This research project delves into the exploration of the sound environment within Intensive Care Units (ICUs), particularly focusing on Neonatal Intensive Care Unit (NICU) and Pediatric Intensive Care Unit (PICU). It aims to enhance the understanding of sound events and their impact on both nurses' decision-making and patients' sleep behaviors. By recognizing the unique challenges of the sound environment in these specialized units, the project focuses on creating a soundscape evaluation metric, incorporating sound event detection algorithms, and simulating real ICU scenarios through synthesized audio. This approach seeks to facilitate better decision-making, foster communication among nurses, improve behavior, and enhance awareness of events within the patient's room.
Utilizing an iterative process that involved technological exploration, algorithmic integration, and UI design, the project offers a novel perspective on sound quality within NICU and PICU settings. The main objective is to transform raw sound data into visually accessible formats for the nursing staff, while also addressing complexities like sound collection, data processing, information storage, deployment methods, and interaction design. The project culminates in the development of a functional product prototype that not only meets the initial goals but also reveals new opportunities and challenges for future exploration. The insights gathered contribute to the wider understanding of the sound environment within NICUs and PICUs, shedding light on potential improvements in patient care and nurse interaction within these critical healthcare environments.