MUMBAI, India, July 13 -- Intellectual Property India has published a patent application (202641074924 A) filed by The Principal,mepco Schlenk Engineering College on June 17, 2026, for An Intelligent Voice-Assisted Non-Invasive Intracranial Pressure Monitoring Device For Real-Time Neurophysiological Assessment And Adaptive Clinical Monitoring.
Inventors include Dr. D. Selvathi; K. Ragul; Dr. A. Meenakumari; Dr. N. Thanappan; and Dr. B. Karthick Kumar.
The application for the patent was published on July 10, 2026, under issue no. 28/2026.
Abstract: Intracranial Pressure (ICP) is a critical physiological parameter associated with neurological conditions such as traumatic brain injury, stroke, and intracranial haemorrhage, add its continuous monitoring is essential for timely clinical intervention. According to global neurological health studies, millions of patients worldwide are affected by conditions involving abnormal ICP, particularly in emergency and critical care settings. Th;: conventional clinical measurement of ICP is performed using invasive catheter-based techniques, which involve surgical insertion into the cranial cavity and may le~d t•) complications such as infection, haemorrhage, and high procedural cost. To overcome thes;: limitations, a non-invasive system named Neuro Voice is developed, which integrates multi- parameter physiological sensing and intelligent processing for real-time ICP estimatiod. Th;: system utilizes inputs such as blood pressure, body mass index (BMI), age, and body temperature, along with derived parameters including Mean Arterial Pressure (MAP), I i Cerebral Perfusion Pressure (CPP), and temperature variability, which are closely related to intracranial dynamics. A microcontroller-based embedded system is used for real:·tim;: acquisition and processing of sensor data, while an ESP-based wireless communi1ation module transmits the data to a mobile application. In the core processing stage, a multiparameter estimation model combines physiological inputs to compute ICP values, Jhich are further classified into Normal, Mild, Moderate, and Severe categories. The Jobile application displays real-time ICP values, classification results, and maintains historical patient data for continuous monitoring and analysis. The dataset used for validation' wa: collected from normal individuals in academic environments and from patients with traumatic brain injury in hospital settings under clinical supervision. The system achieved an accuracy improvement from approximately 75% to 94.70% after error correction, with strong statistical performance indicated by reduced error metrics and high correlation (r 0.9), coefficient of determination (R2 close to 1), and intraclass correlation coefficient riCC 0.9). The developed device is portable, non-invasive, and user-friendly, with an integrated voice-assisted interface enabling operation by lay and unskilled users. The system sup~om real-time monitoring, remote healthcare applications, and provides a cost-effective solution for improving early diagnosis and patient outcomes in diverse clinical and non-clinical environments.
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