Measurement and Monitoring of Cardiorespiratory System Parameters in Operating Room and Postanesthesia Settings

Abstract

This study addresses the pressing issue of cardiovascular diseases (CVDs), the leading global cause of death, by emphasizing the need for continuous monitoring of vital signs, particularly in critical care settings like surgery and ICUs. It aims to develop innovative bio-sensing and noise-reduction technologies to enhance the clarity and reliability of heart and lung sound recordings. The core problem tackled is the interference of excessive ambient noise with auscultation accuracy in noisy clinical environments. By integrating wearable sensors, adaptive noise cancellation, and real-time data processing, the study proposes practical, patient-friendly solutions. Its significance lies in advancing continuous, non-invasive monitoring systems that support early detection, improve clinical decision-making, and ultimately enhance patient safety and outcomes. Chapter 1 of this work introduces cardiovascular diseases (CVDs) as the leading global cause of death, highlighting their historical context, evolving understanding, and classification into various types such as coronary artery disease, stroke, and heart failure. It emphasizes the importance of managing shared risk factors like hypertension and sedentary lifestyles. The chapter also underscores the crucial role of vital sign monitoring—particularly heart rate, respiratory rate, and blood pressure—in detecting early signs of deterioration and guiding interventions. In surgical and ICU settings, continuous monitoring of heart and lung sounds, ECG, and hemodynamic parameters is essential for patient safety. Technological advancements such as AI-driven tools and wearable devices are enhancing early detection, remote monitoring, and proactive clinical decision-making. Chapter 2 explores the evolution of wearable biosensors, highlighting their capacity for continuous, non-invasive monitoring of physiological and biochemical signals. These technologies, integrated into wearables like patches and smartwatches, have transformed cardiovascular care by enabling early detection of conditions such as arrhythmias and myocardial ischemia. Their use extends beyond clinical settings, supporting remote monitoring, post-surgical recovery, and chronic disease management. Integration with AI and cloud platforms enhances predictive analytics and telemedicine capabilities. Despite challenges like accuracy, data privacy, and regulatory compliance, wearable biosensors are poised to play a vital role in personalized and preventive heart healthcare. Chapter 3 of the study discusses the sources and impacts of excessive noise in operating rooms, which can impair communication, raise stress levels, and compromise patient safety. Common noise contributors include surgical tools, alarms, and staff conversations, often exceeding recommended sound levels. The chapter outlines solutions such as sound-absorbing materials, adaptive signal processing, equipment redesign, and behavioral protocols to mitigate noise. These interventions aim to improve surgical performance, reduce fatigue, and enhance both patient outcomes and healthcare provider wellbeing. Chapter 4 presents the design of a digital esophageal stethoscope system for improved auscultation during surgeries under general anesthesia. To address the challenge of excessive background noise in operating rooms, a 3D-printed case filled with Polydimethylsiloxane (PDMS) was developed to house two electret microphones. One microphone captures heart and lung sounds via an esophageal catheter, while the other records ambient OR noise. An adaptive noise canceling algorithm was applied to filter out background noise from the primary biosignal. The processed signal is displayed through a custom software interface. The PDMS-filled case alone reduced some noise, while the adaptive filter significantly enhanced signal clarity. The final system is lightweight, effective, and capable of delivering cleaner heart and lung sound recordings for clinical use. Chapter 5 introduces a wearable bedside monitoring system design for continuous cardiovascular monitoring for postanesthesia and ICU patients. Unlike previous tools that mainly served as screening devices, this system displays real-time cardiopulmonary parameters. It uses a lightweight patch sensor to collect heart and lung sounds via a chest stethoscope and microphones. An adaptive noise cancellation algorithm filters out ambient noise for clearer auscultation. In addition, a short-distance ECG signal is acquired using electrodes and a high-precision analog front end. A high-speed microcontroller enables real-time data processing and waveform display. A custom tablet-based application presents the processed data and vital signals. The system seamlessly integrates heart sounds and ECG monitoring. Rigid–flex PCBs provide both wearability and patient comfort. The solution offers high-quality signal acquisition and holds strong potential as a continuous health monitoring tool. Lastly, Chapter 6 presents a study that explores the acoustic properties of Ecoflex™ 00-35, a soft silicone rubber, for vibration and noise control. Researchers varied curing parameters—like the Part A/B mixing ratio, thinning agent addition, and curing pressure—to examine their effects on sound absorption. SEM was used to analyze microstructure, and impedance tubes measured acoustic performance. Results showed that applying vacuum and using thinning agents increased average cell diameter, enhancing sound absorption (0.35–0.60) in low to mid frequencies. Low-pressure curing further improved low-frequency absorption. Thinning agents also boosted high-frequency performance. The findings demonstrate how curing conditions impact acoustic behavior. This work offers insights into designing soft silicone materials for advanced noise control systems that can be applicable in medical field. In conclusion, this study presents a comprehensive approach to improving cardiovascular monitoring through the integration of wearable biosensors, adaptive noise reduction, and real-time data visualization technologies. By addressing both physiological monitoring needs and environmental challenges such as operating room noise, it advances the field of patient-centered care. The proposed systems demonstrate the potential to enhance diagnostic accuracy, support early intervention, and improve clinical outcomes. This work lays the groundwork for future innovations in continuous, non-invasive health monitoring for critical care and beyond.