Impact of an Ambulatory Monitoring System on Deterioration Detection and Clinical Outcomes in Hospitalised Patients. A Feasibility Randomised Controlled Trial Protocol.

BackgroundDespite the exponential growth of wearable technology, previous research indicates a lack of statistically significant evidence to support the hypothesis that implementation of wearable ambulatory vital sign monitoring systems impact early patient deterioration detection and clinical outcomes. This highlights the need for large, rigorous studies to address this gap. The objective of this feasibility trial is to assess the impact of an ambulatory monitoring system (AMS) on deterioration detection and clinical outcomes in hospitalised patients, compared to standard care. As a secondary objective we will assess the feasibility of conducting a full randomised controlled trial (RCT).MethodsBetween 120 and 240 patients will be recruited and randomised equally to either an AMS or standard care group. Wearable devices will include a pulse oximeter (monitoring pulse rate and oxygen saturation), a chest patch (monitoring heart rate, respiratory rate and temperature) and a wireless blood pressure cuff (monitoring systolic and diastolic blood pressure). Both groups will wear the devices during their ward length of stay, however only data and alerts from the AMS group will be visible to clinical staff.DiscussionRecruitment of participants is expected to start in January 2022, with an anticipated completion date of December 2022. This feasibility RCT will test the early impact of our AMS implementation in a non-intensive care ward and provide data to support the design and deployment of a full RCT which will provide much-needed evidence of the impact of AMS on early deterioration detection and clinical outcomes.

Kalman Filter Implementation of Subglottal Impedance-Based Inverse Filtering to Estimate Glottal Airflow during Phonation

Subglottal Impedance-Based Inverse Filtering (IBIF) allows for the continuous, non-invasive estimation of glottal airflow from a surface accelerometer placed over the anterior neck skin below the larynx. It has been shown to be advantageous for the ambulatory monitoring of vocal function, specifically in the use of high-order statistics to understand long-term vocal behavior. However, during long-term ambulatory recordings over several days, conditions may drift from the laboratory environment where the IBIF parameters were initially estimated due to sensor positioning, skin attachment, or temperature, among other factors. Observation uncertainties and model mismatch may result in significant deviations in the glottal airflow estimates; unfortunately, they are very difficult to quantify in ambulatory conditions due to a lack of a reference signal. To address this issue, we propose a Kalman filter implementation of the IBIF filter, which allows for both estimating the model uncertainty and adapting the airflow estimates to correct for signal deviations. One-way analysis of variance (ANOVA) results from laboratory experiments using the Rainbow Passage indicate an improvement using the modified Kalman filter on amplitude-based measures for phonotraumatic vocal hyperfunction (PVH) subjects compared to the standard IBIF; the latter showing a statistically difference (p-value =0.02, F=4.1) with respect to a reference glottal volume velocity signal estimated from a single notch filter used here as ground-truth in this work. In contrast, maximum flow declination rates from subjects with vocal phonotrauma exhibit a small but statistically difference between the ground-truth signal and the modified Kalman filter when using one-way ANOVA (p-value =0.04, F=3.3). Other measures did not have significant differences with either the modified Kalman filter or IBIF compared to ground-truth, with the exception of H1-H2, whose performance deteriorates for both methods. Overall, both methods (modified Kalman filter and IBIF) show similar glottal airflow measures, with the advantage of the modified Kalman filter to improve amplitude estimation. Moreover, Kalman filter deviations from the IBIF output airflow might suggest a better representation of some fine details in the ground-truth glottal airflow signal. Other applications may take more advantage from the adaptation offered by the modified Kalman filter implementation.

Deleterious Effect of Participant Positioning on the Acceptability and Acceptance of a Wellness Management System under Development

Managing everyday wellness using sensors requires user buy-in and acceptance. The Unified Theory of Acceptance and Use of Technology (UTAUT) was used to measure at D-0 the acceptability (a priori), and at D-21 the acceptance of an ambulatory monitoring system under development, the SHERPAM system. Interviews with the participants revealed that they no longer viewed the system in the same way at the different stages of the study. The results of the qualitative analysis suggest that the time of the research led the participants to stop seeing themselves as potential future users and to take on the role of critical testers of the technology (which corresponds more to a user test). This role change led participants to question the usefulness of the technology, which affected their intention to use the technology in the future (5.30 vs. 4.24; t = 2.58 *). This research identified the reasons why it was crucial to have a fully functional device in the second phase (acceptance study). The results of this study suggest that it is inappropriate to undertake an acceptability study when the technology is under development. While the SHERPAM platform has been the subject of several user tests, none have been carried out in a situation of use. Thus, this study seems to suggest that the dysfunctions observed are more related to the absence of a development phase in the daily activity of the users. Thus, to ensure a good appropriation of the technology and to predict its use, the technology must not only be in perfect working order, but must also have been developed according to the daily activities of the individuals.

Kalman Filter Implementation of Subglottal Impedance-Based Inverse Filtering to Estimate Glottal Airflow during Phonation

Subglottal Impedance-Based Inverse Filtering (IBIF) allows for the continuous, non-invasive estimation of glottal airflow from a surface accelerometer placed over the anterior neck skin below the larynx, which has been shown to be advantageous for the ambulatory monitoring of vocal function. However, during long-term ambulatory recordings over several days, conditions may drift from the laboratory environment where the IBIF parameters were initially estimated due to sensor positioning, skin attachment, and temperature, among other factors. Observation uncertainties and model mismatch may result in significant deviations in the glottal airflow estimates, but are very difficult to quantify in ambulatory conditions due to a lack of a reference signal. To address this issue, we propose a Kalman filter implementation of the IBIF filter, which allows for both estimating the model uncertainty and adapting the airflow estimates to correct for signal deviations. One-way ANOVA results from laboratory experiments using the Rainbow Passage indicate a an improvement on amplitude-based measures for PVH subjects compared to IBIF which shows a statistically difference with respect to the reference oral airflow (p=0.02,F=4.1). MFDR from PVH subjects is slightly different to the oral airflow when compared to IBIF (p=0.04, F=3.3). Other measures did not have significant differences with either Kalman or IBIF, with the exception of H1H2, whose performance deteriorates for both methods. Overall, both methods show similar flottal airflow measures, with the advantage of Kalman by improving amplitude estimation. Moreover, Kalman filter deviations from the IBIF output airflow might suggest a better representation of some fine details in the ground-truth glottal airflow signal. Other applications may take more advantage from the adaptation offered by the Kalman filter implementation.

P112 Under-mattress sleep monitoring to predict readmission risk after COPD exacerbation

Background Recurrent hospitalisation for COPD exacerbations is a major contributor to disease burden and healthcare costs. This study aims to establish if post-discharge sleep or vital sign parameters are predictive of hospital readmissions after COPD exacerbations. Methods Patients admitted with a COPD exacerbation were recruited from November 2019 until May 2021. Sleep parameters were assessed for at least one night in hospital and 10 nights post-discharge using an under-mattress device (EarlySense). Analysis on data from the first 26 participants were conducted using independent sample Mann-Whitney U tests comparing device-estimated sleep parameters between participants admitted versus not readmitted at one- and three-months post-discharge. Progress to date Thirty-four participants have consented. In the 26 participants completing the study to date, all-cause hospital readmission rates at one- and three-months were 26% and 65% respectively. Participants readmitted versus not readmitted at one-month had lower percentage of time in light sleep (43 ± 12% vs 58 ± 12%, p=0.029) and lower estimated AHI (5.6 ± 1.9 vs 17 ± 11 /hr, p=0.042). There were no differences at three-months. Intended outcome and impact Data from the full cohort will be used to assess heart rate and respiratory rate across each night and stage of sleep which could reveal clinically useful methods in the emerging field of ambulatory sleep monitoring. The feasibility and challenges of using ambulatory monitoring devices in patients with chronic respiratory disease will be reported. This study will guide future work that could potentially improve ambulatory monitoring through user-friendly and clinically feasible devices.

Physiological deterioration in the Emergency Department: The SNAP40-ED study

Continuous novel ambulatory monitoring may detect deterioration in Emergency Department (ED) patients more rapidly, prompting treatment and preventing adverse events. Single-centre, open-label, prospective, observational cohort study recruiting high/medium acuity (Manchester triage category 2 and 3) participants, aged over 16 years, presenting to ED. Participants were fitted with a novel wearable monitoring device alongside standard clinical care (wired monitoring and/or manual clinical staff vital sign recording) and observed for up to 4 hours in the ED. Primary outcome was time to detection of deterioration. Two-hundred and fifty (250) patients were enrolled. In 82 patients (32.8%) with standard monitoring (wired monitoring and/or manual clinical staff vital sign recording), deterioration in at least one vital sign was noted during their four-hour ED stay. Overall, the novel device detected deterioration a median of 34 minutes earlier than wired monitoring (Q1, Q3 67,194; n=73, mean difference 39.48, p<0.0001). The novel device detected deterioration a median of 24 minutes (Q1, Q3 2,43; n=42) earlier than wired monitoring and 65 minutes (Q1, Q3 28,114; n=31) earlier than manual vital signs. Deterioration in physiology was common in ED patients. ED staff spent a significant amount of time performing observations and responding to alarms, with many not escalated. The novel device detected deterioration significantly earlier than standard care.

Using smartphone-based accelerometers to gauge postoperative outcomes in patients with NPH: Implications for ambulatory monitoring

Background: The surgical treatment of normal pressure hydrocephalus (NPH) with shunting remains controversial due to the difficulty in distinguishing such pathology from other neurological conditions that can present similarly. Thus, patients with suspected NPH should be carefully selected for surgical intervention. Historically, clinical improvement has been measured by the use of functional grades, alleviation of symptoms, and/or patient/family-member reported surveys. Such outcome analysis can be subjective, and there is difficulty in quantifying cognition. Thus, a push for a more quantifiable and objective investigation is warranted, especially for patients with idiopathic NPH (INPH), for which the final diagnosis is confirmed with postoperative clinical improvement. We aimed to use Apple Health (Apple Inc., Cupertino, CA) data to approximate physical activity levels before and after shunt placement for NPH as an objective outcome measurement. The patients were contacted and verbally consented to export Apple Health activity data. The patient’s physical activity data were then analyzed. A chart review from the patient’s EMR was performed to understand and better correlate recovery. Case Description: Our first patient had short-term improvements in activity levels when compared to his preoperative activity. The patient’s activity level subsequently decreased at 6 months and onward. This decline was simultaneous to new-onset lumbar pain. Our second patient experienced sustained improvements in activity levels for 12 months after his operation. His mobility data were in congruence with his subjectively reported improvement in clinical symptoms. He subsequently experienced a late-decline that began at 48-months. His late deterioration was likely confounded by exogenous factors such as further neurodegenerative diseases coupled with old age. Conclusion: The use of objective activity data offers a number of key benefits in the analysis of shunted patients with NPH/INPH. In this distinctive patient population, detailed functional outcome analysis is imperative because the long-term prognosis can be affected by comorbid factors or life expectancy. The benefits from using smartphone-based accelerometers for objective outcome metrics are abundant and such an application can serve as a clinical aid to better optimize surgical and recovery care.

A Real-Time Wearable System for Monitoring Vital Signs of COVID-19 Patients in a Hospital Setting

The challenges presented by the Coronavirus disease 2019 (COVID-19) pandemic to the National Health Service (NHS) in the United Kingdom (UK) led to a rapid adaptation of infection disease protocols in-hospital. In this paper we report on the optimisation of our wearable ambulatory monitoring system (AMS) to monitor COVID-19 patients on isolation wards. A wearable chest patch (VitalPatch®, VitalConnect, United States of America, USA) and finger-worn pulse oximeter (WristOx2® 3150, Nonin, USA) were used to estimate and transmit continuous Heart Rate (HR), Respiratory Rate (RR), and peripheral blood Oxygen Saturation (SpO2) data from ambulatory patients on these isolation wards to nurse bays remote from these patients, with a view to minimising the risk of infection for nursing staff. Our virtual High-Dependency Unit (vHDU) system used a secure web-based architecture and protocols (HTTPS and encrypted WebSockets) to transmit the vital-sign data in real time from wireless Android tablet devices, operating as patient data collection devices by the bedside in the isolation rooms, into the clinician dashboard interface available remotely via any modern web-browser. Fault-tolerant software strategies were used to reconnect the wearables automatically, avoiding the need for nurses to enter the isolation ward to re-set the patient monitoring equipment. The remote dashboard also displayed the vital-sign observations recorded by the nurses, using a separate electronic observation system, allowing them to review both sources of vital-sign data in one integrated chart. System usage was found to follow the trend of the number of local COVID-19 infections during the first wave of the pandemic in the UK (March to June 2020), with almost half of the patients on the isolation ward monitored with wearables during the peak of hospital admissions in the local area. Patients were monitored for a median of 31.5 [8.8, 75.4] hours, representing 88.1 [62.5, 94.5]% of the median time they were registered in the system. This indicates the system was being used in the isolation ward during this period. An updated version of the system has now also been used throughout the second and third waves of the pandemic in the UK.