Measurement and Data Transmission Validity of a Multi-Biosensor System for Real-Time Remote Exercise Monitoring Among Cardiac Patients

Telemonitoring during Exercise Training in Cardiac Telerehabilitation: A Review

Comprehensive cardiac rehabilitation (CR) is promising strategy for various cardiovascular diseases. Despite these benefits and the recommendation, adherence to outpatient CR remains low. Home-based CR with telemedicine (tele-CR) is emerging concept that is a good alternative to conventional center-based CR. With the development of e-health and e-Cardiology, real-time telemonitoring of patients' parameters such as vital signs and supervising by healthcare professionals during exercise training via internet might make it possible for safe and effective tele-CR to be performed. Therefore, the present study reviews the literature to summarize the current situation and methodology of patient telemonitoring in tele-CR.

Exploring the acute cardiovascular effects of Floatation-REST

The central nervous system (CNS) exerts a strong regulatory influence over the cardiovascular system in response to environmental demands. Floatation-REST (Reduced Environmental Stimulation Therapy) is an intervention that minimizes stimulation from the environment, yet little is known about the autonomic consequences of reducing external sensory input to the CNS. We recently found that Floatation-REST induces a strong anxiolytic effect in anxious patients while paradoxically enhancing their interoceptive awareness for cardiorespiratory sensations. To further investigate the physiologic nature of this anxiolytic effect, the present study measured acute cardiovascular changes during Floatation-REST using wireless and waterproof equipment that allowed for concurrent measurement of heart rate, heart rate variability (HRV), breathing rate, and blood pressure. Using a within-subjects crossover design, 37 clinically anxious participants with high levels of anxiety sensitivity and 20 non-anxious comparison participants were randomly assigned to undergo a 90-min session of either Floatation-REST or an exteroceptive comparison condition that entailed watching a relaxing nature film. Measures of state anxiety and serenity were collected before and after each session, while indices of autonomic activity were measured throughout each session. HRV was calculated using both time-series and frequency domain analyses. Linear mixed-effects modeling revealed a significant main effect of condition such that relative to the film condition, Floatation-REST elicited significant decreases (p < 0.001) in diastolic blood pressure, systolic blood pressure, breathing rate, and certain metrics of HRV including the standard deviation of the interbeat interval (SDNN), low-frequency HRV, and very low-frequency HRV. Heart rate showed a non-significant trend (p = 0.073) toward being lower in the float condition, especially toward the beginning of the session. The only metric that showed a significant increase during Floatation-REST was normalized high-frequency HRV (p < 0.001). The observed physiological changes were consistent across both anxious and non-anxious participants, and there were no significant group by condition interactions. Blood pressure was the only cardiac metric significantly associated with float-related reductions in state anxiety and increases in serenity. These findings suggest that Floatation-REST lowers sympathetic arousal and alters the balance of the autonomic nervous system toward a more parasympathetic state.

Clinical trial registration

[https://clinicaltrials.gov/show/NCT03051074], identifier [NCT03051074].

Wearable Cardiorespiratory Sensors for Aerospace Applications

Emerging Air Traffic Management (ATM) and avionics human-machine system concepts require the real-time monitoring of the human operator to support novel task assessment and system adaptation features. To realise these advanced concepts, it is essential to resort to a suite of sensors recording neurophysiological data reliably and accurately. This article presents the experimental verification and performance characterisation of a cardiorespiratory sensor for ATM and avionics applications. In particular, the processed physiological measurements from the designated commercial device are verified against clinical-grade equipment. Compared to other studies which only addressed physical workload, this characterisation was performed also looking at cognitive workload, which poses certain additional challenges to cardiorespiratory monitors. The article also addresses the quantification of uncertainty in the cognitive state estimation process as a function of the uncertainty in the input cardiorespiratory measurements. The results of the sensor verification and of the uncertainty propagation corroborate the basic suitability of the commercial cardiorespiratory sensor for the intended aerospace application but highlight the relatively poor performance in respiratory measurements during a purely mental activity.

Chronic patient remote monitoring through the application of big data and internet of things

Chronic patients could benefit from the technological advances, but the clinical approaches for this kind of patients are still limited. This paper describes a system for chronic patients monitoring both, in home and external environments. For this purpose, we used novel technologies as big data, cloud computing and internet of things (IoT). Additionally, the system has been validated for three use cases: cardiovascular disease (CVD), hypertension (HPN) and chronic obstructive pulmonary disease (COPD), which were selected for their incidence in the population. This system is innovative within e-health, mainly due to the use of a big data architecture based on open-source components, also it provides a scalable and distributed environment for storage and processing of biomedical sensor data. The proposed system enables the incorporation of non-medical data sources in order to improve the self-management of chronic diseases and to develop better strategies for health interventions for chronic and dependents patients.

Can human posture and range of motion be measured automatically by smart mobile applications?

Human posture and Range of Motion (ROM) are important components of a physical assessment and, from the collected data, it is possible to identify postural deviations such as scoliosis or joint and muscle limitations, hence identifying risks of more serious injuries. Posture assessment and ROM measures are also necessary metrics to monitor the effect of treatments used in the motor rehabilitation of patients, as well as to monitor their clinical progress. These evaluation processes are more frequently performed through visual inspection and manual palpation, which are simple and low cost methods. These methods, however, can be optimized with the use of tools such as photogrammetry and goniometry. Mobile solutions have also been developed to help health professionals to capture more objective data and with less risk of bias. Although there are already several systems proposed for assessing human posture and ROM in the literature, they have not been able to automatically identify and mark Anatomical and Segment Points (ASPs). The hypothesis presented here considers the development of a mobile application for automatic identification of ASPs by using machine learning algorithms and computer vision models associated with technologies embedded in smartphones. From ASPs identification, it will be possible to identify changes in postural alignment and ROM. In this context, our view is that an application derived from the hypothesis will serve as an additional tool to assist in the physical assessment process and, consequently, in the diagnosis of disorders related to postural and movement changes.

Is Continuous Heart Rate Monitoring of Livestock a Dream or Is It Realistic? A Review

For all homoeothermic living organisms, heart rate (HR) is a core variable to control the metabolic energy production in the body, which is crucial to realize essential bodily functions. Consequently, HR monitoring is becoming increasingly important in research of farm animals, not only for production efficiency, but also for animal welfare. Real-time HR monitoring for humans has become feasible though there are still shortcomings for continuously accurate measuring. This paper is an effort to estimate whether it is realistic to get a continuous HR sensor for livestock that can be used for long term monitoring. The review provides the reported techniques to monitor HR of living organisms by emphasizing their principles, advantages, and drawbacks. Various properties and capabilities of these techniques are compared to check the potential to transfer the mostly adequate sensor technology of humans to livestock in term of application. Based upon this review, we conclude that the photoplethysmographic (PPG) technique seems feasible for implementation in livestock. Therefore, we present the contributions to overcome challenges to evolve to better solutions. Our study indicates that it is realistic today to develop a PPG sensor able to be integrated into an ear tag for mid-sized and larger farm animals for continuously and accurately monitoring their HRs.

Wearable devices for remote vital signs monitoring in the outpatient setting: an overview of the field

Early detection of physiological deterioration has been shown to improve patient outcomes. Due to recent improvements in technology, comprehensive outpatient vital signs monitoring is now possible. This is the first review to collate information on all wearable devices on the market for outpatient physiological monitoring.

A scoping review was undertaken. The monitors reviewed were limited to those that can function in the outpatient setting with minimal restrictions on the patient’s normal lifestyle, while measuring any or all of the vital signs: heart rate, ECG, oxygen saturation, respiration rate, blood pressure and temperature.

A total of 270 papers were included in the review. Thirty wearable monitors were examined: 6 patches, 3 clothing-based monitors, 4 chest straps, 2 upper arm bands and 15 wristbands. The monitoring of vital signs in the outpatient setting is a developing field with differing levels of evidence for each monitor. The most common clinical application was heart rate monitoring. Blood pressure and oxygen saturation measurements were the least common applications. There is a need for clinical validation studies in the outpatient setting to prove the potential of many of the monitors identified.

Research in this area is in its infancy. Future research should look at aggregating the results of validity and reliability and patient outcome studies for each monitor and between different devices. This would provide a more holistic overview of the potential for the clinical use of each device.

Reliability of Zephyr Bioharness and Fitbit Charge Measures of Heart Rate and Activity at Rest, During the Modified Canadian Aerobic Fitness Test, and Recovery

Nazari, G, MacDermid, JC, Sinden, KE, Richardson, J, and Tang, A. Reliability of Zephyr Bioharness and Fitbit Charge measures of heart rate and activity at rest, during the modified Canadian Aerobic Fitness Test, and recovery. J Strength Cond Res 33(2): 559-571, 2019-The purpose of this study was to determine the intrasession and intersession reliability of Zephyr Bioharness (ZB) and Fitbit Charge variables in both healthy men and women at rest, during the Modified Canadian Aerobic Fitness Test (mCAFT), and throughout recovery. Stratified convenience and snowball sampling were used to recruit 60 participants (30 women, 48 ± 15 years) and (30 men, 48 ± 15 years) from McMaster University student, staff, and faculty population. At rest, intrasession average heart rate (b·min). Intraclass correlation coefficients (ICCs) and Standard Error of Measurement [SEM] for Zephyr ranged from (0.94-0.97) [1.17-1.70] to (0.92-0.97) [1.45-2.10] for Fitbit Charge. During the mCAFT, the Zephyr ICCs and (SEM) ranged from 0.31-0.99 (1.28-8.10) to 0.45-0.99 (1.45-8.71) for the Fitbit Charge. Throughout the recovery, the ICCs and (SEM) ranged from 0.44-0.98 (1.26-10.47) to 0.45-0.98 (1.15-11.90) for Zephyr and Fitbit devices, respectively. At rest, intersession ICCs (SEM) for Zephyr and Fitbit ranged from 0.90-0.94 (1.73-2.37) to 0.88-0.94 (1.83-2.67), respectively. At mCAFT, the Zephyr ICCs (SEM) ranged from 0.91-0.97 (3.12-4.64) to 0.85-0.98 (3.28-4.88) for the Fitbit. Throughout the recovery, the ICCs (SEM) ranged from 0.93-0.97 (2.65-4.66) to 0.76-0.91 (3.17-4.67) for Zephyr and Fitbit devices, respectively. To conclude, both the ZB and Fitbit Charge devices demonstrated excellent reliability measures throughout the 3 phases. The findings from our study add to the existing pool of literature regarding the reliability parameters of wearable devices and suggest that stable and consistent measures of heart rate and physical activity can be obtained using ZB and Fitbit Charge devices among healthy male and female participants at rest, during a standardized submaximal fitness test (mCAFT), and throughout recovery.

Data Integrity-Based Methodology and Checklist for Identifying Implementation Risks of Physiological Sensing in Mobile Health Projects: Quantitative and Qualitative Analysis

Background

Mobile health (mHealth) technologies have the potential to bring health care closer to people with otherwise limited access to adequate health care. However, physiological monitoring using mobile medical sensors is not yet widely used as adding biomedical sensors to mHealth projects inherently introduces new challenges. Thus far, no methodology exists to systematically evaluate these implementation challenges and identify the related risks.

Objective

This study aimed to facilitate the implementation of mHealth initiatives with mobile physiological sensing in constrained health systems by developing a methodology to systematically evaluate potential challenges and implementation risks.

Methods

We performed a quantitative analysis of physiological data obtained from a randomized household intervention trial that implemented sensor-based mHealth tools (pulse oximetry combined with a respiratory rate assessment app) to monitor health outcomes of 317 children (aged 6-36 months) that were visited weekly by 1 of 9 field workers in a rural Peruvian setting. The analysis focused on data integrity such as data completeness and signal quality. In addition, we performed a qualitative analysis of pretrial usability and semistructured posttrial interviews with a subset of app users (7 field workers and 7 health care center staff members) focusing on data integrity and reasons for loss thereof. Common themes were identified using a content analysis approach. Risk factors of each theme were detailed and then generalized and expanded into a checklist by reviewing 8 mHealth projects from the literature. An expert panel evaluated the checklist during 2 iterations until agreement between the 5 experts was achieved.

Results

Pulse oximetry signals were recorded in 78.36% (12,098/15,439) of subject visits where tablets were used. Signal quality decreased for 1 and increased for 7 field workers over time (1 excluded). Usability issues were addressed and the workflow was improved. Users considered the app easy and logical to use. In the qualitative analysis, we constructed a thematic map with the causes of low data integrity. We sorted them into 5 main challenge categories: environment, technology, user skills, user motivation, and subject engagement. The obtained categories were translated into detailed risk factors and presented in the form of an actionable checklist to evaluate possible implementation risks. By visually inspecting the checklist, open issues and sources for potential risks can be easily identified.

Conclusions

We developed a data integrity–based methodology to assess the potential challenges and risks of sensor-based mHealth projects. Aiming at improving data integrity, implementers can focus on the evaluation of environment, technology, user skills, user motivation, and subject engagement challenges. We provide a checklist to assist mHealth implementers with a structured evaluation protocol when planning and preparing projects.

Psychometric properties of the Zephyr bioharness device: a systematic review

BACKGROUND

Technological development and improvements in Wearable Physiological Monitoring devices, have facilitated the wireless and continuous field-based monitoring/capturing of physiologic measures in healthy, clinical or athletic populations. These devices have many applications for prevention and rehabilitation of musculoskeletal disorders, assuming reliable and valid data is collected. The purpose of this study was to appraise the quality and synthesize findings from published studies on psychometric properties of heart rate measurements taken with the Zephyr Bioharness device.

METHODS

We searched the Embase, Medline, PsycInfo, PuMed and Google Scholar databases to identify articles. Articles were appraised for quality using a structured clinical measurement specific appraisal tool. Two raters evaluated the quality and conducted data extraction. We extracted data on the reliability (intra-class correlation coefficients and standard error of measurement) and validity measures (Pearson/Spearman's correlation coefficients) along with mean differences. Agreement parameters were summarised by the average biases and 95% limits of agreement.

RESULTS

A total of ten studies were included: quality ratings ranged from 54 to 92%. The intra-class correlation coefficients reported ranged from 0.85-0.98. The construct validity coefficients compared against gold standard calibrations or other commercially used devices, ranged from 0.74-0.99 and 0.67-0.98 respectively. Zephyr Bioharness agreement error ranged from - 4.81 (under-estimation) to 3.00 (over-estimation) beats per minute, with varying 95% limits of agreement, when compared with gold standard measures.

CONCLUSION

Good to excellent quality evidence from ten studies suggested that the Zephyr Bioharness device can provide reliable and valid measurements of heart rate across multiple contexts, and that it displayed good agreements vs. gold standard comparators - supporting criterion validity.

Remotely Delivered Exercise-Based Cardiac Rehabilitation: Design and Content Development of a Novel mHealth Platform

Background

Participation in traditional center-based cardiac rehabilitation exercise programs (exCR) is limited by accessibility barriers. Mobile health (mHealth) technologies can overcome these barriers while preserving critical attributes of center-based exCR monitoring and coaching, but these opportunities have not yet been capitalized on.

Objective

We aimed to design and develop an evidence- and theory-based mHealth platform for remote delivery of exCR to any geographical location.

Methods

An iterative process was used to design and develop an evidence- and theory-based mHealth platform (REMOTE-CR) that provides real-time remote exercise monitoring and coaching, behavior change education, and social support.

Results

The REMOTE-CR platform comprises a commercially available smartphone and wearable sensor, custom smartphone and Web-based applications (apps), and a custom middleware. The platform allows exCR specialists to monitor patients’ exercise and provide individualized coaching in real-time, from almost any location, and provide behavior change education and social support. Intervention content incorporates Social Cognitive Theory, Self-determination Theory, and a taxonomy of behavior change techniques. Exercise components are based on guidelines for clinical exercise prescription.

Conclusions

The REMOTE-CR platform extends the capabilities of previous telehealth exCR platforms and narrows the gap between existing center- and home-based exCR services. REMOTE-CR can complement center-based exCR by providing an alternative option for patients whose needs are not being met. Remotely monitored exCR may be more cost-effective than establishing additional center-based programs. The effectiveness and acceptability of REMOTE-CR are now being evaluated in a noninferiority randomized controlled trial.

Telehealth exercise-based cardiac rehabilitation: a systematic review and meta-analysis

OBJECTIVE

Despite proven effectiveness, participation in traditional supervised exercise-based cardiac rehabilitation (exCR) remains low. Telehealth interventions that use information and communication technologies to enable remote exCR programme delivery can overcome common access barriers while preserving clinical supervision and individualised exercise prescription. This meta-analysis aimed to determine the benefits of telehealth exCR on exercise capacity and other modifiable cardiovascular risk factors compared with traditional exCR and usual care, among patients with coronary heart disease (CHD).

METHODS

CINAHL, The Cochrane Library, Embase, MEDLINE, PubMed and PsycINFO were searched from inception through 31 May 2015 for randomised controlled trials comparing telehealth exCR with centre-based exCR or usual care among patients with CHD. Outcomes included maximal aerobic exercise capacity, modifiable cardiovascular risk factors and exercise adherence.

RESULTS

11 trials (n=1189) met eligibility criteria and were included in the review. Physical activity level was higher following telehealth exCR than after usual care. Compared with centre-based exCR, telehealth exCR was more effective for enhancing physical activity level, exercise adherence, diastolic blood pressure and low-density lipoprotein cholesterol. Telehealth and centre-based exCR were comparably effective for improving maximal aerobic exercise capacity and other modifiable cardiovascular risk factors.

CONCLUSIONS

Telehealth exCR appears to be at least as effective as centre-based exCR for improving modifiable cardiovascular risk factors and functional capacity, and could enhance exCR utilisation by providing additional options for patients who cannot attend centre-based exCR. Telehealth exCR must now capitalise on technological advances to provide more comprehensive, responsive and interactive interventions.

Automated Management of Exercise Intervention at the Point of Care: Application of a Web-Based Leg Training System

Background

Recent advances in information and communication technology have prompted development of Web-based health tools to promote physical activity, the key component of cardiac rehabilitation and chronic disease management. Mobile apps can facilitate behavioral changes and help in exercise monitoring, although actual training usually takes place away from the point of care in specialized gyms or outdoors. Daily participation in conventional physical activities is expensive, time consuming, and mostly relies on self-management abilities of patients who are typically aged, overweight, and unfit. Facilitation of sustained exercise training at the point of care might improve patient engagement in cardiac rehabilitation.

Objective

In this study we aimed to test the feasibility of execution and automatic monitoring of several exercise regimens on-site using a Web-enabled leg training system.

Methods

The MedExercise leg rehabilitation machine was equipped with wireless temperature sensors in order to monitor its usage by the rise of temperature in the resistance unit (Δt°). Personal electronic devices such as laptop computers were fitted with wireless gateways and relevant software was installed to monitor the usage of training machines. Cloud-based software allowed monitoring of participant training over the Internet. Seven healthy participants applied the system at various locations with training protocols typically used in cardiac rehabilitation. The heart rates were measured by fingertip pulse oximeters.

Results

Exercising in home chairs, in bed, and under an office desk was made feasible and resulted in an intensity-dependent increase of participants’ heart rates and Δt° in training machine temperatures. Participants self-controlled their activities on smart devices, while a supervisor monitored them over the Internet. Individual Δt° reached during 30 minutes of moderate-intensity continuous training averaged 7.8°C (SD 1.6). These Δt° were used as personalized daily doses of exercise with automatic email alerts sent upon achieving them. During 1-week training at home, automatic notifications were received on 4.4 days (SD 1.8). Although the high intensity interval training regimen was feasible on-site, it was difficult for self- and remote management. Opportunistic leg exercise under the desk, while working with a computer, and training in bed while viewing television were less intensive than dosed exercise bouts, but allowed prolonged leg mobilization of 73.7 minutes/day (SD 29.7).

Conclusions

This study demonstrated the feasibility of self-control exercise training on-site, which was accompanied by online monitoring, electronic recording, personalization of exercise doses, and automatic reporting of adherence. The results suggest that this technology and its applications are useful for the delivery of Web-based exercise rehabilitation and cardiac training programs at the point of care.