Detection of health deterioration in a COVID-19 patient at home: the potential of ambient sensor systems

The COVID-19 pandemic created increased interest in monitoring patients at home to allow timely recognition of health deteriorations. Hospital care is particularly demanding in these patients because of the necessity for isolation to avoid further spread of the disease. Therefore, home care is a preferred treatment setting for these patients. This is, to our knowledge, the first report indicating the potential of an affordable, contactless, and unobtrusive ambient sensor system for the detection of signs of health deterioration in a patient with COVID-19 by a caregiver from a distance. Prospective data acquisition and correlation of the data with clinical events were obtained from an 81-year-old senior with COVID-19 before and, in particular, over a period of 10 days prior to hospitalization. Clinical signs included weakness, increased respiration rate, sleep disturbances, and confusion. The visualization of a combination of this information on a dedicated dashboard allowed the caregiver to recognize a serious health deterioration that required a lifesaving hospitalization. The potential of such ambient sensor systems to detect signs of serious health deterioration in patients with COVID-19 opens new opportunities for use in asymptomatic or oligosymptomatic patients who live alone and are sent back to their homes for isolation in quarantine after diagnosis

Combating Alarm Fatigue: The Quest for More Accurate and Safer Clinical Monitoring Equipment

As the demand for health-care services continues to increase, clinically efficient and cost-effective patient monitoring takes on a critically important role. Key considerations inherent to this area of concern include patient safety, reliability, ease of use, and cost containment. Unfortunately, even the most modern patient monitoring systems carry significant drawbacks that limit their effectiveness and/or applicability. Major opportunities for improvement in both equipment design and monitor utilization have been identified, including the presence of excessive false and nuisance alarms. When poorly optimized, clinical alarm activity can affect patient safety and may have a negative impact on care providers, leading to inappropriate alarm response time due to the so-called alarm fatigue (AF). Ultimately, consequences of AF include missed alerts of clinical significance, with substantial risk for patient harm and potentially fatal outcomes. Targeted quality improvement initiatives and staff training, as well as the proactive incorporation of technological improvements, are the best approaches to address key barriers to the optimal utilization of clinical alarms, AF reduction, better patient care, and improved provider job satisfaction

Continuous sensing and quantification of body motion in infants:A systematic review

Abnormal body motion in infants may be associated with neurodevelopmental delay or critical illness. In contrast to continuous patient monitoring of the basic vitals, the body motion of infants is only determined by discrete periodic clinical observations of caregivers, leaving the infants unattended for observation for a longer time. One step to fill this gap is to introduce and compare different sensing technologies that are suitable for continuous infant body motion quantification. Therefore, we conducted this systematic review for infant body motion quantification based on the PRISMA method (Preferred Reporting Items for Systematic Reviews and Meta-Analyses). In this systematic review, we introduce and compare several sensing technologies with motion quantification in different clinical applications. We discuss the pros and cons of each sensing technology for motion quantification. Additionally, we highlight the clinical value and prospects of infant motion monitoring. Finally, we provide suggestions with specific needs in clinical practice, which can be referred by clinical users for their implementation. Our findings suggest that motion quantification can improve the performance of vital sign monitoring, and can provide clinical value to the diagnosis of complications in infants.</p

DEVELOPMENT OF PIEZOELECTRIC SENSORS AND METHODOLOGY FOR NONINVASIVE SIMULTANEOUS DETECTION OF MULTIPLE VITAL SIGNS

The activity of piezoelectric material linked the applied electric field with the strain generated that can be translated into geometrical variations. Flexible steel substrate exhibits fascinating mechanical properties which enable their integration into the emerging field of flexible microelectronics. This work presents an extended technique based on capacitance-voltage dependency to extract the geometrical variations in thin-film piezoelectric materials deposited on a flexible steel. A 50 μm flexible steel sheet has been sandwiched by two PZT film layers, each of 2.4 μm in thickness deposited by sputtering. An aluminum layer of 370 nm has been deposited above each PZT layer to form the electrical contact. The steel sheet represents the common electrode for both PZT structures. Gamry references 3000 analyzers were used to collect the capacitance-voltage measurements then estimating the piezoelectric charge constant. Experimental work has been validated by implementing the same method on a bulk piezoelectric film. Results have shown that the measured capacitance varies by 1% due to dielectric constant voltage dependency. On the other hand, 99% of capacitance variations depend on the change in physical dimensions of the sample via the piezoelectric effect. Further to that, this thesis explores the utilization of piezoelectric-based sensors to collect a corresponding representative signal from the chest surface. The subject typically needs to hold his or her breath to eliminate the respiration effect. This work further contributes to the extraction of the corresponding representative vital signs directly from the measured respiration signal. The contraction and expansion of the heart muscles, as well as the respiration activities, will induce a mechanical vibration across the chest wall. This vibration can be converted into an electrical output voltage via piezoelectric sensors. During breathing, the measured voltage signal is composed of the cardiac cycle activities modulated along with the respiratory cycle activity. The proposed technique employs the principles of piezoelectric and signal-processing methods to extract the corresponding signal of cardiac cycle activities from a breathing signal measured in real-time. All the results were validated step by step by a conventional apparatus, with good agreement observed

Impact of a Modified Early Warning Score Tool on Nurses’ Ability to Recognize and Respond to Clinical Deterioration

Timely recognition of signs of impending clinical deterioration in acute care hospitalized patients can prevent an unexpected illness from becoming a fatal event. Failure to recognize the precursors of impending doom can have many factors, but the most influential of these is the role of the bedside nurse in detecting the subtle signs of decline. The Modified Early Warning Score (MEWS) has been used successfully to detect clinical deterioration in hospitalized patients, while simulation has been used successfully to provide an environment to test reaction to acute patient decline without harm to actual patients. A translational research project implemented the MEWS tool through an educational intervention that included simulated patient experiences. The aims of this project were to 1) increase awareness of bedside nurses to acute patient deterioration in the rural hospital setting and 2) increase action of bedside nurses to acute patient deterioration in the rural hospital setting. Results indicate that use of the MEWS increases nurses’ use of other deterioration screening tools as well as their knowledge and confidence in responding to a deterioration event. The usefulness of simulation as a method to provide education in post-licensure nurses is also discussed. Finally, the MEWS tool was shown to accurately predict patient deterioration of hospitalized clients if completed consistently. Future research should focus on how to increase usage of deterioration tools to detect acute clinical decline earlier in the deterioration process

Rapid Response Team Utilization of Modified Early Warning Scores to Improve Patient Outcomes

This retrospective, descriptive study was designed to (a) determine if the Modified Early Warning Score risk assessment tool identified moderate to high risk patients prior to the activation of the Rapid Response Team (b) determine how much time occurred from the onset of clinical deterioration until activation of the Rapid Response Team. A Modified Early Warning Score (MEWS) was applied to the documented vital signs in the medical records of a convenience sample of 108 adult patients between the ages of 19 and 99 years of age who had experienced an activation of the Rapid Response Team (RRT). A risk assessment score was given for the time of the RRT activation as well as every previously documented instance of vital signs prior to the RRT call until the MEWS score reached a low risk score of 0 to 1. Of the 108 subjects, 36 subjects had a low risk (score 0 to 1) MEWS at the time of the RRT activation; 72 subjects had a moderate (score of 2 to 3) or high (score 4 or greater) risk MEWS score at the time of the RRT activation. Ten (10.14) hours was the average amount of time earlier deterioration could have been detected if a MEWS system had been in place. The data from this study indicate a need for more frequent observation and documentation of vital signs by nursing staff as the overall average length of time between vital signs collected (MEWS applied) was 291.60 minutes (4.86 hours) when clinical deterioration was evident. These data show that there is a delay in activation of the Rapid Response Team and that implementation of the MEWS system would increase RRT awareness of patients with critically abnormal vital signs so that they can be assessed and clinical deterioration treated to prevent a catastrophic event from occurring