver real-time alerts to healthcare providers. This paper presents the background, system design, methodology, clinical implications, and potential future applications of SilentCare AI, highlighting its role as a bridge between patient emotions and caregiver response in critical care settings.},
        keywords = {CU patients, non-verbal communication, facial expression recognition, deep learning, intelligent healthcare assistant, patient monitoring},
        month = {September},
        }