Feasibility of Using a Smartwatch to Intensively Monitor Patients With Chronic Obstructive Pulmonary Disease: Prospective Cohort Study

The Role of Smartwatch Technology in the Provision of Care for Type 1 or 2 Diabetes Mellitus or Gestational Diabetes: Systematic Review

Background

The use of smart technology in the management of all forms of diabetes mellitus has grown significantly in the past 10 years. Technologies such as the smartwatch have been proposed as a method of assisting in the monitoring of blood glucose levels as well as other alert prompts such as medication adherence and daily physical activity targets. These important outcomes reach across all forms of diabetes and have the potential to increase compliance of self-monitoring with the aim of improving long-term outcomes such as hemoglobin A1c (HbA1c).

Objective

This systematic review aims to explore the literature for evidence of smartwatch technology in type 1, 2, and gestational diabetes.

Methods

A systematic review was undertaken by searching Ovid MEDLINE and CINAHL databases. A second search using all identified keywords and index terms was performed on Ovid MEDLINE (January 1966 to August 2023), Embase (January 1980 to August 2023), Cochrane Central Register of Controlled Trials (CENTRAL, the Cochrane Library, latest issue), CINAHL (from 1982), IEEE Xplore, ACM Digital Libraries, and Web of Science databases. Type 1, type 2, and gestational diabetes were eligible for inclusion. Quantitative studies such as prospective cohort or randomized clinical trials that explored the feasibility, usability, or effect of smartwatch technology in people with diabetes were eligible. Outcomes of interest were changes in blood glucose or HbA1c, physical activity levels, medication adherence, and feasibility or usability scores.

Results

Of the 8558 titles and abstracts screened, 5 studies were included for qualitative synthesis in this review. A total of 322 participants with either type 1 or type 2 diabetes mellitus were included in the review. A total of 4 studies focused on the feasibility and usability of smartwatch technology in diabetes management. One study conducted a proof-of-concept randomized clinical trial including smartwatch technology for exercise time prescriptions for participants with type 2 diabetes mellitus. Adherence of participants to smartwatch technology varied between included studies, with one reporting input submissions of 58% and another reporting that participants logged 50% more entries than they were required to. One study reported significantly improved glycemic control with integrated smartwatch technology, with increased exercise prescriptions; however, this study was not powered and required a longer observational period.

Conclusions

This systematic review has highlighted the lack of robust randomized clinical trials that explore the efficacy of smartwatch technology in the management of patients with type 1, type 2, and gestational diabetes. Further research is required to establish the role of integrated smartwatch technology in important outcomes such as glycemic control, exercise participation, drug adherence, and diet monitoring in people with all forms of diabetes mellitus.

The experiences of people with chronic obstructive pulmonary disease (COPD) using activity monitors in everyday life: an interpretative phenomenological study

PURPOSE

Understanding the experiences of people with Chronic Obstructive Pulmonary Disease (COPD) using activity monitors in daily life could support the utilisation of technology within healthcare to increase physical activity and support self-management. This qualitative study aimed to explore the experiences of people with COPD using activity monitors at home in everyday life.

METHODS

Semi-structured face-to-face or telephone interviews were conducted with seven people with COPD between August 2018 and June 2020. Participants had all used an activity monitor within the last year (Fitbit, Garmin, or Apple Watch). Interviews were analysed in-depth using Interpretative Phenomenological Analysis (IPA).

RESULTS

Four themes, developed using IPA, highlight participants' engagement with activity monitors and integrating them into their lives: (1) Motivational features to monitor activity, (2) Importance of setting achievable goals, (3) Developing knowledge and awareness, and (4) Integration into everyday life for self-management.

CONCLUSION

Activity monitors were perceived to be beneficial and useful to people with COPD, not just for monitoring their activity, but also helping to self-manage their condition. Activity monitors may be a useful tool within rehabilitation and healthcare services for COPD.

Feasibility of snapshot testing using wearable sensors to detect cardiorespiratory illness (COVID infection in India)

The COVID-19 pandemic has challenged the current paradigm of clinical and community-based disease detection. We present a multimodal wearable sensor system paired with a two-minute, movement-based activity sequence that successfully captures a snapshot of physiological data (including cardiac, respiratory, temperature, and percent oxygen saturation). We conducted a large, multi-site trial of this technology across India from June 2021 to April 2022 amidst the COVID-19 pandemic (Clinical trial registry name: International Validation of Wearable Sensor to Monitor COVID-19 Like Signs and Symptoms; NCT05334680; initial release: 04/15/2022). An Extreme Gradient Boosting algorithm was trained to discriminate between COVID-19 infected individuals (n = 295) and COVID-19 negative healthy controls (n = 172) and achieved an F1-Score of 0.80 (95% CI = [0.79, 0.81]). SHAP values were mapped to visualize feature importance and directionality, yielding engineered features from core temperature, cough, and lung sounds as highly important. The results demonstrated potential for data-driven wearable sensor technology for remote preliminary screening, highlighting a fundamental pivot from continuous to snapshot monitoring of cardiorespiratory illnesses.

Continuous Monitoring of Heart Rate Variability and Respiration for the Remote Diagnosis of Chronic Obstructive Pulmonary Disease: Prospective Observational Study

BACKGROUND

Conventional daytime monitoring in a single day may be influenced by factors such as motion artifacts and emotions, and continuous monitoring of nighttime heart rate variability (HRV) and respiration to assist in chronic obstructive pulmonary disease (COPD) diagnosis has not been reported yet.

OBJECTIVE

The aim of this study was to explore and compare the effects of continuously monitored HRV, heart rate (HR), and respiration during night sleep on the remote diagnosis of COPD.

METHODS

We recruited patients with different severities of COPD and healthy controls between January 2021 and November 2022. Vital signs such as HRV, HR, and respiration were recorded using noncontact bed sensors from 10 PM to 8 AM of the following day, and the recordings of each patient lasted for at least 30 days. We obtained statistical means of HRV, HR, and respiration over time periods of 7, 14, and 30 days by continuous monitoring. Additionally, the effects that the statistical means of HRV, HR, and respiration had on COPD diagnosis were evaluated at different times of recordings.

RESULTS

In this study, 146 individuals were enrolled: 37 patients with COPD in the case group and 109 participants in the control group. The median number of continuous night-sleep monitoring days per person was 56.5 (IQR 32.0-113.0) days. Using the features regarding the statistical means of HRV, HR, and respiration over 1, 7, 14, and 30 days, binary logistic regression classification of COPD yielded an accuracy, Youden index, and area under the receiver operating characteristic curve of 0.958, 0.904, and 0.989, respectively. The classification performance for COPD diagnosis was directionally proportional to the monitoring duration of vital signs at night. The importance of the features for diagnosis was determined by the statistical means of respiration, HRV, and HR, which followed the order of respiration > HRV > HR. Specifically, the statistical means of the duration of respiration rate faster than 21 times/min (RRF), high frequency band power of 0.15-0.40 Hz (HF), and respiration rate (RR) were identified as the top 3 most significant features for classification, corresponding to cutoff values of 0.1 minute, 1316.3 nU, and 16.3 times/min, respectively.

CONCLUSIONS

Continuous monitoring of nocturnal vital signs has significant potential for the remote diagnosis of COPD. As the duration of night-sleep monitoring increased from 1 to 30 days, the statistical means of HRV, HR, and respiration showed a better reflection of an individual's health condition compared to monitoring the vital signs in a single day or night, and better was the classification performance for COPD diagnosis. Further, the statistical means of RRF, HF, and RR are crucial features for diagnosing COPD, demonstrating the importance of monitoring HRV and respiration during night sleep.

COVID-19 surveillance based on consumer wearable devices

Background

Consumer wearable devices such as wristbands and smartwatches have potential application value in communicable disease surveillance.

Objective

We investigated the ability of wearable devices to monitor COVID-19 patients of varying severity.

Methods

COVID-19 patients with mobile phones supporting wearable device applications were selected from Dalian Sixth People Hospital. Physiological parameters from the wearable devices and electronic questionnaires were collected from the device wearing until 14 days post-discharge. Clinical information during hospitalization was also recorded. Based on imaging data, the patients were categorized into the milder group without pneumonia and the more severe group with pneumonia. We plotted the curves of the physiological parameters of the two groups to compare the differences and changes.

Results

Ninety-eight patients were included in the analysis. The mean age was 39.6 ± 10.5 years, including 45 males (45.9%). There were 24 asymptomatic patients, 10 mild patients, 60 moderate patients, and 4 severe patients. Compared with the milder group, the more severe group had higher heart rate-related parameters, while the heart rate variability (HRV) was the opposite. In the more severe group, the heart rate-related parameters showed a downward trend from 0 to 7 days after the fever resolution. Among them, the resting heart rate and sleep heart rate decreased on the 25th day after the onset and were close to the milder group 1 week after discharge.

Conclusions

Consumer wearable devices have the potential to monitor respiratory infections. Heart rate-related parameters obtained from these devices can be sensitive indicators of COVID-19 severity and correlate with disease evolution.

Trial registration

ClinicalTrials.gov NCT04459637.

Acceptance of the Apple Watch Series 6 for Telemonitoring of Older Adults With Chronic Obstructive Pulmonary Disease: Qualitative Descriptive Study Part 1

BACKGROUND

The Apple Watch is not a medical device per se; it is a smart wearable device that is increasingly being used for health monitoring. Evidence exists that the Apple Watch Series 6 can reliably measure blood oxygen saturation (SpO2) in patients with chronic obstructive pulmonary disease under controlled circumstances.

OBJECTIVE

This study aimed to better understand older adults' acceptance of the Watch as a part of telemonitoring, even with these advancements.

METHODS

This study conducted content analysis on data collected from 10 older adults with chronic obstructive pulmonary disease who consented to wear the Watch.

RESULTS

Using the Extended Unified Theory of Acceptance and Use of Technology model, results showed that participants experienced potential health benefits; however, the inability of the Watch to reliably measure SpO2 when in respiratory distress was concerning. Participants' level of tech savviness varied, which caused some fear and frustration at the start, yet all felt supported by family and would have explored more features if they owned the Watch. All agreed that the Watch is mainly a medical tool and not a gadget.

CONCLUSIONS

To conclude, although the Watch may enhance their physical health and well-being, results indicated that participants are more likely to accept the Watch if it ultimately proves to be useful when experiencing respiratory distress.

Remote patient monitoring strategies and wearable technology in chronic obstructive pulmonary disease

Chronic obstructive pulmonary disease (COPD) is highly prevalent and is associated with a heavy burden on patients and health systems alike. Exacerbations of COPD (ECOPDs) are a leading cause of acute hospitalization among all adult chronic diseases. There is currently a paradigm shift in the way that ECOPDs are conceptualized. For the first time, objective physiological parameters are being used to define/classify what an ECOPD is (including heart rate, respiratory rate, and oxygen saturation criteria) and therefore a mechanism to monitor and measure their changes, particularly in an outpatient ambulatory setting, are now of great value. In addition to pre-existing challenges on traditional 'in-person' health models such as geography and seasonal (ex. winter) impacts on the ability to deliver in-person visit-based care, the COVID-19 pandemic imposed additional stressors including lockdowns, social distancing, and the closure of pulmonary function labs. These health system stressors, combined with the new conceptualization of ECOPDs, rapid advances in sophistication of hardware and software, and a general openness by stakeholders to embrace this technology, have all influenced the propulsion of remote patient monitoring (RPM) and wearable technology in the modern care of COPD. The present article reviews the use of RPM and wearable technology in COPD. Context on the influences, factors and forces which have helped shape this health system innovation is provided. A focused summary of the literature of RPM in COPD is presented. Finally, the practical and ethical principles which must guide the transition of RPM in COPD into real-world clinical use are reviewed.

A Scoping Review of the Use of Machine Learning in Health Economics and Outcomes Research: Part 1-Data From Wearable Devices

OBJECTIVES

With the emerging use of machine learning (ML) techniques, there has been particular interest in using wearable data for health economics and outcomes research (HEOR). We aimed to understand the emerging patterns of how ML has been applied to wearable data in HEOR.

METHODS

We identified studies published in PubMed between January 2016 and March 2021. Studies that included at least 1 HEOR-related Medical Subject Headings term, applied an ML, and used wearable data were eligible for inclusion. Two reviewers abstracted information including ML application types and data on which ML was applied and analyzed them using descriptive analyses.

RESULTS

A total of 148 studies were identified from PubMed, among which 32 studies met the inclusion criteria. There has been an increase over time in the number of ML studies using wearable data. ML has been more frequently used for monitoring events in real time (78%) than to predict future events (22%). There has been a wide range of outcomes examined, ranging from general physical or mental health (24%) to more disease-specific outcomes (eg, disease incidence [19%] and progression [13%]) and treatment-related outcomes (eg, treatment adherence [9%] and outcomes [9%]). Data for ML models were more often derived from wearable devices with specific medical purposes (60%) than those without (40%).

CONCLUSION

There has been a wide range of applications of ML to wearable data. Both medical and nonmedical wearable devices have been used as a data source, showing the potential for providing rich data for ML studies in HEOR.

The efficacy of a novel smart watch on medicine adherence and symptom control of allergic rhinitis patients: Pilot study

Background

Allergic rhinitis (AR) is a common allergic airway disorder that is often poorly managed. There is an urgent need to enhance medication adherence in order to improve treatment outcomes in patients with AR. The efficacy of wearable smart watches in improving medication adherence is currently unclear.

Objectives

This study aimed to evaluate the efficacy of a novel smart watch in improving medication adherence and symptom control in patients with AR. The reliability of self-reported medication use was also investigated.

Methods

This randomized, open-label, parallel controlled, pilot study enrolled adult patients with AR caused by cypress pollen. Patients were randomized in a 1:2 ratio to an intervention group and control group. Smart watches were only distributed to patients in the intervention group. During the cypress pollen season, all patients were required to take oral antihistamines daily and use nasal corticosteroids and antihistamine eye drops as needed. Daily AR symptom scores and medication usage were recorded in both groups. The smart watch was able to identify medication-taking behaviors of patients via artificial intelligence (AI) and relay this information to physicians, who sent short message service reminders to patients who forgot to take oral antihistamines for more than 2 days.

Results

During the pollen season, the adherence rate to oral antihistamines in the intervention group (n = 17) was significantly higher than that in the control group (n = 38) (63.3% ± 28.5% versus 43.2% ± 30.2%, P = 0.02). The daily symptom score of the intervention group was lower than that of the control group (2.4 ± 1.1 versus 3.9 ± 1.0, P < 0.001). There was no significant difference in the on-demand medication score between the 2 groups (1.3 ± 0.4 versus 1.5 ± 0.5, P = 0.13). The consistency rate between self-reported nasal corticosteroid usage and the gold standard (ie, human observation of medication usage in the videos recorded by the smart watch) was 20.0% (0%, 53.7%), and the consistency rate between self-reported antihistamine eye drop usage and the gold standard was 24.3% (2.1%, 67.1%).

Conclusions

This pilot study showed that the application of smart watches in patients with AR was associated with improved medication adherence and symptom control. Furthermore, the reliability of self-reported medication usage was limited.

Feasibility of Monitoring Patients Who Have Cancer With a Smart T-shirt: Protocol for the OncoSmartShirt Study

Background

Studies have shown that there may be dissimilar perceptions on symptoms or side effects between patients with cancer and health care professionals. This may lead to symptomatic patients notifying the clinic irregularly or not telling the clinic at all. Wearables could help identify symptoms earlier. Patients with low socioeconomic status and less self-awareness of their health may benefit from this. A new design of wearables is a smart t-shirt that, with embedded sensors, provides measurement flows such as electrocardiogram, thoracic and abdominal respiration, and temperature.

Objective

This study evaluates the feasibility of using a smart t-shirt for home monitoring of biometric sensor data in adolescent and young adult and elderly patients during cancer treatment.

Methods

The OncoSmartShirt study is an explorative study investigating the feasibility of using the Chronolife smart t-shirt during cancer treatment. This smart t-shirt is designed with multiple fully embedded sensors and electrodes that engender 6 different measurement flows continuously. A total of 20 Danish patients with cancer ≥18 years old in antineoplastic treatment at Department of Oncology Rigshospitalet Denmark will be recruited from all cancer wards, whether patients are in curative or palliative care. Of these 20 patients, 10 (50%) will be <39 years old, defined as adolescent and young adult, and 10 (50%) will be patients >65 years old, defined as elderly. Consenting patients will be asked to wear a smart t-shirt daily for 2 weeks during their treatment course.

Results

The primary outcome is to determine if it is feasible to wear a smart t-shirt throughout the day (preferably 8 hours per day) for 2 weeks. Inclusion of patients started in March 2022.

Conclusions

The study will assess the feasibility of using the Chronolife smart t-shirt for home monitoring of vital parameters in patients with cancer during their treatment and bring new insights into how wearables and biometric data can be used as part of symptom or side-effect recognition in patients with cancer during treatment, with the aim to increase patients’ quality of life.

Trial Registration

ClinicalTrials.gov NCT05235594; https://beta.clinicaltrials.gov/study/NCT05235594

International Registered Report Identifier (IRRID)

PRR1-10.2196/37626

What Are the Experiences of People with COPD Using Activity Monitors?: A Qualitative Scoping Review

Physical activity monitoring technology (e.g. smartphone apps or wearables) can objectively record physical activity levels, potentially support interventions to increase activity levels, and support the self-management of Chronic Obstructive Pulmonary Disease (COPD). Insight into patients' experiences of monitoring physical activity is needed to inform future healthcare practice and policy utilizing this technology to support long-term positive health behavior change. This scoping review aimed to explore the experiences of using technology for monitoring physical activity among people with COPD. The Joanna Briggs Institute scoping review methodological framework was used. Relevant scientific databases (CINAHL Complete, MEDLINE, PsycINFO, SPORTDiscus, Cochrane Library and Scopus) were searched from 1st January 2016 to 16th March 2021. Thematic synthesis was used to analyze the data. Twelve studies exploring the experiences of people with COPD using technology for monitoring physical activity were included in the synthesis. Seven themes were developed and summarize experiences: 1) Monitoring and keeping track of their activity and health, 2) Supporting motivation to be active, 3) Acceptability of the device, 4) Experiencing technical issues with the device, 5) Setting appropriate and achievable goals for their health condition, 6) Integrating the device into their life and daily routine, and 7) Perceived physical and psychological benefits of using the device. Further high-quality research is needed to understand the experiences of people with COPD using technology to monitor physical activity in everyday life and better self-manage their health condition. Supporting people with COPD to monitor their physical activity could enable them to better self-manage their health condition.

Using smartwatches to observe changes in activity during recovery from critical illness following COVID-19: a 1 year multi-centre observational study. (Preprint)

Background

As a sequela of the COVID-19 pandemic, a large cohort of critical illness survivors have had to recover in the context of ongoing societal restrictions.

Objective

We aimed to use smartwatches (Fitbit Charge 3; Fitbit LLC) to assess changes in the step counts and heart rates of critical care survivors following hospital admission with COVID-19, use these devices within a remote multidisciplinary team (MDT) setting to support patient recovery, and report on our experiences with this.

Methods

We conducted a prospective, multicenter observational trial in 8 UK critical care units. A total of 50 participants with moderate or severe lung injury resulting from confirmed COVID-19 were recruited at discharge from critical care and given a smartwatch (Fitbit Charge 3) between April and June 2020. The data collected included step counts and daily resting heart rates. A subgroup of the overall cohort at one site—the MDT site (n=19)—had their smartwatch data used to inform a regular MDT meeting. A patient feedback questionnaire and direct feedback from the MDT were used to report our experience. Participants who did not upload smartwatch data were excluded from analysis.

Results

Of the 50 participants recruited, 35 (70%) used and uploaded data from their smartwatch during the 1-year period. At the MDT site, 74% (14/19) of smartwatch users uploaded smartwatch data, whereas 68% (21/31) of smartwatch users at the control sites uploaded smartwatch data. For the overall cohort, we recorded an increase in mean step count from 4359 (SD 3488) steps per day in the first month following discharge to 7914 (SD 4146) steps per day at 1 year (P=.003). The mean resting heart rate decreased from 79 (SD 7) beats per minute in the first month to 69 (SD 4) beats per minute at 1 year following discharge (P<.001). The MDT subgroup’s mean step count increased more than that of the control group (176% increase vs 42% increase, respectively; +5474 steps vs +2181 steps, respectively; P=.04) over 1 year. Further, 71% (10/14) of smartwatch users at the MDT site and 48% (10/21) of those at the control sites strongly agreed that their Fitbit motivated them to recover, and 86% (12/14) and 48% (10/21), respectively, strongly agreed that they aimed to increase their activity levels over time.

Conclusions

This is the first study to use smartwatch data to report on the 1-year recovery of patients who survived a COVID-19 critical illness. This is also the first study to report on smartwatch use within a post–critical care MDT. Future work could explore the role of smartwatches as part of a randomized controlled trial to assess clinical and economic effectiveness.

International Registered Report Identifier (IRRID)

RR2-10.12968/ijtr.2020.0102

Device Invariant Deep Neural Networks for Pulmonary Audio Event Detection Across Mobile and Wearable Devices

Mobile and wearable devices are being increasingly used for developing audio based machine learning models to infer pulmonary health, exacerbation and activity. A major challenge to widespread usage and deployment of such pulmonary health monitoring audio models is to maintain accuracy and robustness across a variety of commodity devices, due to the effect of device heterogeneity. Because of this phenomenon, pulmonary audio models developed with data from one type of device perform poorly when deployed on another type of device. In this work, we propose a framework incorporating feature normalization across individual frequency bins and combining task specific deep neural networks for model invariance across devices for pulmonary event detection. Our empirical and extensive experiments with data from 131 real pulmonary patients and healthy controls show that our framework can recover up to 163.6% of the accuracy lost due to device heterogeneity for four different pulmonary classification tasks across two broad classification scenarios with two common mobile and wearable devices: smartphone and smartwatch.Clinical relevance- The methods presented in this paper will enable efficient and easy portability of clinician recommended pulmonary audio event detection and analytic models across various mobile and wearable devices used by a patient.

Assessing the usability of wearable devices to measure gait and physical activity in chronic conditions: a systematic review

BACKGROUND

The World Health Organisation's global strategy for digital health emphasises the importance of patient involvement. Understanding the usability and acceptability of wearable devices is a core component of this. However, usability assessments to date have focused predominantly on healthy adults. There is a need to understand the patient perspective of wearable devices in participants with chronic health conditions.

METHODS

A systematic review was conducted to identify any study design that included a usability assessment of wearable devices to measure mobility, through gait and physical activity, within five cohorts with chronic conditions (Parkinson's disease [PD], multiple sclerosis [MS], congestive heart failure, [CHF], chronic obstructive pulmonary disorder [COPD], and proximal femoral fracture [PFF]).

RESULTS

Thirty-seven studies were identified. Substantial heterogeneity in the quality of reporting, the methods used to assess usability, the devices used, and the aims of the studies precluded any meaningful comparisons. Questionnaires were used in the majority of studies (70.3%; n = 26) with a reliance on intervention specific measures (n = 16; 61.5%). For those who used interviews (n = 17; 45.9%), no topic guides were provided, while methods of analysis were not reported in over a third of studies (n = 6; 35.3%).

CONCLUSION

Usability of wearable devices is a poorly measured and reported variable in chronic health conditions. Although the heterogeneity in how these devices are implemented implies acceptance, the patient voice should not be assumed. In the absence of being able to make specific usability conclusions, the results of this review instead recommends that future research needs to: (1) Conduct usability assessments as standard, irrespective of the cohort under investigation or the type of study undertaken. (2) Adhere to basic reporting standards (e.g. COREQ) including the basic details of the study. Full copies of any questionnaires and interview guides should be supplied through supplemental files. (3) Utilise mixed methods research to gather a more comprehensive understanding of usability than either qualitative or quantitative research alone will provide. (4) Use previously validated questionnaires alongside any intervention specific measures.

The Healthcare Cost Burden in Adults with High Risk for Cardiovascular Disease

OBJECTIVE

We calculated the short- and long-term care resource use and costs in adults with high-risk conditions for cardiovascular disease (HRCVD) as defined by the Canadian Cardiovascular Society dyslipidemia guidelines.

METHODS

We linked Alberta health databases to identify patients aged ≥ 18 years with HRCVD between fiscal year (FY) 2012 and FY2016. The first HRCVD event was the index event. Patients were categorized into (1) primary prevention patients and (2) secondary prevention patients at the index event and were followed until death, they moved out of the province, or they were censored at March 2018. We calculated the resource use and costs for each of the 5 years after the index event.

RESULTS

The study included 459,739 HRCVD patients (13,947 [3%] were secondary prevention patients). The secondary prevention patients were older (median age 61 years vs. 55 years; p < 0.001), and there were fewer females in this group (30.4% vs. 51.3%; p < 0.001). The total healthcare costs in the first year decreased over time (FY2012: 1.16 billion Canadian dollars (CA$); FY2016: CA$1.05 billion; p < 0.001). An HRCVD patient incurred CA$12,068, CA$5626, and CA$4655 during the first, second, and fifth year, respectively (p for trend < 0.001). During the first year, healthcare costs per secondary prevention patient (CA$36,641) were triple that for a primary prevention patient (CA$11,299; p < 0.001), primarily due to higher hospitalization costs in secondary prevention patients (CA$26,896 vs. CA$6051; p < 0.001).

CONCLUSIONS

The healthcare costs for HRCVD patients were substantial but decreased over time. The costs were highest in the year following the index event and decreased thereafter. Secondary prevention patients incurred higher costs than the primary prevention patients.

Machine-learning based feature selection for a non-invasive breathing change detection

BACKGROUND

Chronic Obstructive Pulmonary Disease (COPD) is one of the top 10 causes of death worldwide, representing a major public health problem. Researchers have been looking for new technologies and methods for patient monitoring with the intention of an early identification of acute exacerbation events. Many of these works have been focusing in breathing rate variation, while achieving unsatisfactory sensitivity and/or specificity. This study aims to identify breathing features that better describe respiratory pattern changes in a short-term adjustment of the load-capacity-drive balance, using exercising data.

RESULTS

Under any tested circumstances, breathing rate alone leads to poor capability of classifying rest and effort periods. The best performances were achieved when using Fourier coefficients or when combining breathing rate with the signal amplitude and/or ARIMA coefficients.

CONCLUSIONS

Breathing rate alone is a quite poor feature in terms of prediction of breathing change and the addition of any of the other proposed features improves the classification power. Thus, the combination of features may be considered for enhancing exacerbation prediction methods based in the breathing signal.

TRIAL REGISTRATION

ClinicalTrials NCT03753386. Registered 27 November 2018, https://clinicaltrials.gov/show/NCT03753386.

Digitally enhanced recovery from severe COVID-19: a new frontier?

During the first wave of intensive care unit admissions with COVID-19, in response to the constraints of social distancing we introduced a new digitally enabled critical care rehabilitation pathway. Using smartwatch technology, this pathway rapidly enabled our multidisciplinary team to observe the recovery of a COVID-19 cohort across eight NHS acute hospitals across the south of England. This represents one of the geographically largest smartwatch studies of its kind.

Wearable Devices in Health Monitoring from the Environmental towards Multiple Domains: A Survey

The World Health Organization (WHO) recognizes the environmental, behavioral, physiological, and psychological domains that impact adversely human health, well-being, and quality of life (QoL) in general. The environmental domain has significant interaction with the others. With respect to proactive and personalized medicine and the Internet of medical things (IoMT), wearables are most important for continuous health monitoring. In this work, we analyze wearables in healthcare from a perspective of innovation by categorizing them according to the four domains. Furthermore, we consider the mode of wearability, costs, and prolonged monitoring. We identify features and investigate the wearable devices in the terms of sampling rate, resolution, data usage (propagation), and data transmission. We also investigate applications of wearable devices. Web of Science, Scopus, PubMed, IEEE Xplore, and ACM Library delivered wearables that we require to monitor at least one environmental parameter, e.g., a pollutant. According to the number of domains, from which the wearables record data, we identify groups: G1, environmental parameters only; G2, environmental and behavioral parameters; G3, environmental, behavioral, and physiological parameters; and G4 parameters from all domains. In total, we included 53 devices of which 35, 9, 9, and 0 belong to G1, G2, G3, and G4, respectively. Furthermore, 32, 11, 7, and 5 wearables are applied in general health and well-being monitoring, specific diagnostics, disease management, and non-medical. We further propose customized and quantified output for future wearables from both, the perspectives of users, as well as physicians. Our study shows a shift of wearable devices towards disease management and particular applications. It also indicates the significant role of wearables in proactive healthcare, having capability of creating big data and linking to external healthcare systems for real-time monitoring and care delivery at the point of perception.

Perspectives of older adults with chronic disease on the use of wearable technology and video games for physical activity

BACKGROUND

There is increasing interest in technology to deliver physical rehabilitation and allow clinicians to monitor progress. Examples include wearable activity trackers and active video games (AVGs), where physical activity is required to play the game. However, few studies have explored what may influence the effectiveness of these as technology-based physical activity interventions in older adults with chronic diseases.

OBJECTIVE

This study aimed to explore: 1) perceptions about wearable physical activity trackers; 2) perceptions about using technology to share physical activity information with clinicians; 3) barriers and motivators to playing games, including AVGs for rehabilitation.

METHODS

Qualitative study based on semi-structured interviews with older adults (n = 19) with chronic obstructive pulmonary disease (COPD).

RESULTS

Wearable activity trackers were perceived as useful to quantify activity, facilitate goal-setting, visualize long-term improvements and provide reminders. Participants generally wished to share data with their clinicians to gain greater accountability, receive useful feedback and improve the quality of clinical care. Participants were motivated to play games (including AVGs) by seeking fun, social interaction and health benefits. Some felt that AVGs were of no benefit or were too difficult. Competition was both a motivator and a barrier.

CONCLUSIONS

The findings of the present study seek to inform the design of technology to encourage physical activity in older adults with chronic diseases.

Wearable Health Devices in Health Care: Narrative Systematic Review

BACKGROUND

With the rise of mobile medicine, the development of new technologies such as smart sensing, and the popularization of personalized health concepts, the field of smart wearable devices has developed rapidly in recent years. Among them, medical wearable devices have become one of the most promising fields. These intelligent devices not only assist people in pursuing a healthier lifestyle but also provide a constant stream of health care data for disease diagnosis and treatment by actively recording physiological parameters and tracking metabolic status. Therefore, wearable medical devices have the potential to become a mainstay of the future mobile medical market.

OBJECTIVE

Although previous reviews have discussed consumer trends in wearable electronics and the application of wearable technology in recreational and sporting activities, data on broad clinical usefulness are lacking. We aimed to review the current application of wearable devices in health care while highlighting shortcomings for further research. In addition to daily health and safety monitoring, the focus of our work was mainly on the use of wearable devices in clinical practice.

METHODS

We conducted a narrative review of the use of wearable devices in health care settings by searching papers in PubMed, EMBASE, Scopus, and the Cochrane Library published since October 2015. Potentially relevant papers were then compared to determine their relevance and reviewed independently for inclusion.

RESULTS

A total of 82 relevant papers drawn from 960 papers on the subject of wearable devices in health care settings were qualitatively analyzed, and the information was synthesized. Our review shows that the wearable medical devices developed so far have been designed for use on all parts of the human body, including the head, limbs, and torso. These devices can be classified into 4 application areas: (1) health and safety monitoring, (2) chronic disease management, (3) disease diagnosis and treatment, and (4) rehabilitation. However, the wearable medical device industry currently faces several important limitations that prevent further use of wearable technology in medical practice, such as difficulties in achieving user-friendly solutions, security and privacy concerns, the lack of industry standards, and various technical bottlenecks.

CONCLUSIONS

We predict that with the development of science and technology and the popularization of personalized health concepts, wearable devices will play a greater role in the field of health care and become better integrated into people's daily lives. However, more research is needed to explore further applications of wearable devices in the medical field. We hope that this review can provide a useful reference for the development of wearable medical devices.

Hardware Prototype for Wrist-Worn Simultaneous Monitoring of Environmental, Behavioral, and Physiological Parameters

We designed a low-cost wrist-worn prototype for simultaneously measuring environmental, behavioral, and physiological domains of influencing factors in healthcare. Our prototype continuously monitors ambient elements (sound level, toxic gases, ultraviolet radiation, air pressure, temperature, and humidity), personal activity (motion tracking and body positioning using gyroscope, magnetometer, and accelerometer), and vital signs (skin temperature and heart rate). An innovative three-dimensional hardware, based on the multi-physical-layer approach is introduced. Using board-to-board connectors, several physical hardware layers are stacked on top of each other. All of these layers consist of integrated and/or add-on sensors to measure certain domain (environmental, behavioral, or physiological). The prototype includes centralized data processing, transmission, and visualization. Bi-directional communication is based on Bluetooth Low Energy (BLE) and can connect to smartphones as well as smart cars and smart homes for data analytic and adverse-event alerts. This study aims to develop a prototype for simultaneous monitoring of the all three areas for monitoring of workplaces and chronic obstructive pulmonary disease (COPD) patients with a concentration on technical development and validation rather than clinical investigation. We have implemented 6 prototypes which have been tested by 5 volunteers. We have asked the subjects to test the prototype in a daily routine in both indoor (workplaces and laboratories) and outdoor. We have not imposed any specific conditions for the tests. All presented data in this work are from the same prototype. Eleven sensors measure fifteen parameters from three domains. The prototype delivers the resolutions of 0.1 part per million (PPM) for air quality parameters, 1 dB, 1 index, and 1 °C for sound pressure level, UV, and skin temperature, respectively. The battery operates for 12.5 h under the maximum sampling rates of sensors without recharging. The final expense does not exceed 133€. We validated all layers and tested the entire device with a 75 min recording. The results show the appropriate functionalities of the prototype for further development and investigations.

Temporal Trends Of Pharmacologic Therapies For Patients With Chronic Obstructive Pulmonary Disease In Alberta, Canada

Objectives

To describe the trends in pharmacologic treatment for patients newly diagnosed with chronic obstructive pulmonary disease (COPD) in Alberta, Canada.

Methods

We linked Alberta health databases to identify patients aged ≥35 years with incident COPD between April 2010 and March 2017. Incident cases were defined as those who did not have a hospitalization or outpatient visit with COPD in the previous 2 years. Patients were categorized into two groups: 1) incident cases at a hospital and 2) incident cases at an outpatient clinic, and both were followed until death or being censored by 31 March 2018. Utilization of COPD medication for 30 days following incident event and adherence in maintenance therapy over time were reported.

Results

The study included 33,169 patients with incident COPD (hospital: 9,089; outpatient: 24,080). In 18,666 (56.3%) patients starting medication within 30 days of the incident event (2010: 52.7%; 2016: 56.6%; p=0.002), SABA (60.5%) and LABA/ICS (41.6%) were most commonly used. ICS (without LABA) was used in 14.2% and was used as monotherapy in 4.5% of patients. The proportion of patients who initiated any ICS was similar (hospital: 56.7%; outpatient: 55.7%; p=0.194) and decreased in both settings over time (p<0.001). Drug adherence during the first year after the incident event was 54.3%, higher among hospital patients (66.5% vs 48.9%; p<0.001), and improved over time (2010: 53.4%; 2016: 57.4%; p<0.001).

Conclusion

The initiation of and adherence to pharmacologic therapy for patients with COPD is low but improves over time. While SABA and LABA/ICS are most commonly used, ICS utilization decreases over time.

Using wearables and self-management apps in patients with COPD: a qualitative study

Background

Technology such as wearable technology and self-management applications could improve the care of patients with chronic obstructive pulmonary disease (COPD) by real-time continuous monitoring, early detection of COPD and improved self-management. However, patients have not been willing to use technology when it is too difficult to use, interferes with their daily lives or threatens their identity, independence and self-care.

Methods

We conducted a qualitative study to determine what patients with COPD would like to see in a wearable device and a mobile application to help manage their condition. Semi-structured interviews were conducted, recorded and transcribed. Thematic analysis was used to identify themes and concepts.

Results

We interviewed 14 people with COPD with an average age of 69 years. Participants perceived that the technology could improve their ability to manage their condition both in daily life and during exacerbations by connecting how they feel and by knowing their oxygen saturation, heart rate and activity. The technology may help them address feelings of fear and panic associated with exacerbations and may provide reassurance and connectedness. Some people with COPD wanted their healthcare providers to have access to their data, while others were concerned about inundating them with too much information. Of note, people wanted to maintain control of the information; to make connections with the data, but also in order to be alerted when a possible exacerbation occurs.

Conclusion

Patients perceived significant potential for wearables and apps to help manage their condition.

In-depth interviews with COPD patients found that they face significant challenges managing their condition. Patients perceive significant potential for wearables to help with self-management and alerting them to a possible exacerbation.http://bit.ly/2xcyBlB

A qualitative study of chronic obstructive pulmonary disease patient perceptions of the barriers and facilitators to adopting digital health technology

Objective

Non-adherence to self-management plans in chronic obstructive pulmonary disease (COPD) results in poorer outcomes for patients. Digital health technology (DHT) promises to support self-management by enhancing the sense of control patients possess over their disease. COPD digital health studies have yet to show significant evidence of improved outcomes for patients, with many user-adoption issues still present in the literature. To help better address the adoption needs of COPD patients, this paper explores their perceived barriers and facilitators to the adoption of DHT.

Methods

A sample of convenience was chosen and patients (n = 30) were recruited from two Dublin university hospitals. Each patient completed a qualitative semi-structured interview. Thematic analysis of the data was performed using NVivo 12 software.

Results

Barrier sub-themes included lack of perceived usefulness, digital literacy, illness perception, and social context; facilitator sub-themes included existing digital self-efficacy, personalised education, and community-based support.

Conclusion

The findings represent a set of key considerations for researchers and clinicians to inform the design of patient-centred study protocols that aim to account for the needs and preferences of patients in the development of implementation and adoption strategies for DHT in COPD.

Current perspectives of physical activity in cystic fibrosis

Introduction: Regular exercise and physical activity participation are recommended in guideline-based care for individuals with cystic fibrosis (CF) across the spectrum of age and disease severity. However, the best training methods to improve physical function and encourage ongoing exercise and activity participation are not clear, which is an ongoing challenge for clinicians. Areas covered: This perspective provides an overview of current evidence for exercise and physical activity relative to clinical outcomes and health-care utilization in people with CF, and highlights areas of future research need. Expert commentary: What kind, how much, how often, and how best to support people with CF to be physically active is uncertain. Whether new methods of training, the use of technology, or pharmaceutical developments could best deliver increased activity and physiological benefit without increased therapeutic burden is unclear. At present, if people with CF are going to be physically active, seemingly they should aim to perform this activity in the way most likely to confer some health benefit i.e. concerted exercise bouts of at least 10 min in addition to any incidental (habitual) activity performed during the course of daily life.