Continuous Monitoring Of Vital Signs Research Articles

Wireless Patient Health Monitoring System

Wireless Patient Health Monitoring Systems (WPHMS) have emerged as transformative solutions in modern healthcare, facilitating continuous and remote monitoring of patients' vital signs in real-time. This paper presents a comprehensive exploration of a Wireless Patient Health Monitoring System leveraging the Blynk app, a versatile IoT platform. The system is designed to enable seamless data collection, transmission, and visualization of critical health parameters such as pulse rate, temperature, and blood pressure. By integrating cutting-edge hardware components with intuitive software interfaces, the proposed system offers unprecedented flexibility and accessibility in patient monitoring, transcending the limitations of traditional wired monitoring systems. The research begins with a thorough review of existing literature on wireless healthcare technologies, highlighting the evolution of patient monitoring systems and the role of IoT platforms in revolutionizing healthcare delivery. Building upon this foundation, the paper proceeds to outline the hardware architecture of the WPHMS, detailing the selection and integration of microcontroller boards, sensor modules.

Continuous Vital Sign Monitoring on Hospital Wards and Postoperative Mortality

Continuous Vital Sign Monitoring on Hospital Wards and Postoperative Mortality

Continuous monitoring of vital signs and clinical deterioration in frail elderly cardiac surgery patients: AGE AWARE study: A prospective cohort study.

Continuous monitoring of vital signs and clinical deterioration in frail elderly cardiac surgery patients: AGE AWARE study: A prospective cohort study.

Rational Design of a Surface Acoustic Wave Device for Wearable Body Temperature Monitoring.

Continuous monitoring of vital signs based on advanced sensing technologies has attracted extensive attention due to the ravages of COVID-19. A maintenance-free and low-cost passive wireless sensing system based on surface acoustic wave (SAW) device can be used to continuously monitor temperature. However, the current SAW-based passive sensing system is mostly designed at a low frequency around 433 MHz, which leads to the relatively large size of SAW devices and antenna, hindering their application in wearable devices. In this paper, SAW devices with a resonant frequency distributed in the 870 MHz to 960 MHz range are rationally designed and fabricated. Based on the finite-element method (FEM) and coupling-of-modes (COM) model, the device parameters, including interdigital transducer (IDT) pairs, aperture size, and reflector pairs, are systematically optimized, and the theoretical and experimental results show high consistency. Finally, SAW temperature sensors with a quality factor greater than 2200 are obtained for real-time temperature monitoring ranging from 20 to 50 °C. Benefitting from the higher operating frequency, the size of the sensing system can be reduced for human body temperature monitoring, showing its potential to be used as a wearable monitoring device in the future.

Enhancing discharge decision-making through continuous monitoring in an acute admission ward: a randomized controlled trial.

In Acute Admission Wards, vital signs are commonly measured only intermittently. This may result in failure to detect early signs of patient deterioration and impede timely identification of patient stability, ultimately leading to prolonged stays and avoidable hospital admissions. Therefore, continuous vital sign monitoring may improve hospital efficacy. The objective of this randomized controlled trial was to evaluate the effect of continuous monitoring on the proportion of patients safely discharged home directly from an Acute Admission Ward. Patients were randomized to either the control group, which received usual care, or the sensor group, which additionally received continuous monitoring using a wearable sensor. The continuous measurements could be considered in discharge decision-making by physicians during the daily bedside rounds. Safe discharge was defined as no unplanned readmissions, emergency department revisits or deaths, within 30 days after discharge. Additionally, length of stay, the number of Intensive Care Unit admissions and Rapid Response Team calls were assessed. In total, 400 patients were randomized, of which 394 completed follow-up, with 196 assigned to the sensor group and 198 to the control group. The proportion of patients safely discharged home was 33.2% in the sensor group and 30.8% in the control group (p = 0.62). No significant differences were observed in secondary outcomes. The trial was terminated prematurely due to futility. In conclusion, continuous monitoring did not have an effect on the proportion of patients safely discharged from an Acute Admission Ward. Implementation challenges of continuous monitoring may have contributed to the lack of effect observed. Trial registration: https://clinicaltrials.gov/ct2/show/NCT05181111 . Registered: January 6, 2022.

Wearable wireless continuous vital signs monitoring on the general ward.

Wearable wireless sensors for continuous vital signs monitoring (CVSM) offer the potential for early identification of patient deterioration, especially in low-intensity care settings like general wards. This study aims to review advances in wearable CVSM - with a focus on the general ward - highlighting the technological characteristics of CVSM systems, user perspectives and impact on patient outcomes by exploring recent evidence. The accuracy of wearable sensors measuring vital signs exhibits variability, especially notable in ambulatory patients within hospital settings, and standard validation protocols are lacking. Usability of CMVS systems is critical for nurses and patients, highlighting the need for easy-to-use wearable sensors, and expansion of the number of measured vital signs. Current software systems lack integration with hospital IT infrastructures and workflow automation. Imperative enhancements involve nurse-friendly, less intrusive alarm strategies, and advanced decision support systems. Despite observed reductions in ICU admissions and Rapid Response Team calls, the impact on patient outcomes lacks robust statistical significance. Widespread implementation of CVSM systems on the general ward and potentially outside the hospital seems inevitable. Despite the theoretical benefits of CVSM systems in improving clinical outcomes, and supporting nursing care by optimizing clinical workflow efficiency, the demonstrated effects in clinical practice are mixed. This review highlights the existing challenges related to data quality, usability, implementation, integration, interpretation, and user perspectives, as well as the need for robust evidence to support their impact on patient outcomes, workflow and cost-effectiveness.

Hospital-Level Care at Home for Patients with Cirrhosis.

Patients with cirrhosis have a 30-day readmission rate of over 30%. Novel care delivery models are needed to reduce healthcare costs and utilization associated with cirrhosis care. One such model is Home Hospital (HH), which provides inpatient-level care at home. Limited evidence currently exists supporting HH for cirrhosis patients. The aims of this study were to characterize patients with cirrhosis who received hospital-level care at home in a two-site clinical trial and to describe the care they received. Secondary aims included describing their outcomes, including adverse events, readmissions and mortality. We identified all patients with cirrhosis who enrolled in HH as part of a two-site clinical trial between 2017 and 2022. HH services include daily clinician visits, intravenous and oral medications, continuous vital sign monitoring, and telehealth specialist consultation. We collected sociodemographic data and analyzed HH stays, including interventions, outcomes, adverse events, and follow-up. 22 patients with cirrhosis (45% Hispanic; 50% limited English proficiency, median MELD-Na 12) enrolled in HH during the study period. Interventions included lab chemistries (82%), intravenous medications (77%), specialist consultation (23%), and advanced diagnostics/procedures (23%). The median length of stay was 7days (IQR 4-12); 186 bed-days were saved. Two patients (9%) experienced adverse events (AKI). No patients required escalation of care; 9% were readmitted within 30days. In this two-site study, HH was feasible for patients with cirrhosis, holding promise as a hepatology delivery model. Future randomized trials are needed to further evaluate the efficacy of HH for patients with cirrhosis.

A Comparative Study of Narrow/Ultra-Wideband Microwave Sensors for the Continuous Monitoring of Vital Signs and Lung Water Level.

This article presents an in-depth investigation of wearable microwave antenna sensors (MASs) used for vital sign detection (VSD) and lung water level (LWL) monitoring. The study looked at two different types of MASs, narrowband (NB) and ultra-wideband (UWB), to decide which one was better. Unlike recent wearable respiratory sensors, these antennas are simple in design, low-profile, and affordable. The narrowband sensor employs an offset-feed microstrip transmission line, which has a bandwidth of 240 MHz at -10 dB reflection coefficient for the textile substrate. The UWB microwave sensor uses a CPW-fed line to excite an unbalanced U-shaped radiator, offering an extended simulated operating bandwidth from 1.5 to 10 GHz with impedance matching ≤-10 dB. Both types of microwave sensors are designed on a flexible RO 3003 substrate and textile conductive fabric attached to a cotton substrate. The specific absorption rate (SAR) of the sensors is measured at different resonant frequencies on 1 g and 10 g of tissue, according to the IEEE C95.3 standard, and both sensors meet the standard limit of 1.6 W/kg and 2 W/kg, respectively. A simple peak-detection algorithm is used to demonstrate high accuracy in the detection of respiration, heartbeat, and lung water content. Based on the experimental results on a child and an adult volunteer, it can be concluded that UWB MASs offer superior performance when compared to NB sensors.

IoT Based Health Monitoring System

Abstract: The rapid advancements in the Internet of Things (IoT) have paved the way for revolutionary healthcare solutions. This paper proposes an IoT-based health monitoring system aimed at providing continuous and remote monitoring of patients' vital signs and physiological parameters. This real-time data collection and analysis empowers proactive healthcare, enhancing patient safety and quality of life.

Tetanus Severity Classification in Low-Middle Income Countries through ECG Wearable Sensors and a 1D-Vision Transformer

Tetanus, a life-threatening bacterial infection prevalent in low- and middle-income countries like Vietnam, impacts the nervous system, causing muscle stiffness and spasms. Severe tetanus often involves dysfunction of the autonomic nervous system (ANS). Timely detection and effective ANS dysfunction management require continuous vital sign monitoring, traditionally performed using bedside monitors. However, wearable electrocardiogram (ECG) sensors offer a more cost-effective and user-friendly alternative. While machine learning-based ECG analysis can aid in tetanus severity classification, existing methods are excessively time-consuming. Our previous studies have investigated the improvement of tetanus severity classification using ECG time series imaging. In this study, our aim is to explore an alternative method using ECG data without relying on time series imaging as an input, with the aim of achieving comparable or improved performance. To address this, we propose a novel approach using a 1D-Vision Transformer, a pioneering method for classifying tetanus severity by extracting crucial global information from 1D ECG signals. Compared to 1D-CNN, 2D-CNN, and 2D-CNN + Dual Attention, our model achieves better results, boasting an F1 score of 0.77 ± 0.06, precision of 0.70 ± 0. 09, recall of 0.89 ± 0.13, specificity of 0.78 ± 0.12, accuracy of 0.82 ± 0.06 and AUC of 0.84 ± 0.05.

Executive Summary: Society of Critical Care Medicine Guidelines on Recognizing and Responding to Clinical Deterioration Outside the ICU.

Clinical deterioration of patients hospitalized outside the ICU is a source of potentially reversible morbidity and mortality. To address this, some acute care facilities have implemented systems aimed at detecting and responding to such patients. To provide evidence-based recommendations for hospital clinicians and administrators to optimize recognition and response to clinical deterioration in non-ICU patients. The 25-member panel included representatives from medicine, nursing, respiratory therapy, pharmacy, patient/family partners, and clinician-methodologists with expertise in developing evidence-based clinical practice guidelines. We generated actionable questions using the Population, Intervention, Control, and Outcomes format and performed a systematic review of the literature to identify and synthesize the best available evidence. We used the Grading of Recommendations Assessment, Development, and Evaluation approach to determine certainty in the evidence and to formulate recommendations and good practice statements (GPSs). The panel issued 10 statements on recognizing and responding to non-ICU patients with critical illness. Healthcare personnel and institutions should ensure that all vital sign acquisition is timely and accurate (GPS). We make no recommendation on the use of continuous vital sign monitoring among "unselected" patients due to the absence of data regarding the benefit and the potential harms of false positive alarms, the risk of alarm fatigue, and cost. We suggest focused education for bedside clinicians in signs of clinical deterioration, and we also suggest that patient/family/care partners' concerns be included in decisions to obtain additional opinions and help (both conditional recommendations). We recommend hospital-wide deployment of a rapid response team or medical emergency team (RRT/MET) with explicit activation criteria (strong recommendation). We make no recommendation about RRT/MET professional composition or inclusion of palliative care members on the responding team but suggest that the skill set of responders should include eliciting patients' goals of care (conditional recommendation). Finally, quality improvement processes should be part of a rapid response system (GPS). The panel provided guidance to inform clinicians and administrators on effective processes to improve the care of patients at-risk for developing critical illness outside the ICU.

Society of Critical Care Medicine Guidelines on Recognizing and Responding to Clinical Deterioration Outside the ICU: 2023.

Clinical deterioration of patients hospitalized outside the ICU is a source of potentially reversible morbidity and mortality. To address this, some acute care hospitals have implemented systems aimed at detecting and responding to such patients. To provide evidence-based recommendations for hospital clinicians and administrators to optimize recognition and response to clinical deterioration in non-ICU patients. The 25-member panel included representatives from medicine, nursing, respiratory therapy, pharmacy, patient/family partners, and clinician-methodologists with expertise in developing evidence-based Clinical Practice Guidelines. We generated actionable questions using the Population, Intervention, Control, and Outcomes (PICO) format and performed a systematic review of the literature to identify and synthesize the best available evidence. We used the Grading of Recommendations Assessment, Development, and Evaluation Approach to determine certainty in the evidence and to formulate recommendations and good practice statements (GPSs). The panel issued 10 statements on recognizing and responding to non-ICU patients with critical illness. Healthcare personnel and institutions should ensure that all vital sign acquisition is timely and accurate (GPS). We make no recommendation on the use of continuous vital sign monitoring among unselected patients. We suggest focused education for bedside clinicians in signs of clinical deterioration, and we also suggest that patient/family/care partners' concerns be included in decisions to obtain additional opinions and help (both conditional recommendations). We recommend hospital-wide deployment of a rapid response team or medical emergency team (RRT/MET) with explicit activation criteria (strong recommendation). We make no recommendation about RRT/MET professional composition or inclusion of palliative care members on the responding team but suggest that the skill set of responders should include eliciting patients' goals of care (conditional recommendation). Finally, quality improvement processes should be part of a rapid response system. The panel provided guidance to inform clinicians and administrators on effective processes to improve the care of patients at-risk for developing critical illness outside the ICU.

Three Years of Continuous Vital Signs Monitoring on the General Surgical Ward: Is It Sustainable? A Qualitative Study.

Continuous monitoring of vital signs using a wireless wearable device was implemented in 2018 at a surgical care unit of an academic hospital. This study aimed at gaining insight into nurses' and patients' perspectives regarding the use and innovation of a continuous vital signs monitoring system, three years after its introduction. This qualitative study was performed in a surgical, non-intensive care unit of an academic hospital in 2021. Key-user nurses (nurses with additional training and expertise with the device) and patients were selected for semi-structured interviews, and nurses from the ward were selected for a focus group interview using a topic list. Transcripts of the audio tapes were deductively analysed using four dimensions for adoptions of information and communication technologies (ICT) devices in healthcare. The device provided feelings of safety for nurses and patients. Nurses and patients had a few issues with the device, including the size and the battery life. Nurses gained knowledge and skills in using the system for measurement and interpretations. They perceived the system as a tool to improve the recognition of clinical decline. The use of the system could be further developed regarding the technical device's characteristics, nurses' interpretation of the data and the of type of alarms, the information needs of patients, and clarification of the definition and standardization of continuous monitoring. Three years after the introduction, wireless continuous vital signs monitoring is the new standard of care according to the end-users at the general surgical ward.

Enhancing well-being in modern education: A comprehensive eHealth proposal for managing stress and anxiety based on machine learning

In the evolving education landscape, institutions are transitioning to a hybrid model encompassing physical and virtual classes. In this scenario, as working hours and exhausting routines increase, individuals accumulate psychological and physical challenges over time. This change requires students and educators to adjust to changes in teaching and learning routines, leading to moments of stress and anxiety. Cultivating self-awareness about unhealthy habits emerges as a pragmatic strategy to address this issue. In this work, a comprehensive eHealth proposal is developed to provide individuals with pertinent health information, assisting educational agents (students and teachers) in identifying and managing these stressful instances during their daily activities. This proposal acquires, processes, and disseminates vital sign data using IoT devices, supported by a Fog Computing architecture for scalability and adaptability. IoT plays a pivotal role in this eHealth proposal, facilitating the seamless collection and transmission of real-time data from various devices. Connected wearables and sensors enable the continuous monitoring of vital signs, enhancing the accuracy and responsiveness of the system. Heart rate data from educational agents were collected for implementation, allowing the evaluation of system performance. Machine learning models were leveraged to discern behavioral profiles and predict possible irregularities in vital signs. The results confirm the system’s ability to perform its intended functions, giving users quick and accurate insights into their evolving behavioral patterns. Integrating these research perspectives underscores the importance of adaptive systems in navigating the challenges of modern education environments. The incorporation of IoT technology not only enhances data collection but also opens avenues for real-time interventions and personalized feedback, ultimately contributing to a more proactive approach in addressing health-related concerns within the educational context.

Surveillance of high-risk early postsurgical patients for real-time detection of complications using wireless monitoring (SHEPHERD study): results of a randomized multicenter stepped wedge cluster trial.

Vital signs measurements on the ward are performed intermittently. This could lead to failure to rapidly detect patients with deteriorating vital signs and worsens long-term outcome. The aim of this study was to test the hypothesis that continuous wireless monitoring of vital signs on the postsurgical ward improves patient outcome. In this prospective, multicenter, stepped-wedge cluster randomized study, patients in the control group received standard monitoring. The intervention group received continuous wireless monitoring of heart rate, respiratory rate and temperature on top of standard care. Automated alerts indicating vital signs deviation from baseline were sent to ward nurses, triggering the calculation of a full early warning score followed. The primary outcome was the occurrence of new disability three months after surgery. The study was terminated early (at 57% inclusion) due to COVID-19 restrictions. Therefore, only descriptive statistics are presented. A total of 747 patients were enrolled in this study and eligible for statistical analyses, 517 patients in the control group and 230 patients in the intervention group, the latter only from one hospital. New disability at three months after surgery occurred in 43.7% in the control group and in 39.1% in the intervention group (absolute difference 4.6%). This is the largest randomized controlled trial investigating continuous wireless monitoring in postoperative patients. While patients in the intervention group seemed to experience less (new) disability than patients in the control group, results remain inconclusive with regard to postoperative patient outcome due to premature study termination. ClinicalTrials.gov, ID: NCT02957825.

Flourishing electronic textiles towards pervasive, personalized and intelligent healthcare

In the face of pandemic infectious diseases and increasing aging trends, traditional public health systems lack the capacity for real-time monitoring, immediate clinical detection, continuous vital sign monitoring, and the implementation of long-cycle treatment protocols, among other deficiencies. On the basis of the rapid development of wearable electronic devices, the Internet of Things, and artificial intelligence, the future healthcare model will transform from a therapeutic, centralized, passive, and even one-size-fits-all treatment to a new paradigm of proactive, preventive, personalized, customized, and intelligent way. The development of wearable electronics has facilitated the evolution of healthcare from healthcare to biological monitoring, enabling continuous monitoring of critical biomarkers for diagnostic treatment, physiological health monitoring, and assessment. Electronic textiles (e-textiles) are among the rapidly developing wearable electronics in recent years. They have revolutionized the functionality of traditional textiles by incorporating smart attributes, enabling unique and multifunctional applications. Significantly, e-textiles have made notable advancements in the field of personalized healthcare. The article introduces several common e-textiles and their applications in personalized medicines, which also gives a forward-looking outlook on their future growth in infectious diseases, real-time health preventive monitoring, auxiliary therapy, and rehabilitation training.

Impact of wearable wireless continuous vital sign monitoring in abdominal surgical patients: before-after study.

Technological advances have enabled continuous monitoring of vital signs (CMVS) by wearable, wireless devices on general hospital wards to facilitate early detection of clinical deterioration, which could potentially improve clinical outcomes. However, evidence on the impact of these CMVS systems on patient outcomes is limited. This research aimed to explore the effect of CMVS on the clinical outcomes in major abdominal surgery patients in a general surgery ward. A single-centre before-after study was conducted from October 2019 to June 2022. Patients in the intervention group received CMVS in addition to conventional intermittent vital sign monitoring (standard care for control group). With CMVS, heart rate and respiratory rate were measured every 5 min by a patch sensor. Proactive vital signs trends assessments and, when necessary, subsequent nursing activities were performed every nursing shift. The primary outcome of interest was the length of hospital stay (LOS); also, 12 patient-related outcomes were analysed. In the CMVS group, follow-up nursing activities of deviating vital signs trends were described and patient acceptability was measured. Post-hoc subgroup analysis was performed for colorectal and hepatopancreatobiliary surgery. A total of 908 patients were included (colorectal: n = 650; hepatopancreatobiliary: n = 257). Overall, median LOS was lower in the CMVS group (5.0 versus 5.5 days; P = 0.012), respectively. Post-hoc subgroup analysis showed this reduction in LOS was mostly observed in the colorectal group and not in the hepatopancreatobiliary group. Apart from a decrease in nurse-to-house-officer calls (from 15.3% to 7.7%; P = 0.007), all secondary clinical outcomes were similar in CMVS and control groups. However, a non-significant trend towards less-severe complications and reduced ICU LOS was observed in the CMVS group. In CMVS patients, 109 additional nursing activities were performed and 83% of patients indicated CMVS was acceptable. CMVS was associated with a significant reduction in LOS, while other clinical outcomes were unchanged. CMVS triggered additional nursing activities such as extra patient assessments and therapeutic interventions.

Reliability of continuous vital sign monitoring in post-operative patients employing consumer-grade fitness trackers: A randomised pilot trial.

Fitness trackers can provide continuous monitoring of vital signs and thus have the potential to become a complementary, mobile and effective tool for early detection of patient deterioration and post-operative complications. To evaluate potential implementations in acute care setting, we included 36 patients after moderate to major surgery in a recent randomised pilot trial to compare the performance of vital sign monitoring by three different fitness trackers (Apple Watch 7, Garmin Fenix 6pro and Withings ScanWatch) with established standard clinical monitors in post-anaesthesia care units and monitoring wards. During a cumulative period of 56 days, a total of 53,197 heart rate (HR) measurements, as well as 12,219 measurements of the peripheral blood oxygen saturation (SpO2) and 28,954 respiratory rate (RR) measurements were collected by fitness trackers. Under real-world conditions, HR monitoring was accurate and reliable across all benchmarked devices (r = [0.95;0.98], p < 0.001; Bias = [-0.74 bpm;-0.01 bpm]; MAPE∼2%). However, the performance of SpO2 (r = [0.21;0.68]; p < 0.001; Bias = [-0.46%;-2.29%]; root-mean-square error = [2.82%;4.1%]) monitoring was substantially inferior. RR measurements could not be obtained for two of the devices, therefore exclusively the accuracy of the Garmin tracker could be evaluated (r = 0.28, p < 0.001; Bias = -1.46/min). Moreover, the time resolution of the vital sign measurements highly depends on the tracking device, ranging from 0.7 to 117.94 data points per hour. According to the results of the present study, tracker devices are generally reliable and accurate for HR monitoring, whereas SpO2 and RR measurements should be interpreted carefully, considering the clinical context of the respective patients.

Impact of continuous and wireless monitoring of vital signs on clinical outcomes: a propensity-matched observational study of surgical ward patients

BackgroundContinuous and wireless vital sign monitoring is superior to intermittent monitoring in detecting vital sign abnormalities; however, the impact on clinical outcomes has not been established. MethodsWe performed a propensity-matched analysis of data describing patients admitted to general surgical wards between January 2018 and December 2019 at a single, tertiary medical centre in the USA. The primary outcome was a composite of in-hospital mortality or ICU transfer during hospitalisation. Secondary outcomes were the odds of individual components of the primary outcome, and heart failure, myocardial infarction, acute kidney injury, and rapid response team activations. Data are presented as odds ratios (ORs) with 95% confidence intervals (CIs) and n (%). ResultsWe initially screened a population of 34,636 patients (mean age 58.3 (Range 18–101) yr, 16,456 (47.5%) women. After propensity matching, intermittent monitoring (n=12 345) was associated with increased risk of a composite of mortality or ICU admission (OR 3.42, 95% CI 3.19–3.67; P<0.001), and heart failure (OR 1.48, 95% CI 1.21–1.81; P<0.001), myocardial infarction (OR 3.87, 95% CI 2.71–5.71; P<0.001), and acute kidney injury (OR 1.32, 95% CI 1.09–1.57; P<0.001) compared with continuous wireless monitoring (n=7955). The odds of rapid response team intervention were similar in both groups (OR 0.86, 95% CI 0.79–1.06; P=0.726). ConclusionsPatients who received continuous ward monitoring were less likely to die or be admitted to ICU than those who received intermittent monitoring. These findings should be confirmed in prospective randomised trials.

Artificial Intelligence in anesthesia: Biotechnology applications for optimal patient outcomes

Artificial intelligence (AI) is revolutionizing various fields of medicine, and anesthesia is no exception. AI in anesthesia is not only streamlining the work of anesthesiologists but also improving patient outcomes. The integration of biotechnology and AI has created opportunities for personalized care in anesthesia, with the aim of optimizing patient outcomes. The use of biotechnology in conjunction with AI has further expanded the possibilities in anesthesia care. Biotechnology tools such as genomics and proteomics can provide insights into individual patient responses to anesthesia drugs, enabling personalized drug dosing and reducing the risk of adverse events. Similarly, the use of biosensors and wearable devices can provide continuous monitoring of vital signs and other physiological parameters, allowing for real-time adjustments to anesthesia care. In future the integration of AI and biotechnology in anesthesia care has the potential to transform the field of anesthesia and improve patient outcomes. The development of personalized care plans and the early identification of at-risk patients can lead to a safer and more efficient anesthesia experience for patients.