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Technological advancements have played a significant role in improving pupillometers, enhancing their accuracy, functionality, and usability. Traditional pupillometers used visible light to measure pupillary responses. However, infrared pupillometry has become the standard in modern devices. Infrared light is utilized to capture pupillary data, which offers improved accuracy and reliability, particularly in various lighting conditions. Pupillometers now incorporate high-resolution cameras with advanced imaging capabilities to capture precise and detailed images of the pupil.
Further, integration with digital health systems, wireless connectivity, portable and handheld devices, automated measurements and algorithms, real-time monitoring and analysis and user-friendly interfaces are among the key pointers driving the product demand. Furthermore, AI algorithms are being developed and integrated into pupillometers to enhance their diagnostic capabilities. AI can assist in automated analysis, pattern recognition, and prediction of neurological conditions based on pupillary responses, providing valuable insights to healthcare providers.