Continuous Monitoring of Heart Rate Variability in Free-Living Conditions Using Wearable Sensors: Exploratory Observational Study.

BACKGROUND: Wearable physiological monitoring devices are promising tools for remote monitoring and early detection of potential health changes of interest. The widespread adoption of such an approach across communities and over long periods of time will require an automated data platform for collecting, processing, and analyzing relevant health information. OBJECTIVE: In this study, we explore prospective monitoring of individual health through an automated data collection, metrics extraction, and health anomaly analysis pipeline in free-living conditions over a continuous monitoring period of several months with a focus on viral respiratory infections, such as influenza or COVID-19. METHODS: A total of 59 participants provided smartwatch data and health symptom and illness reports daily over an 8-month window. Physiological and activity data from photoplethysmography sensors, including high-resolution interbeat interval (IBI) and step counts, were uploaded directly from Garmin Fenix 6 smartwatches and processed automatically in the cloud using a stand-alone, open-source analytical engine. Health risk scores were computed based on a deviation in heart rate and heart rate variability metrics from each individual's activity-matched baseline values, and scores exceeding a predefined threshold were checked for corresponding symptoms or illness reports. Conversely, reports of viral respiratory illnesses in health survey responses were also checked for corresponding changes in health risk scores to qualitatively assess the risk score as an indicator of acute respiratory health anomalies. RESULTS: The median average percentage of sensor data provided per day indicating smartwatch wear compliance was 70%, and survey responses indicating health reporting compliance was 46%. A total of 29 elevated health risk scores were detected, of which 12 (41%) had concurrent survey data and indicated a health symptom or illness. A total of 21 influenza or COVID-19 illnesses were reported by study participants; 9 (43%) of these reports had concurrent smartwatch data, of which 6 (67%) had an increase in health risk score. CONCLUSIONS: We demonstrate a protocol for data collection, extraction of heart rate and heart rate variability metrics, and prospective analysis that is compatible with near real-time health assessment using wearable sensors for continuous monitoring. The modular platform for data collection and analysis allows for a choice of different wearable sensors and algorithms. Here, we demonstrate its implementation in the collection of high-fidelity IBI data from Garmin Fenix 6 smartwatches worn by individuals in free-living conditions, and the prospective, near real-time analysis of the data, culminating in the calculation of health risk scores. To our knowledge, this study demonstrates for the first time the feasibility of measuring high-resolution heart IBI and step count using smartwatches in near real time for respiratory illness detection over a long-term monitoring period in free-living conditions.

A two-year examination of the relation between internal and external load and heart rate variability in Australian Rules Football.

The relationship between heart rate variability (HRV) and training load in team-sport is unknown. We therefore assessed relations between completed training-load in the previous 1-, 3- and 7-days and waking HRV in professional Australian Rules Football. Linear-mixed models analysed changes in HRV, considering training load from the previous 1-, 3- and 7-days. Total Distance (TD), distance >14.4 km ‧ h-1 (HSR) and >24.9 km ‧ h-1 (Sprint-Distance), duration >85% max heart rate and Rating of Perceived Exertion were included as independent variables. Sub-group analysis of season-phase and years of professional experience was also conducted. Increased three-day Sprint-Distance reduced HRV in the first 8-weeks of pre-season (-13.1 ms, p = 0.03) and across the data collection period (-3.75 ms, p = 0.01). In first-year players, higher previous-day (-63.3 ms, p=0.04) and seven-day TD (-38.2 ms, p = 0.02) reduced HRV, whilst higher seven-day HSR increased HRV (34.5 ms, p = 0.01). In players with five-to-seven years of professional experience, higher three-day (-14.4 ms, p = 0.02) and seven-day TD (-15.7 ms, p = 0.01) reduced HRV, while higher three-day HSR increased HRV (12.5 ms, p = 0.04). In players with greater than eight years of professional experience, higher previous-day Sprint-Distance reduced HRV (-13.1 ms, p < 0.008). Completed training load across the previous 7-days influences HRV, but the relation between variables is complex and influenced by professional experience and season-phase.

A practical guide for selecting continuous monitoring wearable devices for community-dwelling adults.

Importance: The burgeoning landscape of wearable devices warrants a guide for the selection of devices. Existing guidelines and recommendations provide evaluation frameworks with theoretical principles but tend to lack a pragmatic application and systematic approach for device selection. While fitness trackers exemplify the convenience of wearable technologies, their selection for specific health monitoring purposes demands a nuanced understanding of varying functionalities and user compatibilities. Objective: The objective is to develop and present a practical guide for researchers, healthcare professionals, and device users to systematically select wearable devices for continuous monitoring in community-dwelling adults. Methods & results: Based on diverse sources, such as the United States Food and Drug Administration (FDA), the Clinical Trials Transformation Initiative (CTTI), the Electronic Patient-Reported Outcome (ePRO) Consortium, and comparative analyses of wearable technology performances from feasibility and usability studies, the guide incorporates five core criteria: continuous monitoring capability, device availability and suitability, technical performance (accuracy and precision), feasibility of use, and cost evaluation. The structured criteria can be applied in device selection as well as device evaluation. Conclusions: This practical guide provides a step-by-step solution for researchers, healthcare professionals, and device users to choose suitable wearable devices for continuous monitoring. It provides a comprehensive starting point, outlining how to effectively navigate the selection process for wearable devices amidst a plethora of similar options.

Thermal mapping: Assessing the optimal sites for temperature measurement in the human body and emerging technologies.

Numerous body locations have been utilized to obtain an accurate body temperature. While some are commonly used, their accuracy, response time, invasiveness varies greatly, and determines their potential clinical and/or research use. This review discusses human body temperature locations, their accuracy, ease of use, advantages, and drawbacks. We explain the concept of core body temperature and which of the locations achieve the best correlation to this temperature. The body locations include axilla, oral cavity, rectum, digestive and urinary tracts, skin, tympanic, nasopharynx, esophagus, and pulmonary artery. The review also discusses the latest temperature technologies, heat-flux technology and telemetric ingestible temperature pills, and the body locations used to validate these devices. Rectal and esophageal measurements are the most frequently used.

Integrated pulmonary index during procedural sedation and analgesia: A cluster-randomized trial.

AIM: To evaluate the effectiveness of utilizing the integrated pulmonary index for capnography implementation during sedation administered by nurses. DESIGN: Cluster-randomized trial. METHODS: Participants were enrolled from the interventional radiology department at an academic hospital in Canada. Nurses were randomized to either enable or disable the Integrated Pulmonary Index feature of the capnography monitor. Procedures were observed by a research assistant to collect information about alarm performance characteristics. The primary outcome was the number of seconds in an alert condition state without an intervention being applied. RESULTS: The number of seconds in an alarm state without intervention was higher in the group that enabled the integrated pulmonary index compared to the group that disabled this feature, but this difference did not reach statistical significance. Likewise, the difference between groups for the total alarm duration, total number of alarms and the total number of appropriate alarms was not statistically significant. The number of inappropriate alarms was higher in the group that enabled the Integrated Pulmonary Index, but this estimate was highly imprecise. There was no difference in the odds of an adverse event (measured by the Tracking and Reporting Outcomes of Procedural Sedation tool) occurring between groups. Desaturation events were uncommon and brief in both groups but the area under the SpO2 90% desaturation curve scores were lower for the group that enabled the integrated pulmonary index. CONCLUSION: Enabling the integrated pulmonary index during nurse-administered procedural sedation did not reduce nurses' response times to alarms. Therefore, integrating multiple physiological parameters related to respiratory assessment into a single index did not lower the threshold for intervention by nurses. IMPLICATIONS FOR THE PROFESSION AND/OR PATIENT CARE: The time it takes to respond to capnography monitor alarms will not be reduced if the integrated pulmonary Iindex feature of capnography monitors is enabled during nurse-administered procedural sedation. IMPACT: Results do not support the routine enabling of the integrated pulmonary index when nurses use capnography to monitor patients during procedural sedation as a strategy to reduce the time it takes to initiate responses to alarms. REPORTING METHOD: CONSORT. PATIENT OR PUBLIC CONTRIBUTION: There was no patient or public contribution. TRIAL REGISTRATION: This study was prospectively registered at ClinicalTrials.gov (ID: NCT05068700).

Risk of unfavorable pain prognosis impacts walking physiomechanical parameters and psychophysiological workload in sufferers of chronic low back pain.

BACKGROUND: Tolerating physical tasks depends not only on task-specific characteristics but also on an individual's psychophysiological capacity to respond to the imposed load. People suffering from chronic low back pain (CLBP) may experience reduced psychophysiological capacity and are at risk for poor pain prognosis, which could lead to an increased walking workload. AIM: To investigate how the risk of unfavorable pain prognosis in CLBP can impact walking physiomechanical parameters and psychophysiological workload. METHODS: A cross-sectional observational study. The study classified 74 volunteers into four groups based on their prognosis for pain: pain-free control (CG/n = 20), low (LrG/n = 21), medium (MrG/n = 22), and high (HrG/n = 11) risk of poor prognosis for CLBP. The ground assessments identified the self-selected (SSW) and optimal (OWS) walking speeds, as well as the locomotor rehabilitation index (LRI). Treadmill assessments were conducted at two different speeds (0.83 and 1.11 m s-1, SSW and OWS) to record physiomechanical parameters. Psychophysiological workloads during walking were measured via workload impulse for the session (TRIMP), determined by variations in heart rate. RESULTS: CLBP groups exhibited slower SSW and lower LRI compared to the CG. The TRIMP was lower in the LrG. However, both MrG and HrG exhibited a comparable overload to the CG, even while walking at a lower intensity with a psychophysical demand. SSW and OWS displayed an increased TRIMP compared to fixed speeds. CONCLUSION: Psychosocial factors may affect SSW in people with CLBP but not among the risk strata. An unfavorable prognosis for pain could jeopardize the psychophysiological capacity to withstand walking demands.

Accuracy of the SenseWear Armband during Short Bouts of Exercise.

A goal of mobile monitoring is to approximate metabolic energy expenditure (EE) during activities of daily living and exercise. Many physical activity monitors are inaccurate with respect to estimated EE and differentiating between activities that occur over short intervals. The objective of our study was to assess the validity of the SenseWear Armband (SWA) compared to indirect calorimetry (IC) during short intervals of walking and running. Twenty young, fit participants walked (preferred speed) and ran (75%, 85%, and 95% of predicted VO2max run speeds) on a treadmill. EE estimates from IC, SWA, and prediction equations that used the SWA, speed, and heart rate were examined during each 4 min interval and across the whole protocol (Total). The level of significance was p < 0.05. The SWA overestimated EE relative to IC by 1.62 kcal·min-1 while walking and 1.05 kcal·min-1 while running at 75%. However, it underestimated EE at the 85% (0.05 kcal·min-1) and 95% (0.92 kcal·min-1) speeds, but not significantly, and overestimated total EE by 28.29 kcal. Except for walking, our results suggest that the SWA displayed a good level of agreement (ICC = 0.76 to 0.84) with IC measures. Activity-specific algorithms using SWA, speed, and heart rate improved EE estimates, based on the standard error of the estimates, but perhaps not enough to justify extra sensors. The SWA may enable EE estimation of locomotion outside the laboratory, including those with short bouts of high intensity activity, but continued development of the SWA, or devices like it, is needed to enable accurate monitoring.

Feasibility and acceptability of remotely monitoring spirometry and pulse oximetry as part of interstitial lung disease clinical care: a single arm observational study.

BACKGROUND: Remote monitoring of patient-recorded spirometry and pulse oximetry offers an alternative approach to traditional hospital-based monitoring of interstitial lung disease (ILD). Remote spirometry has been observed to reasonably reflect clinic spirometry in participants with ILD but remote monitoring has not been widely incorporated into clinical practice. We assessed the feasibility of remotely monitoring patients within a clinical ILD service. METHODS: Prospective, single-arm, open-label observational multi-centre study (NCT04850521). Inclusion criteria included ILD diagnosis, age ≥ 18 years, FVC ≥ 50% predicted. 60 participants were asked to record a single spirometry and oximetry measurement at least once daily, monitored weekly by their local clinical team. Feasibility was defined as ≥ 68% of participants with ≥ 70% adherence to study measurements and recording measurements ≥ 3 times/week throughout. RESULTS: A total of 60 participants were included in the analysis. 42/60 (70%) were male; mean age 67.8 years (± 11.2); 34/60 (56.7%) had idiopathic pulmonary fibrosis (IPF), Median ILD-GAP score was 3 (IQR 1-4.75). Spirometry adherence was achieved for ≥ 70% of study days in 46/60 participants (77%) and pulse oximetry adherence in 50/60 participants (83%). Recording ≥ 3 times/week every week was provided for spirometry in 41/60 participants (68%) and pulse oximetry in 43/60 participants (72%). Mean difference between recent clinic and baseline home spirometry was 0.31 L (± 0.72). 85.7% (IQR 63.9-92.6%) home spirometry attempts/patient were acceptable or usable according to ERS/ATS spirometry criteria. Positive correlation was observed between ILD-GAP score and adherence to spirometry and oximetry (rho 0.24 and 0.38 respectively). Adherence of weekly monitoring by clinical teams was 80.95% (IQR 64.19-95.79). All participants who responded to an experience questionnaire (n = 33) found remote measurements easy to perform and 75% wished to continue monitoring their spirometry at the conclusion of the study. CONCLUSION: Feasibility of remote monitoring within an ILD clinical service was demonstrated over 3 months for both daily home spirometry and pulse oximetry of patients. Remote monitoring may be more acceptable to participants who are older or have more advanced disease. TRIAL REGISTRATION: clinicaltrials.gov NCT04850521 registered 20th April 2021.

Integrating Smartphone Applications and Wearable Devices for Postoperative Rehabilitation in Total Knee Arthroplasty: A Critical Review.

BACKGROUND: Smartphone and wearable technologies offer innovative methods for monitoring postoperative recovery in total knee arthroplasty (TKA) patients. This review assessed the benefits of these technologies in postoperative care, focusing on (1) smartphone applications, (2) wearable devices, and (3) their combination. METHODS: A systematic search identified studies on smartphone applications and wearables for post-TKA monitoring. The review analyzed 2,119 studies, with 58 meeting criteria: 25 on applications, 25 on wearables, and 8 on both. Studies were rated with a methodology index as well as by levels of evidence. They were then analyzed by categorizing them by adherence and patient satisfaction, functional outcomes and pain scores, gait analyses and ranges of motion, and measurement and comparison tools. RESULTS: A review of 24 of 25 publications related to smartphone applications used for postoperative recovery in TKA showed the potential for improved patient's satisfaction, gait recovery, pain medication scheduling guidance with improved pain management, cost savings, and functional outcomes. Wearable technologies used in postoperative recovery demonstrated monitoring accuracy in 25 studies. These devices also showed effectiveness in gait and motion analysis. Other demonstrated benefits of the wearables were improved outcomes, return to function, cost reduction, and again, better management of pain due to patient interaction and guidance. Studies that combined applications and wearables demonstrated the individual findings with the addition of adherence, patient's satisfaction, and overall mobility improvement at 3 months. CONCLUSIONS: Smartphone applications and wearables can enhance postoperative rehabilitation for TKA patients. Smartphone applications and wearables have been shown in randomized trials to be accurate, effective, and useful in the postoperative rehabilitation of TKA patients. A recurring theme in the review was improved adherence to care plans and medication schedules that ultimately result in improved functional outcomes. These technologies and the data that they generate offer direct patient benefits and the potential for future cost savings.

A profile of occupational tasks performed by mounted police officers.

BACKGROUND: Within individual policing organisations, there are a wide variety of units and job roles. OBJECTIVE: To profile the occupational tasks performed by Australian mounted police officers, aiming to offer conditioning insight into this unique job role. METHODS: Thirteen fully qualified and operational mounted police officers (n = 11 females), who served in the mounted police unit for ∼3.3 (±2.3) years, participated in this observational cohort study. Participants completed a survey outlining common occupational tasks and were monitored throughout four consecutive shifts. Participants' heart rate (HR), respiratory rate (RR), and skin temperature (ST) data were collected via wearable monitoring (Equivital EQ-02, Hidalgo, UK) and body position, physical activity undertaken, task effort, and load carriage were recorded by researchers. A one-way ANOVA was used to assess mean differences in physiological measures between the three most reported tasks. RESULTS: Survey identified 130 tasks, with 38 listed as most common. The three most reported mounted police tasks were: 'horse riding' (n = 13, 34%), 'mounted patrols' (n = 10, 26%), and 'horse care' (n = 10, 26%). These were also reported as the most physically demanding. HR during 'horse care' and 'horse riding' were significantly higher than when 'mounted patrolling' (27±7bpm, p = 0.001 and 33±8bpm; p = 0.001, respectively). Mean RR was higher when 'horse riding' when compared to 'horse care' (5.3±1.6brpm) and 'mounted patrol' (8.5±1.9brpm). CONCLUSION: Mounted police officers experience unique physiological challenges throughout their routine occupational tasks. This study highlights the significance of understanding occupation-specific tasks and stressors undertaken by mounted police to develop relevant conditioning, rehabilitation, and monitoring procedures.

Pain assessment tools in adults with communication disorders: systematic review and meta-analysis.

BACKGROUND: Verbal communication is the "gold standard" for assessing pain. Consequently, individuals with communication disorders are particularly vulnerable to incomplete pain management. This review aims at identifying the current pain assessment instruments for adult patients with communication disorders. METHODS: A systematic review with meta-analysis was conducted on PubMed, PEDRO, EBSCOhost, VHL and Cochrane databases from 2011 to 2023 using MeSH terms "pain assessment, "nonverbal communication" and "communication disorders" in conjunction with additional inclusion criteria: studies limited to humans, interventions involving adult patients, and empirical investigations. RESULTS: Fifty articles were included in the review. Seven studies report sufficient data to perform the meta-analysis. Observational scales are the most common instruments to evaluate pain in individuals with communication disorders followed by physiological measures and facial recognition systems. While most pain assessments rely on observational scales, current evidence does not strongly endorse one scale over others for clinical practice. However, specific observational scales appear to be particularly suitable for identifying pain during certain potentially painful procedures, such as suctioning and mobilization, in these populations. Additionally, specific observational scales appear to be well-suited for certain conditions, such as mechanically ventilated patients. CONCLUSIONS: While observational scales dominate pain assessment, no universal tool exists for adults with communication disorders. Specific scales exhibit promise for distinct populations, yet the diverse landscape of tools hampers a one-size-fits-all solution. Crucially, further high-quality research, offering quantitative data like reliability findings, is needed to identify optimal tools for various contexts. Clinicians should be informed to select tools judiciously, recognizing the nuanced appropriateness of each in diverse clinical situations. TRIAL REGISTRATION: This systematic review is registered in PROSPERO (International prospective register of systematic reviews) with the ID: CRD42022323655 .

Cardiorespiratory Sensors and Their Implications for Out-of-Hospital Cardiac Arrest Detection: A Systematic Review.

Out-of-hospital cardiac arrest (OHCA) is a major health problem, with a poor survival rate of 2-11%. For the roughly 75% of OHCAs that are unwitnessed, survival is approximately 2-4.4%, as there are no bystanders present to provide life-saving interventions and alert Emergency Medical Services. Sensor technologies may reduce the number of unwitnessed OHCAs through automated detection of OHCA-associated physiological changes. However, no technologies are widely available for OHCA detection. This review identifies research and commercial technologies developed for cardiopulmonary monitoring that may be best suited for use in the context of OHCA, and provides recommendations for technology development, testing, and implementation. We conducted a systematic review of published studies along with a search of grey literature to identify technologies that were able to provide cardiopulmonary monitoring, and could be used to detect OHCA. We searched MEDLINE, EMBASE, Web of Science, and Engineering Village using MeSH keywords. Following inclusion, we summarized trends and findings from included studies. Our searches retrieved 6945 unique publications between January, 1950 and May, 2023. 90 studies met the inclusion criteria. In addition, our grey literature search identified 26 commercial technologies. Among included technologies, 52% utilized electrocardiography (ECG) and 40% utilized photoplethysmography (PPG) sensors. Most wearable devices were multi-modal (59%), utilizing more than one sensor simultaneously. Most included devices were wearable technologies (84%), with chest patches (22%), wrist-worn devices (18%), and garments (14%) being the most prevalent. ECG and PPG sensors are heavily utilized in devices for cardiopulmonary monitoring that could be adapted to OHCA detection. Developers seeking to rapidly develop methods for OHCA detection should focus on using ECG- and/or PPG-based multimodal systems as these are most prevalent in existing devices. However, novel sensor technology development could overcome limitations in existing sensors and could serve as potential additions to or replacements for ECG- and PPG-based devices.

The utility of heart rate and heart rate variability to identify limits of tolerance to moderate-intensity work in the heat: a secondary analysis.

We investigated the utility of heart rate (HR) and heart rate variability (HRV) for identifying individuals who may terminate work early due to excessive heat strain. Forty-eight men and women (median = 36 years; Q1 = 20 years; Q3 = 54 years) attempted 180 min of moderate-intensity work at a fixed metabolic rate (∼200 W/m2; ∼3.5 METs) in a hot environment (wet-bulb globe temperature: 32 °C). Receiver operating characteristics (ROC) curves were used to identify the ability of indices of HR (absolute HR, percentage of maximum HR, percentage of HR reserve) and HRV (root-mean-square of successive differences (RMSSD), high-frequency power, and detrended fluctuation analysis component alpha 1 (DFA α1)) to discriminate between participants who completed the 180 min work bout or terminated prematurely. Participants who terminated work prematurely (n = 26) exhibited higher HR and percentage of HR measures, as well as reduced RMSSD and DFA α1 after the first hour of work compared to participants who completed the bout. The discriminative utility of HR and HRV indices was strongest within the first hour of work, with percentage of HR reserve demonstrating excellent discriminative power (ROC area under curve (AUC) of 0.8). Stratifying participants by age and sex improved ROC AUC point estimates for most indices, particularly in female participants. The study provides preliminary evidence supporting the use of noninvasive cardiac monitoring for predicting work tolerance in healthy individuals exposed to occupational heat stress. HR and percentage of HR reserve were suggested to discriminate work termination most effectively. Further investigations are warranted to explore the influence of individual factors and refine the discriminative thresholds for early identification of excessive occupational heat strain.

A Novel Continuous Real-Time Vital Signs Viewer for Intensive Care Units: Design and Evaluation Study.

BACKGROUND: Clinicians working in intensive care units (ICUs) are immersed in a cacophony of alarms and a relentless onslaught of data. Within this frenetic environment, clinicians make high-stakes decisions using many data sources and are often oversaturated with information of varying quality. Traditional bedside monitors only depict static vital signs data, and these data are not easily viewable remotely. Clinicians must rely on separate nursing charts-handwritten or electric-to review physiological patterns, including signs of potential clinical deterioration. An automated physiological data viewer has been developed to provide at-a-glance summaries and to assist with prioritizing care for multiple patients who are critically ill. OBJECTIVE: This study aims to evaluate a novel vital signs viewer system in a level 1 trauma center by subjectively assessing the viewer's utility in a high-volume ICU setting. METHODS: ICU attendings were surveyed during morning rounds. Physicians were asked to conduct rounds normally, using data reported from nurse charts and briefs from fellows to inform their clinical decisions. After the physician finished their assessment and plan for the patient, they were asked to complete a questionnaire. Following completion of the questionnaire, the viewer was presented to ICU physicians on a tablet personal computer that displayed the patient's physiologic data (ie, shock index, blood pressure, heart rate, temperature, respiratory rate, and pulse oximetry), summarized for up to 72 hours. After examining the viewer, ICU physicians completed a postview questionnaire. In both questionnaires, the physicians were asked questions regarding the patient's stability, status, and need for a higher or lower level of care. A hierarchical clustering analysis was used to group participating ICU physicians and assess their general reception of the viewer. RESULTS: A total of 908 anonymous surveys were collected from 28 ICU physicians from February 2015 to June 2017. Regarding physicians' perception of whether the viewer enhanced the ability to assess multiple patients in the ICU, 5% (45/908) strongly agreed, 56.6% (514/908) agreed, 35.3% (321/908) were neutral, 2.9% (26/908) disagreed, and 0.2% (2/908) strongly disagreed. CONCLUSIONS: Morning rounds in a trauma center ICU are conducted in a busy environment with many data sources. This study demonstrates that organized physiologic data and visual assessment can improve situation awareness, assist clinicians with recognizing changes in patient status, and prioritize care.

Effect of protocol-based family visitation on physiological indicators in ICU patients: a randomized controlled trial.

BACKGROUND: Intensive care unit (ICU) patients often experience significant physiological stress. This study evaluated the effect of a defined family visitation protocol on physiological responses in the ICU. METHODS: A randomized, block-randomized clinical trial was conducted on 78 ICU patients at Imam Reza Hospital between February 8, 2017, and August 8, 2017. The intervention group received protocol-based visits, and the control group continued with standard visitation. Block randomization was utilized for group assignments. The primary outcome was the measurement of physiological signs using designated monitoring devices. Data were analyzed using SPSS version 22, employing independent t-tests, Mann-Whitney U test, repeated measures analysis, and Friedman's test. RESULTS: The results showed no significant differences in systolic blood pressure, diastolic blood pressure, mean arterial pressure, respiratory rate, and arterial blood oxygen levels between the two groups. However, heart rate in the intervention group was significantly lower in three stages before, during, and after the meaningful visiting (P = 0.008). CONCLUSION: Protocol-based scheduled family visits in the ICU may reduce physiological stress, as evidenced by a decrease in patients' heart rate. Implementing tailored visitation protocols sensitive to patient preferences and clinical contexts is advisable, suggesting the integration of family visits into standard care practices for enhanced patient outcomes. TRIAL REGISTRATION: IRCT20161229031654N2; 25/01/2018; Iranian Registry of Clinical Trials ( https://en.irct.ir ).

Were Frailty Identification Criteria Created Equal? A Comparative Case Study on Continuous Non-Invasively Collected Neurocardiovascular Signals during an Active Standing Test in the Irish Longitudinal Study on Ageing (TILDA).

BACKGROUND: In this observational study, we compared continuous physiological signals during an active standing test in adults aged 50 years and over, characterised as frail by three different criteria, using data from The Irish Longitudinal Study on Ageing (TILDA). METHODS: This study utilised data from TILDA, an ongoing landmark prospective cohort study of community-dwelling adults aged 50 years or older in Ireland. The initial sampling strategy in TILDA was based on random geodirectory sampling. Four independent groups were identified: those characterised as frail only by one of the frailty tools used (the physical Frailty Phenotype (FP), the 32-item Frailty Index (FI), or the Clinical Frailty Scale (CFS) classification tree), and a fourth group where participants were not characterised as frail by any of these tools. Continuous non-invasive physiological signals were collected during an active standing test, including systolic (sBP) and diastolic (dBP) blood pressure, as well as heart rate (HR), using digital artery photoplethysmography. Additionally, the frontal lobe cerebral oxygenation (Oxy), deoxygenation (Deoxy), and tissue saturation index (TSI) were also non-invasively measured using near-infrared spectroscopy (NIRS). The signals were visualised across frailty groups and statistically compared using one-dimensional statistical parametric mapping (SPM). RESULTS: A total of 1124 participants (mean age of 63.5 years; 50.2% women) were included: 23 were characterised as frail only by the FP, 97 by the FI, 38 by the CFS, and 966 by none of these criteria. The SPM analyses revealed that only the group characterised as frail by the FI had significantly different signals (p < 0.001) compared to the non-frail group. Specifically, they exhibited an attenuated gain in HR between 10 and 15 s post-stand and larger deficits in sBP and dBP between 15 and 20 s post-stand. CONCLUSIONS: The FI proved to be more adept at capturing distinct physiological responses to standing, likely due to its direct inclusion of cardiovascular morbidities in its definition. Significant differences were observed in the dynamics of cardiovascular signals among the frail populations identified by different frailty criteria, suggesting that caution should be taken when employing frailty identification tools on physiological signals, particularly the neurocardiovascular signals in an active standing test.

Personalized ECG monitoring and adaptive machine learning.

This non-technical review introduces key concepts in personalized ECG monitoring (pECG), which aims to optimize the detection of clinical events and their warning signs as well as the selection of alarm thresholds. We review several pECG methods, including anomaly detection and adaptive machine learning (ML), in which learning is performed sequentially as new data are collected. We describe a distributed-network multiscale pECG system to show how the computational load and time associated with adaptive ML could be optimized. In this architecture, the limited analysis of ECG waveforms is performed locally (e.g., on a smart phone) to determine a small number of clinically important ECG elements, and an adaptive ML engine is located on a remote server (Internet cloud) to determine an individual's "fingerprint" basis patterns and to detect anomalies in those patterns.

Continuous Electrocardiographic Monitoring for 24 Hours Before Death in Patients with Terminal Cancer.

BACKGROUND: Purposeless physiological monitoring at the end-of-life is not recommended. However, studies on how families feel regarding the death of patients with terminal cancer without continuous electrocardiographic monitoring (CEM) are lacking. OBJECTIVES: To explore the impact on the quality of care and the feelings and psychological distress experienced by families when CEM is not used during the 24 hours preceding a patient's death. METHODS: In this multicenter cross-sectional, self-report questionnaires were distributed to 1087 bereaved families at Japanese specialized palliative care units in 2018. RESULTS: Out of 671 responses, 394 valid responses were analyzed. Families of nonmonitored patients (NM-group) accounted for 79.2%, while those with bedside electrocardiogram monitoring (MB-group) and remote nurse station monitoring (MC-group) comprised 11.9% and 8.9%, respectively. In the NM-group, 85.5% expressed satisfaction without CEM, which was more than 10% lower than other groups. While 14% in the NM-group desired patient monitoring, families who received adequate explanations about CEM had lower proportions compared to the MB-group (P = .021). Univariate analyses showed no significant differences in evaluations of the quality of care and families' psychological distress (mean scores of Overall Care Satisfaction, Care Evaluation Scale, Good Death Inventory, Brief Grief Questionnaires) across all groups. CONCLUSION: While the majority of NM-group were satisfied with their patient's care without CEM, the proportion of dissatisfied families was higher than in other groups. Although not using CEM is not a major hindrance to end-of-life care for patients with terminal cancer, providing sufficient explanations may be important for satisfactory care.

Predicting Cardiopulmonary Arrest with Digital Biomarkers: A Systematic Review.

(1) Background: Telemetry units allow the continuous monitoring of vital signs and ECG of patients. Such physiological indicators work as the digital signatures and biomarkers of disease that can aid in detecting abnormalities that appear before cardiac arrests (CAs). This review aims to identify the vital sign abnormalities measured by telemetry systems that most accurately predict CAs. (2) Methods: We conducted a systematic review using PubMed, Embase, Web of Science, and MEDLINE to search studies evaluating telemetry-detected vital signs that preceded in-hospital CAs (IHCAs). (3) Results and Discussion: Out of 45 studies, 9 met the eligibility criteria. Seven studies were case series, and 2 were case controls. Four studies evaluated ECG parameters, and 5 evaluated other physiological indicators such as blood pressure, heart rate, respiratory rate, oxygen saturation, and temperature. Vital sign changes were highly frequent among participants and reached statistical significance compared to control subjects. There was no single vital sign change pattern found in all patients. ECG alarm thresholds may be adjustable to reduce alarm fatigue. Our review was limited by the significant dissimilarities of the studies on methodology and objectives. (4) Conclusions: Evidence confirms that changes in vital signs have the potential for predicting IHCAs. There is no consensus on how to best analyze these digital biomarkers. More rigorous and larger-scale prospective studies are needed to determine the predictive value of telemetry-detected vital signs for IHCAs.

[Development of intelligent monitoring system based on Internet of Things and wearable technology and exploration of its clinical application mode].

Wearable monitoring, which has the advantages of continuous monitoring for a long time with low physiological and psychological load, represents a future development direction of monitoring technology. Based on wearable physiological monitoring technology, combined with Internet of Things (IoT) and artificial intelligence technology, this paper has developed an intelligent monitoring system, including wearable hardware, ward Internet of Things platform, continuous physiological data analysis algorithm and software. We explored the clinical value of continuous physiological data using this system through a lot of clinical practices. And four value points were given, namely, real-time monitoring, disease assessment, prediction and early warning, and rehabilitation training. Depending on the real clinical environment, we explored the mode of applying wearable technology in general ward monitoring, cardiopulmonary rehabilitation, and integrated monitoring inside and outside the hospital. The research results show that this monitoring system can be effectively used for monitoring of patients in hospital, evaluation and training of patients' cardiopulmonary function, and management of patients outside hospital.