Next Article in Journal
Digitalization, Electricity Consumption and Carbon Emissions—Evidence from Manufacturing Industries in China
Next Article in Special Issue
Patients’ Perceptions of Exercise-Based Cardiac Telerehabilitation after a Myocardial Infarction—A Qualitative Study
Previous Article in Journal
Understand Delegates Risk Attitudes and Behaviour: The Moderating Effect of Trust in COVID-19 Vaccination
Previous Article in Special Issue
Characteristics, Components, and Efficacy of Telerehabilitation Approaches for People with Chronic Obstructive Pulmonary Disease: A Systematic Review and Meta-Analysis
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
IJERPH
Volume 20
Issue 5
10.3390/ijerph20053937
ijerph-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Assessing the Efficacy of a Virtual Assistant in the Remote Cardiac Rehabilitation of Heart Failure and Ischemic Heart Disease Patients: Case-Control Study of Romanian Adult Patients

by
Andreea-Elena Lăcraru
1,
Ștefan-Sebastian Busnatu
1,
Maria-Alexandra Pană
1,*,
Gabriel Olteanu
1,
Liviu Șerbănoiu
1,
Kai Gand
2,
Hannes Schlieter
2,
Sofoklis Kyriazakos
3,
Octavian Ceban
4,
Cătălina Liliana Andrei
1 and
Crina-Julieta Sinescu
1
1
Department of Cardiology, University of Medicine and Pharmacy “Carol Davila”, Emergency Hospital “Bagdasar-Arseni”, 050474 Bucharest, Romania
2
Research Group Digital Health, Faculty of Business and Economics, Technische Universitat Dresden, 01062 Dresden, Germany
3
Department of Business Development and Technology, Aarhus University, 7400 Aarhus, Denmark
4
Economic Cybernetics and Informatics Department, University of Economic Studies, 010374 Bucharest, Romania
*
Author to whom correspondence should be addressed.
Int. J. Environ. Res. Public Health 2023, 20(5), 3937; https://doi.org/10.3390/ijerph20053937
Submission received: 6 January 2023 / Revised: 17 February 2023 / Accepted: 19 February 2023 / Published: 22 February 2023
(This article belongs to the Special Issue Telerehabilitation for Patients)
Browse Figures
Review Reports Versions Notes

Abstract

:
Cardiovascular diseases (CVDs) are the leading cause of mortality in Europe, with potentially more than 60 million deaths per year, with an age-standardized rate of morbidity-mortality higher in men than women, exceeding deaths from cancer. Heart attacks and strokes account for more than four out of every five CVD fatalities globally. After a patient overcomes an acute cardiovascular event, they are referred for rehabilitation to help them to restore most of their normal cardiac functions. One effective way to provide this activity regimen is via virtual models or telerehabilitation, where the patient can avail themselves of the rehabilitation services from the comfort of their homes at designated timings. Under the funding of the European Union’s Horizon 2020 Research and Innovation program, grant no 769807, a virtual rehabilitation assistant has been designed for elderly patients (vCare), with the overall objective of supporting recovery and an active life at home, enhancing patients’ quality of life, lowering disease-specific risk factors, and ensuring better adherence to a home rehabilitation program. In the vCare project, the Carol Davila University of Bucharest (UMFCD) was in charge of the heart failure (HF) and ischemic heart disease (IHD) groups of patients. By creating a digital environment at patients’ homes, the vCare system’s effectiveness, use, and feasibility was evaluated. A total of 30 heart failure patients and 20 ischemic heart disease patients were included in the study. Despite the COVID-19 restrictions and a few technical difficulties, HF and IHD patients who performed cardiac rehabilitation using the vCare system had similar results compared to the ambulatory group, and better results compared to the control group.

1. Introduction

1.1. Epidemiology of Cardiovascular Disease and the Current Status of Cardiac Rehabilitation

Coronary heart disease, cerebrovascular disease, rheumatic heart disease, and other illnesses are within the category of heart and blood vessel disorders known as cardiovascular diseases (CVDs). According to the World Health Organization (WHO), CVDs are the leading cause of mortality in Europe, with potentially more than 60 million deaths per year, with an age-standardized rate of morbidity-mortality higher in men than women, exceeding deaths from cancer. Heart attacks and strokes account globally for more than four out of every five CVD fatalities [1,2,3].
After a patient overcomes an acute cardiovascular event, they are referred for rehabilitation to help them restore most of their normal cardiac functions. That is where cardiovascular rehabilitation comes in. Cardiovascular rehabilitation (CR) is a customized program that combines medical therapy and physical activity with medical education, in order to accelerate recovery and enhance the health status in people with heart disease [4]. The 2021 European guidelines’ recommendations on CVD prevention in clinical practice underline that medication adherence and lifestyle modifications are crucial in secondary CVD prevention, which may be expanded and improved via CR programs, lowering the incidence of recurrent heart disease and the risk of overall mortality [5].
After the outbreak of the COVID-19 pandemic, there has been a great burden on hospitals and outpatient departments to cater to the needs of all patients appropriately and in a satisfactory manner, while respecting the conditions for preventing the new coronavirus from spreading. As a result, CR programs have been suspended, partly or altogether, in numerous hospitals and specialized rehabilitation clinics. Exercise testing and group-based exercise training programs have been difficult to implement during this period [6,7]. Despite all these difficulties that the pandemic has brought, the European Society of Cardiology and the American Heart Association maintain the recommendation of cardiac rehabilitation after myocardial infarction (MI), coronary artery bypass graft (CABG), and percutaneous coronary intervention (PCI), and find CR to be an important step towards the complete recovery of affected patients [8,9,10,11,12].

1.2. Virtual Assistants as an Alternative to Classic Recovery Programs

Despite the relaxation of COVID-19 restrictions, its presence still lingers in our society, and we must look after patients who need CR. One effective way to provide this activity regimen is via virtual models or telerehabilitation, where the patient can avail themselves of rehabilitation services from the comfort of their homes, at designated times. In 2021, in Belgium, 52% of rehabilitation facilities already offered CR programs with the use of telerehabilitation. Physicians, nurses, dieticians, physiotherapists, and psychologists were all engaged in remote CR application. Exercise instruction, nutrition counselling, smoking cessation assistance, cardiovascular education, psychological support, medication adherence, and weight management were among the CR components that were carried out [13,14,15].
It would be safe to say that virtual rehabilitation is not an unknown concept, and providing virtual care to affected patients from the comfort of their homes is possible, as noted in a stroke study conducted in 2018. These needs could be met by virtual reality (VR). As a more engaging and motivational tool, game-based treatments may increase patients’ involvement in rehabilitation therapy. Mobile devices may provide customized home-based treatment, with interactive contact between patients and therapists, such as cellphones, tablets, and personal computers, which can provide much-needed therapy and rehabilitation to the patients, within their comfort zone [16,17].
Despite the benefits of telerehabilitation, demonstrated in multiple studies, there are also data that cast doubt, which leaves a gap for us to explore whether virtual services, in the form of telerehabilitation or video games, provide the sufficient care that a patient needs after an acute cardiovascular or neurological event [18].
In 2017, under the funding of the European Union’s Horizon 2020 Research and Innovation program, grant no 769807, a virtual rehabilitation assistant has been designed for elderly patients, with the overall objective of supporting recovery and an active life at home, enhance patients’ quality of life, lowering disease-specific risk factors, and ensuring better adherence to a home rehabilitation program. The Virtual Coaching Activities for Rehabilitation in Elderly (vCare) project has included partners from seven European countries, with the necessary technical and medical specialization for its construction. The entire project lasted five years, ending in August 2022 [19].
The primary goal of the project was to build and implement the virtual assistant in patients’ homes and to remotely monitor the individualized rehabilitation program that each of them received. Medical recovery areas included stroke (SD), Parkinson’s disease (PD), heart failure (HF), and ischemic heart disease (IHD) [19].
The secondary aim of the project was to evaluate the effectiveness of the remote recovery program. Contextually, part of the project took place during the COVID-19 pandemic, which made it difficult on one hand to implement the project in the patients’ homes, but on the other hand highlighted the importance of such a system in the patients’ lives [19].
In the vCare project, the Carol Davila University of Bucharest (UMFCD) was in charge of the heart failure and ischemic heart disease use cases.

2. Materials and Methods

2.1. Study Design and Objectives

We conducted a prospective interventional pilot study within Carol Davila University of Medicine and Pharmacy, Bucharest, on patients diagnosed with chronic heart failure and ischemic heart disease.
The primary objective of the study was to evaluate the use, feasibility, and effectiveness of the vCare system in motivating heart failure and ischemic heart disease patients to actively engage in a personalized cardiac rehabilitation program, in order to improve independence and quality of life.
The secondary objectives evaluated were the impact of the virtual system on the reduction of cardiovascular risk factors, on the adherence of patients to the rehabilitation plan of care, and on the personalization of treatment and promotion of an active life at home. The user experience was also evaluated through standardized questionnaires, with the aim of improving the system in the future with the help of user perception.
The virtual coaching system aimed to support the patient based on his/her needs, both in the home rehabilitation process (continuity of care) and in everyday activities, in order to promote an active and healthy lifestyle and to reduce the worsening of the disease and/or the occurrence of dangerous events (e.g., decompensation of heart failure). Data from various devices were processed and transformed into useful information for the patient.

2.2. Profile of Enrolled Patients

The recruitment period of the subjects was between 6–12 weeks and took place in the cardiology clinic of UMFCD within Bagdasar–Arseni Emergency Clinical Hospital in Bucharest. At the end of this period we managed to enroll 30 patients with chronic heart failure and 20 patients with ischemic heart disease. The inclusion and exclusion criteria used for enrollment in the study are presented in Table 1.
Considering that all patients eligible for enrollment in the project would have benefited from a cardiac rehabilitation program, we considered that the most equitable method of dividing them into study subgroups was by randomization.
After enrollment, the heart failure study group was randomly divided into: the vCare experimental subgroup (EG), who performed cardiac rehabilitation at home using the vCare app; the ambulatory subgroup (AG), who underwent conventional cardiac rehabilitation at Bagdasar–Arseni Hospital, in Bucharest; and the control subgroup (CG), who only received advice at discharge on how to perform a cardiac rehabilitation program at home. Consequently, the ischemic heart disease study group was randomly divided into: the vCare experimental subgroup (EG), who performed cardiac rehabilitation at home using the vCare app; and the control subgroup (AG), who only received advice at discharge on how to perform a cardiac rehabilitation program at home. Each of the presented subgroups had an equivalent number of 10 patients. The study took place over a period of three months for both use cases: heart failure (HF) and ischemic heart disease (IHD). After this period, the analysis and interpretation of the collected data, and the outline of the obtained results, were carried out, an action that stretched over a period of two months.
The enrollment of a small number of patients in this project was essential for testing the implemented system. As expected, technical errors occurred during the study, requiring them to be physically addressed by a technical team, which would have been difficult to achieve on a large group of patients. The implementation of this project overlapped with the COVID-19 pandemic, which led to the emergence of various difficulties (patient refusal, delay in the delivery of equipment, fear on the part of patients). Because of these problems, the cardiac recovery period of some patients in the experimental groups was less than 3 months, which may have adversely influenced the results obtained.

2.3. Ethical Considerations

The study groups consisted of patients who met the inclusion criteria and did not present any exclusion criteria, and who, prior to enrollment, underwent a detailed presentation of the study and training and guidance in the use of the equipment provided by the research team. The protection of patient data was carried out by means of the pseudo-anonymization method as follows: each patient received an identifier, with the purpose of separating personal data from those collected in the study. Also, each study participant was informed about the confidentiality, the collecting method, and the use of personal data. The research study presented no potential physical, legal, or psychological risk and was conducted in accordance with the ethical principles of the Helsinki Declaration of Human Rights. Each enrolled patient signed an informed consent for voluntary participation.

2.4. Initial Assessment and Structuring of the Virtual Environment

The clinical and paraclinical examination protocol was the same for each use case. Each patient underwent a clinical examination at the time of enrollment (T0), the collection of blood samples (blood count, ionogram, creatinine level, liver enzyme levels lipid profile, blood sugar, uric acid, creatine kinase level, erythrocyte sedimentation rate, fibrinogen, urine test), echocardiography, a cardio-pulmonary exercise test (for the assessment of exercise capacity and personalization of the cardiac rehabilitation program), a 24 h blood pressure monitoring, a 24 h electrocardiogram monitoring (to rule out uncontrolled blood pressure and potentially fatal arrhythmias), and psychological evaluation by means of standardized questionnaires (Minnesota, HADS scale, Fagerstrom, EuroQol-5D, EQ-VAS). With the note that the Minnesota questionnaire has been applied only to heart failure patients (Table 2).
Each patient of both vCare experimental groups (HF and IHD) received a toolkit that structured the virtual assistant digital environment. The devices that led to the structuring of this digital environment are presented in Table 3. The role, and collected parameters, of each of the devices used are presented in Table 4.

2.5. 3-Month Assessment and Collected Parameters

At the end of the rehabilitation program (T1), all patients were re-evaluated following the same examination protocol from baseline. The subjects allocated in the experimental group were additionally examined with three other evaluation scales, aiming to rate the usability perceived with the vCare components during their experience in the pilot trial (user experience questionnaire, system usability scale, technology acceptance model) (Table 5).
Standardized psychological and usability questionnaires were used in the study due to the increased reliability, validity, sensitivity, and objectivity of the answers provided.
The evaluation of the enrolled patients led to the collection of demographic, social, clinical, biological, and imaging parameters, and to a quantification of the cardiovascular risk factors present in the study groups. Along with them, the answers to the standardized questionnaires applied were collected and indexed. Parameters recorded by the virtual assistant were automatically collected and indexed for each patient of the two experimental groups.

2.6. Virtual Assistant Components

The cardiac rehabilitation program offered by the virtual assistant consisted of the components that are presented in Table 6, alongside the services provided. Apart from the alcohol reduction component, which has been designed and used only for the IHD study group, these were common to both study groups (Table 6).
The vCare virtual assistant was controlled remotely by the medical research team through a platform called Kiola, with access restricted to medical staff only. When the patient was enrolled in the remote cardiac recovery program, their medical data were entered and the cardiac recovery program was established by the cardiac rehabilitation team of specialists. Once active, it was found on the patient’s tablet at home, and the virtual assistant would guide them step by step in order to carry out the recommended daily activities. Each component of the vCare program had the capacity of automatic self-regulation through positive or negative feedback received from the patient, its positive or negative evolution, and/or the vital parameters monitored. The Kiola platform also had the role of storing all the recorded parameters, in order that they could be visualized at any time by the medical team.

2.7. Statistical Analysis

The UMFCD team entered the collected parameters from the HF and IHD patients who were recruited in the study into a Microsoft Excel database. Input variables were of type integer, real, or Boolean and were analyzed and studied individually. In order to draw conclusions regarding the improvements, distributions, and means of values for each subgroup, before and after values were compared. The t-test was used to determine if there were any changes between the values recorded at T0 (prior to initiation of the cardiac rehabilitation program) and T1 (after the conclusion of the rehabilitation program), and if these differences were by chance or had statistical significance. There were not missing values in the dataset. Finally, Python 3.8.5 was used to aggregate the findings, refine the data, and create tables.

3. Results

3.1. Heart Failure Participants

During the recruitment period, 47 initially eligible patients were identified for enrollment in the study. After clinical and paraclinical evaluation, 13 patients were excluded, due to the fact that their medical status did not allow them to enroll in a cardiac rehabilitation program. Thirty-four patients remained, of which four did not have the possibility of internet connection and/or a TV with an HDMI port at home. They were also excluded, thus forming a group of 30 patients. The 30 patients were randomly divided into the three previously mentioned subgroups and, out of the 10 patients of the experimental subgroup, one patient dropped out of the study, stating that there was too little space at home to carry out the exercises. However, the patient who dropped out performed the final assessment of the study, so their data were taken into account in the final analysis.
A total of 30 heart failure patients (17/13 M/F; 61.53 ± 9.41 years) were included in the study. The gender distribution in the EG and AG was five male patients and five female patients each, and in the CG there were six male patients and four female patients. The area of origin of the enrolled patients was mostly urban, with only one rural patient in EG, two rural patients in AG, and four rural patients in CG. From an educational point of view, most of the enrolled subjects had a high educational level, and only seven had an inferior educational level. From the point of view of financial status, 17 patients had average incomes, seven high incomes, and six patients had low incomes, evaluated at the current financial status of Romania.
Cardiovascular risk factors were evaluated in the study group and the following were identified, out of 30 patients: 10 were smokers; 21 were overweight, three had grade I obesity, and six had normal weight; 18 were identified with a sedentary level of physical activity; 28 were hypertensive, 10 patients had type 2 diabetes miellitus, and 18 had dyslipidemia.
The evaluation of exercise capacity, measured by VO2max at T0 and T1, shows a statistically significant difference between the pre- and post-intervention groups’ values. Thus, an improvement in exercise capacity can be observed in both EG and AG, from 19.21 mL/kg/min and 19.18 mL/kg/min, to 21.32 mL/kg/min and 21.98 mL/kg/min, respectively. On the other hand, in the CG the VO2max decreased from 18.46 mL/kg/min to 17.04 mL/kg/min (Figure 1).
According to Figure 2, between T0 and T1, LDL-cholesterol levels decreased in both experimental and ambulatory groups. The LDL-cholesterol improvement was much more pronounced in the EG, the decrease being approximately 30% of the initial value. The CG did not show significant changes between T0 and T1 (Figure 2).
In terms of quality of life, in the vCare and ambulatory groups an improvement was observed, along with a decrease in anxiety and depression levels. Patients enrolled in the EG and AG showed significantly improved results in both the MLFQH questionnaire and on the HAD scale. Unlike them, in the CG no improvement in quality of life and anxiety levels was observed, but the severity of the depression level increased (p-value = 0.4) (Figure 3, Figure 4 and Figure 5).
All smoking patients in the heart failure study group were assessed by means of the Fagerstrom questionnaire at the beginning of the cardiac rehabilitation program. In the EG, we enrolled three smokers, out of which only one was considered a regular smoker. Through the intervention of the virtual assistant, the patients in the EG presented a 50% reduction in nicotine use. In the AG, the decline in tobacco use was similar in terms of impact. In the CG, all four patients who were identified as smokers continued to smoke, but they also showed reductions in the number of cigarettes consumed per day (Figure 6).

3.2. Ischemic Heart Disease Pilot Results

During the recruitment period, 34 eligible patients were identified for enrollment in the study. After clinical and paraclinical evaluations, six patients were excluded due to the fact that their medical status did not allow them to enroll in a cardiac rehabilitation program. Twenty-eight patients remained, of which eight did not have the possibility of internet connection at home, and/or a TV with an HDMI port at home, and/or found the virtual assistant too difficult to use, according to the initial presentation. They were excluded, thus forming a group of 20 patients. The 20 patients were randomly divided into the two previously mentioned subgroups and, out of the experimental subgroup, two patients dropped out of the study, due to technical errors that occurred during the cardiac recovery program. However, the patients that dropped out performed the final assessment of the study, so their data were considered in the final analysis.
A total of 20 ischemic heart disease patients (16/4 M/F; 58.1 ± 7.12 years) were included in the study. The gender distribution was even between the two subgroups, with eight male and two female patients in each. The area of origin of the enrolled patients was mostly urban, with two rural patients in the EG and one rural patient in the CG. From the educational point of view, most of the enrolled patients had a high educational level and only three patients had inferior educational level. From the point of view of financial status, 11 patients had average incomes, four high incomes, and five low incomes, evaluated at the current financial status of Romania.
Cardiovascular risk factors were evaluated in the study group and the following were identified, out of 20 patients: seven were smokers; 12 were overweight, five patients had grade I obesity, and three patients had normal weight; 17 patients were identified with a sedentary level of physical activity; 20 patients were hypertensive, seven patients had type 2 diabetes miellitus, and 17 patients had dyslipidemia.
The effort capacity of the IHD study group was evaluated equivalently by means of the VO2max parameter of the cardiopulmonary test. The patients enrolled in the EG improved their VO2max level from 16.58 mL/kg/min to 20.7 mL/kg/min, while the ones in the CG showed a decrease of 1.75 mL/kg/min from T0 to T1 (Figure 7).
Regarding the assessment of dyslipidemia, both EG and CG showed improvements of LDL-cholesterol levels. In this regard, the CG showed a greater decrease, from 165.34 mg/dL to 132.42 mg/dL, but without reaching the target values for an ischemic heart disease patient. In the EG group a decrease of only 21.05 mg/dL from baseline was observed. (Figure 8).
The anxiety and depression levels in the IHD study group were assessed using the HAD scale. The anxiety level did not undergo any change in the CG during the study period, while a slight increase was observed in the EG. On the other hand, a significant improvement was assessed in depression level, with a much greater decrease in EG compared to CG (Figure 9).
At the end of the cardiac rehabilitation program, in the EG only one out of four smokers continued to use tobacco, but with a reduction in the addiction level, quantified by the number of daily consumed cigarettes. In the CG, two patients quit smoking, and one continued, with the same level of addiction as before the study period (Figure 10).

3.3. Quality of Life Assessment

3.3.1. Heart Failure Quality of Life Results

EuroQol-5D assesses five parameters considered as defining factors for a high quality of life (mobility, pain, anxiety, self-care, and daily activities). Between T0 and T1 a considerable improvement was evaluated in the EG and AG of the HF study groups, with superior results in the latter. In the CG, the quality of life did not undergo significant changes, with the parameters undergoing statistically insignificant changes (Figure 11).
In the self-assessment quality of life questionnaire, the results were slightly different, with a small increase in the EG results and a more important one in the AG. An important discrepancy to mention is in the CG results, which highlight different scores than those of the EuroQol-5D. This difference may underline the importance of using multiple analysis parameters in the health status of patients (Figure 12).

3.3.2. Ischemic Heart Disease Quality of Life Results

The patients enrolled in the EG of the IHD study groups were assessed with an increase in quality of life at the end of the cardiac rehabilitation program via the vCare app, while the quality of life of the CG patients remained the same between T0 and T1 (Figure 13).
Regarding the application of the EQ-VAS questionnaire to the IHD study groups, the results were consistent with those of the EuroQol-5D. Consequently, patients from the EG showed a 15% increase in quality of life between T0 and T1, while in the CG there were no changes observed (Figure 14).
An insight into how the parameters recorded by the virtual assistant are stored is shown in Table 7 and Table 8. These are examples of monitoring the number of steps and active weeks parameters within the cardiac recovery program. In a similar manner, all parameters recorded by the virtual assistant were stored and found on the Kiola platform, where they were analyzed by the medical team. It is important to mention that each parameter was individualized for each patient, so that the adherence may be different depending on the preset target for each one (Table 7 and Table 8).

3.4. Usefulness of vCare system

In the user experience questionnaire, all patients from the HF and IHD EG evaluated the system as an element of novelty, attractiveness, and perspicuity. Neutral and low scores were received for efficiency and stimulation, due to the technical problems they encountered while using it. The system usability scale score received was above 68 points in both study groups, which is considered the limit of acceptability, a result which highlights that patients appreciated the ease of use of the system. The TAM questionnaire results showed a mean score of 30.5 ± 4.08 for perceived usefulness, a mean score of 28.6 ± 3.35 for perceived ease of use, and a mean total score of 59.1 ± 7.43, in the HF EG; and a mean score of 29.8 ± 4.82 for perceived usefulness, a mean score of 29.6 ± 5.46 for perceived ease of use, and a mean total score of 59.1 ± 7.43, in the IHD EG.

4. Discussion

Cardiac rehabilitation is a central element of the secondary prevention of cardiovascular disease in patients, due to the benefits it has in terms of decreasing the morbidity-mortality rate, hospitalizations, and by improving effort tolerance and ensuring social reintegration. Despite its multiple benefits, there is a constant gap in the non-pharmacological treatment of cardiovascular patients, caused by the absence of continuity of care after discharge [28,29].
The pilot study we conducted on heart failure and ischemic heart disease Romanian patients aimed to evaluate the effectiveness and use of the vCare virtual assistant in their remote cardiac rehabilitation. In terms of exercise capacity, we can state that in the HF study group, the virtual assistant is at least equivalent to an ambulatory cardiac rehabilitation treatment. Considering the negative results obtained in the control group, we can consider it an extremely efficient alternative for patients who cannot access in-person cardiac recovery programs. In the IHD study group, although the results on exercise capacity were not as spectacular, they were also superior to not performing any cardiac recovery. The results highlighted in our study are in line with the study conducted by Chen and colleagues, where they observed that exercise tolerance, peak oxygen uptake, and quality of life may all be considerably improved by home-based cardiac rehabilitation in individuals with HF. Also, other data from other current specialized literature highlights the positive effect of telerehabilitation on the increased physical performance of cardiovascular patients. The patients’ perceived sense of monitoring increases their compliance with cardiac rehabilitation programs [30,31].
The virtual assistant also showed effectiveness in reducing cardiovascular risk factors, particularly high cholesterol levels and nicotine addiction, in both the HF and IHD study groups. Here, we consider the medical education service provided via the vCare app and the constant assistant–patient relationship to be of great help. Robotic medical education is a secondary prevention alternative that has been long discussed in the medical field as a solution to the gap between patients’ discharge and follow-up, especially for the elderly [32].
In terms of anxiety and depression levels, the experimental and ambulatory groups of patients experienced a reduction, whereas in the control groups there was no change. A recent review of telerehabilitation effects on heart failure patients found an improvement in patients’ depression and anxiety levels, physical capacity, and overall quality of life [33].
Further, the self-assessment of state of health (EQ-VAS) data collected at T0 and T1, suggested that patients in the vCare group had an important improvement in quality of life at the end of the rehabilitation program. Current literature suggests equivalence or a slight positive difference in quality of life between center-based cardiac rehabilitation and telerehabilitation, in favor of the latter [34,35,36].
In a systematic review and meta-analysis of telerehabilitation of heart failure patients, Cordeiro et al. highlighted that telerehabilitation enhances social skills, exercise tolerance, sexual activity, and heart failure symptoms, being at least as effective as center-based cardiac rehabilitation programs [37,38].
For ischemic heart disease patients, similar results from the current literature state that home-based cardiac recovery via remote-monitoring has as effective results as the classic cardiac rehabilitation programs. In their study, Escobar et al. used a remote electrocardiographic monitoring device for the remote-monitored group and stated no significant difference between the two methods in terms of exercise tolerance and recovery rate [39].
Based on our results, and those provided by the current literature, the virtual assistant seems a viable alternative for heart failure and ischemic heart disease patients to perform remote cardiac rehabilitation with the same benefits as a center-based one, from the comfort of their home [40].

5. Future Perspectives

Our results might serve as a stepping stone for future studies to come, that would explore the vCare system’s efficacy on larger groups of patients. Furthermore, our findings may assist policymakers in developing new legislation to incorporate this system in the non-pharmacological treatment of cardiac patients at home. In addition to the above stated points, the vCare system could further be improved by creating an application that is compatible with mobile phones, in order to facilitate its use.

6. Limitations

The study’s shortcomings are represented by the small sample size and the use of only the vCare tablet app. A more accurate understanding of the effectiveness of this method would have resulted from having an app that could operate cross-platform, on both tablets and phones and multiple operating systems.

7. Conclusions

In conclusion, cardiac recovery via a virtual assistant is possible, and the results on exercise capacity, cardiovascular risk factors, and quality of life are almost equivalent to those of classical rehabilitation.

Author Contributions

Conceptualization, Ș.-S.B., A.-E.L., M.-A.P., C.-J.S. methodology, Ș.-S.B., K.G., H.S., C.L.A.; software, O.C.; validation, A.-E.L., M.-A.P., L.Ș.; formal analysis, Ș.-S.B., A.-E.L., S.K.; investigation, L.S, G.O.; resources, Ș.-S.B., C.L.A., C.-J.S.; data curation, O.C.; writing—original draft preparation, A.-E.L., Ș.-S.B., M.-A.P.; writing—review and editing, M.-A.P., Ș.-S.B., C.L.A., C.-J.S.; visualization, G.O.; supervision, Ș.-S.B., C.L.A., C.-J.S.; project administration, C.-J.S.; funding acquisition, Ș.-S.B. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the European Union’s Horizon 2020 research and innovation program under grant agreement No. 769807. The authors would like to acknowledge the research effort of all vCARE colleagues, as well as the European Commission for providing the funding framework.

Institutional Review Board Statement

The study was conducted in accordance with the Declaration of Helsinki and approved by the Ethics Committee of Carol Davila University of Medicine and Pharmacy, Bucharest, Romania (P0-35-F-03, no: 36288/21.12.2021 for heart failure use case and no. 9731/11.04.2022 for ischemic heart disease use case).

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

Data available upon request due to ethical restrictions. The data presented in this study are available upon request from the corresponding author. The data are not publicly available due to ethical restrictions.

Conflicts of Interest

The funders had no role in the design of the study, in the collection, analysis or interpretation of data, in the manuscript writing or in the decision of the published results.

References

  1. Townsend, N.; Kazakiewicz, D.; Wright, F.L.; Timmis, A.; Huculeci, R.; Torbica, A.; Gale, C.P.; Achenbach, S.; Weidinger, F.; Vardas, P. Epidemiology of cardiovascular disease in Europe. Nat. Rev. Cardiol. 2022, 19, 133–143. [Google Scholar] [CrossRef]
  2. Roth, G.A.; Abate, D.; Abate, K.H.; Abay, S.M.; Abbafati, C.; Abbasi, N.; Abbastabar, H.; Abd-Allah, F.; Abdela, J.; Abdelalim, A.; et al. Global, regional, and national age-sex-specific mortality for 282 causes of death in 195 countries and territories, 1980–2017: A systematic analysis for the Global Burden of Disease Study 2017; GBD 2017 Causes of Death Collaborators. Lancet 2018, 392, 1736–1788. [Google Scholar] [CrossRef] [Green Version]
  3. Timmis, A.; Townsend, N.; Gale, C.; Grobbee, R.; Maniadakis, N.; Flather, M.; Wilkins, E.; Wright, L.; Vos, R.; Bax, J.; et al. European Society of Cardiology: Cardiovascular Disease Statistics 2017. Eur. Heart J. 2018, 39, 508–579. [Google Scholar] [CrossRef] [Green Version]
  4. Busnatu, S.S.; Pană, M.-A.; Lăcraru, A.E.; Jercălău, C.-E.; Paun, N.; Caprino, M.; Gand, K.; Schlieter, H.; Kyriazakos, S.; Andrei, C.L.; et al. Patient Perception When Transitioning from Classic to Remote Assisted Cardiac Rehabilitation. Diagnostics 2022, 12, 926. [Google Scholar] [CrossRef]
  5. Visseren, F.L.J.; Mach, F.; Smulders, Y.M.; Carballo, D.; Koskinas, K.C.; Bäck, M.; Benetos, A.; Biffi, A.; Boavida, J.-M.; Capodanno, D.; et al. ESC Guidelines on cardiovascular disease prevention in clinical practice. Eur. Heart J. 2021, 42, 3227–3337. [Google Scholar] [CrossRef]
  6. Stefanakis, M.; Batalik, L.; Papathanasiou, J.; Dipla, L.; Antoniou, V.; Pepera, G. Exercise-based cardiac rehabilitation programs in the era of COVID-19: A critical review. Rev. Cardiovasc. Med. 2022, 22, 1143–1155. [Google Scholar] [CrossRef]
  7. Khera, A.; Baum, S.J.; Gluckman, T.J.; Gulati, M.; Martin, S.S.; Michos, E.D.; Navar, A.M.; Taub, P.R.; Toth, P.P.; Virani, S.S.; et al. Continuity of care and outpatient management for patients with and at high risk for cardiovascular disease during the COVID-19 pandemic: A scientific statement from the American Society for Preventive Cardiology. Am. J. Prev. Cardiol. 2020, 1, 100009. [Google Scholar] [CrossRef]
  8. Mattioli, A.V.; Puviani, M.B.; Nasi, M.; Farinetti, A. COVID-19 pandemic: The effects of quarantine on cardiovascular risk. Eur. J. Clin. Nutr. 2020, 74, 852–855. [Google Scholar] [CrossRef]
  9. Doimo, S.; Fabris, E.; Piepoli, M.; Barbati, G.; Antonini-Canterin, F.; Bernardi, G.; Maras, P.; Sinagra, G. Impact of ambulatory cardiac rehabilitation on cardiovascular outcomes: A long-term follow-up study. Eur. Heart J. 2019, 40, 678–685. [Google Scholar] [CrossRef]
  10. Ibanez, B.; James, S.; Agewall, S.; Antunes, M.J.; Bucciarelli-Ducci, C.; Bueno, H.; Caforio, A.L.P.; Crea, F.; Goudevenos, J.A.; Halvorsen, S.; et al. 2017 ESC Guidelines for the management of acute myocardial infarction in patients presenting with ST-segment elevation: The Task Force for the management of acute myocardial infarction in patients presenting with ST-segment elevation of the European Society of Cardiology (ESC). Eur. Heart J. 2018, 39, 119–177. [Google Scholar] [CrossRef] [Green Version]
  11. Thomas, R.J.; Beatty, A.; Beckie, T.M.; Brewer, L.C.; Brown, T.M.; Forman, D.E.; Franklin, B.A.; Keteyian, S.J.; Kitzman, D.W.; Regensteiner, J.G.; et al. Home-Based Cardiac Rehabilitation: A Scientific Statement from the American Association of Cardiovascular and Pulmonary Rehabilitation, the American Heart Association, and the American College of Cardiology. Circulation 2019, 140, e69–e89. [Google Scholar] [CrossRef]
  12. Kim, Y.H.; So, W.-Y. Gender differences in home-based cardiac rehabilitation of post-percutaneous coronary intervention patients. Aging Clin. Exp. Res. 2019, 31, 249–255. [Google Scholar] [CrossRef]
  13. Afilalo, J. Evaluating and Treating Frailty in Cardiac Rehabilitation. Clin. Geriatr. Med. 2019, 35, 445–457. [Google Scholar] [CrossRef]
  14. Schopfer, D.; Forman, D.E. Cardiac Rehabilitation in Older Adults. Can. J. Cardiol. 2016, 32, 1088–1096. [Google Scholar] [CrossRef]
  15. O’Doherty, A.F.; Humphreys, H.; Dawkes, S.; Cowie, A.; Hinton, S.; Brubaker, P.H.; Butler, T.; Nichols, S. How was technology been used to deliver cardiac rehabilitation during the COVID-19 pandemic? An interntional cross-sectional survey of healthcare professionals conducted by the BACPR. BMJ Open 2021, 11, e046051. [Google Scholar] [CrossRef]
  16. Scherrenberg, M.; Frederix, I.; De Sutter, J.; Dendale, P. Use of cardiac telerehabilitation during COVID-19 pandemic in Belgium. Acta Cardiol. 2021, 76, 773–776. [Google Scholar] [CrossRef]
  17. Choi, Y.-H.; Paik, N.-J. Mobile Game-based Virtual Reality Program for Upper Extremity Stroke Rehabilitation. J. Vis. Exp. 2018, 133, e56241. [Google Scholar] [CrossRef]
  18. Laver, K.E.; Lange, B.; George, S.; Deutsch, J.E.; Saposnik, G.; Crotty, M. Virtual reality for stroke rehabilitation. Cochrane Database Syst. Rev. 2017, 2018, CD008349. [Google Scholar] [CrossRef] [Green Version]
  19. Available online: https://vcare-project.eu/ (accessed on 20 November 2022).
  20. Bilbao, A.; Escobar, A.; García-Perez, L.; Navarro, G.; Quirós, R. The Minnesota living with heart failure questionnaire: Comparison of different factor structures. Health Qual. Life Outcomes 2016, 14, 23. [Google Scholar] [CrossRef] [Green Version]
  21. Wu, Y.; Levis, B.; Sun, Y.; He, C.; Krishnan, A.; Neupane, D.; Bhandari, P.M.; Negeri, Z.; Benedetti, A.; Thombs, B.D. Accuracy of the Hospital Anxiety and Depression Scale Depression subscale (HADS-D) to screen for major depression: Systematic review and individual participant data meta-analysis. BMJ 2021, 373, n972. [Google Scholar] [CrossRef]
  22. Pomerleau, C.S.; Carton, S.M.; Lutzke, M.L.; Flessland, K.A.; Pomerleau, O.F. Reliability of the fagerstrom tolerance questionnaire and the fagerstrom test for nicotine dependence. Addict. Behav. 1994, 19, 33–39. [Google Scholar] [CrossRef] [Green Version]
  23. Feng, Y.-S.; Kohlmann, T.; Janssen, M.F.; Buchholz, I. Psychometric properties of the EQ-5D-5L: A systematic review of the literature. Qual. Life Res. 2020, 30, 647–673. [Google Scholar] [CrossRef]
  24. Feng, Y.; Parkin, D.; Devlin, N.J. Assessing the performance of the EQ-VAS in the NHS PROMs programme. Qual. Life Res. 2014, 23, 977–989. [Google Scholar] [CrossRef] [Green Version]
  25. Rauschenberger, M.; Schrepp, M.; Perez-Cota, M.; Olschner, S.; Thomaschewski, J. Efficient Measurement of the User Experience of Interactive Products. How to use the User Experience Questionnaire (UEQ). Example: Spanish Language Version. Int. J. Interact. Multimedia Artif. Intell. 2013, 2, 39. [Google Scholar] [CrossRef]
  26. Lewis, J.R. The System Usability Scale: Past, Present, and Future. Int. J. Hum. Comput. Interact. 2018, 34, 577–590. [Google Scholar] [CrossRef]
  27. Pai, F.-Y.; Huang, K.-I. Applying the Technology Acceptance Model to the introduction of healthcare information systems. Technol. Forecast. Soc. Chang. 2011, 78, 650–660. [Google Scholar] [CrossRef]
  28. Hansen, D.; Dendale, P.; Coninx, K.; Vanhees, L.; Piepoli, M.F.; Niebauer, J.; Cornelissen, V.; Pedretti, R.; Geurts, E.; Ruiz, G.R.; et al. The European Association of Preventive Cardiology Exercise Prescription in Everyday Practice and Rehabilitative Training (EXPERT) tool: A digital training and decision support system for optimized exercise prescription in cardiovascular disease. Concept, definitions and construction methodology. Eur. J. Prev. Cardiol. 2017, 24, 1017–1031. [Google Scholar] [CrossRef]
  29. Winnige, P.; Filakova, K.; Hnatiak, J.; Dosbaba, F.; Bocek, O.; Pepera, G.; Papathanasiou, J.; Batalik, L.; Grace, S.L. Validity and Reliability of the Cardiac Rehabilitation Barriers Scale in the Czech Republic (CRBS-CZE): Determination of Key Barriers in East-Central Europe. Int. J. Environ. Res. Public Health 2021, 18, 13113. [Google Scholar] [CrossRef]
  30. Chen, Y.W.; Wang, C.Y.; Lai, Y.H.; Liao, Y.C.; Wen, Y.K.; Chang, S.T.; Huang, J.L.; Wu, T.J. Home-based cardiac rehabilitation improves quality of life, aerobic capacity, and readmission rates in patients with chronic heart failure. Medicine 2018, 97, e9629. [Google Scholar] [CrossRef]
  31. Casas, J.; Senft, E.; Gutiérrez, L.F.; Rincón-Rocancio, M.; Múnera, M.; Belpaeme, T.; Cifuentes, C.A. Social Assistive Robots: Assessing the Impact of a Training Assistant Robot in Cardiac Rehabilitation. Int. J. Soc. Robot. 2020, 13, 1189–1203. [Google Scholar] [CrossRef]
  32. Astley, C.M.; Clarke, R.A.; Cartledge, S.; Beleigoli, A.; Du, H.; Gallagher, C.; Millington, S.; Hendriks, J.M. Remote cardiac rehabilitation services and the digital divide: Implications for elderly populations during the COVID19 pandemic. Eur. J. Cardiovasc. Nurs. 2021, 20, 521–523. [Google Scholar] [CrossRef]
  33. Robinson, H.; Macdonald, B.; Broadbent, E. The Role of Healthcare Robots for Older People at Home: A Review. Int. J. Soc. Robot. 2014, 6, 575–591. [Google Scholar] [CrossRef]
  34. Schacksen, C.S.; Henneberg, N.C.; Muthulingam, J.A.; Morimoto, Y.; Sawa, R.; Saitoh, M.; Morisawa, T.; Kagiyama, N.; Takahashi, T.; Kasai, T.; et al. Effects of Telerehabilitation Interventions on Heart Failure Management (2015-2020): Scoping Review. JMIR Rehabil. Assist. Technol. 2021, 8, e29714. [Google Scholar] [CrossRef]
  35. Owen, O.; O’Carroll, V. The effectiveness of cardiac telerehabilitation in comparison to centre-based cardiac rehabilitation programmes: A literature review. J. Telemed. Telecare 2022. [Google Scholar] [CrossRef]
  36. Dias, J.F.; Oliveira, V.C.; Borges, P.R.T.; Dutra, F.C.M.S.; Mancini, M.C.; Kirkwood, R.N.; Resende, R.A.; Sampaio, R.F. Effectiveness of exercises by telerehabilitation on pain, physical function and quality of life in people with physical disabilities: A systematic review of randomised controlled trials with GRADE recommendations. Br. J. Sports Med. 2020, 55, 155–162. [Google Scholar] [CrossRef]
  37. Cordeiro, A.L.L.; Miranda, A.D.S.; de Almeida, H.M.; Santos, P. Quality of Life in Patients with Heart Failure Assisted by Telerehabilitation: A Systematic Review and Meta-Analysis. Int. J. Telerehabilitation 2022, 14, e6456. [Google Scholar] [CrossRef]
  38. Scherrenberg, M.; Wilhelm, M.; Hansen, D.; Völler, H.; Cornelissen, V.; Frederix, I.; Kemps, H.; Dendale, P. The future is now: A call for action for cardiac telerehabilitation in the COVID-19 pandemic from the secondary prevention and rehabilitation section of the European Association of Preventive Cardiology. Eur. J. Prev. Cardiol. 2021, 28, 524–540. [Google Scholar] [CrossRef]
  39. Bravo-Escobar, R.; González-Represas, A.; Gómez-González, A.M.; Montiel-Trujillo, A.; Aguilar-Jimenez, R.; Carrasco-Ruíz, R.; Salinas-Sánchez, P. Effectiveness and safety of a home-based cardiac rehabilitation programme of mixed surveillance in patients with ischemic heart disease at moderate cardiovascular risk: A randomised, controlled clinical trial. BMC Cardiovasc. Disord. 2017, 17, 66. [Google Scholar] [CrossRef] [Green Version]
  40. Spindler, H.; Leerskov, K.; Joensson, K.; Nielsen, G.; Andreasen, J.J.; Dinesen, B. Conventional Rehabilitation Therapy Versus Telerehabilitation in Cardiac Patients: A Comparison of Motivation, Psychological Distress, and Quality of Life. Int. J. Environ. Res. Public Health 2019, 16, 512. [Google Scholar] [CrossRef] [Green Version]
Ijerph 20 03937 g001 550
Figure 1. Values of VO2max pre- and post-intervention. VO2max = maximal oxygen consumption by the body (measured in mL/kg/min); EG = experimental group; AG = ambulatory group; CG = control group; T0 = before the rehabilitation period; T1 = after the rehabilitation period.
Figure 1. Values of VO2max pre- and post-intervention. VO2max = maximal oxygen consumption by the body (measured in mL/kg/min); EG = experimental group; AG = ambulatory group; CG = control group; T0 = before the rehabilitation period; T1 = after the rehabilitation period.
Ijerph 20 03937 g001
Ijerph 20 03937 g002 550
Figure 2. LDL cholesterol values in the heart failure study group. EG = experimental group; AG = ambulatory group; CG = control group; T0 = before the rehabilitation period; T1 = after the rehabilitation period.
Figure 2. LDL cholesterol values in the heart failure study group. EG = experimental group; AG = ambulatory group; CG = control group; T0 = before the rehabilitation period; T1 = after the rehabilitation period.
Ijerph 20 03937 g002
Ijerph 20 03937 g003 550
Figure 3. Minnesota questionnaire results. MLFQH = Minnesota living with heart failure questionnaire; EG = experimental group; AG = ambulatory group; CG = control group; T0 = before the rehabilitation period; T1 = after the rehabilitation period.
Figure 3. Minnesota questionnaire results. MLFQH = Minnesota living with heart failure questionnaire; EG = experimental group; AG = ambulatory group; CG = control group; T0 = before the rehabilitation period; T1 = after the rehabilitation period.
Ijerph 20 03937 g003
Ijerph 20 03937 g004 550
Figure 4. HAD scale results for HF EG and CG at T0 and T1. (a) HAD scale EG. (b) HAD scale CG. HAD = hospital anxiety and depression scale; HF= heart failure; EG = experimental group; CG = control group; T0 = before the rehabilitation period; T1 = after the rehabilitation period.
Figure 4. HAD scale results for HF EG and CG at T0 and T1. (a) HAD scale EG. (b) HAD scale CG. HAD = hospital anxiety and depression scale; HF= heart failure; EG = experimental group; CG = control group; T0 = before the rehabilitation period; T1 = after the rehabilitation period.
Ijerph 20 03937 g004
Ijerph 20 03937 g005 550
Figure 5. HAD scale results for AG at T0 and T1. HAD = hospital anxiety and depression scale; AG = control group; T0 = before the rehabilitation period; T1 = after the rehabilitation period.
Figure 5. HAD scale results for AG at T0 and T1. HAD = hospital anxiety and depression scale; AG = control group; T0 = before the rehabilitation period; T1 = after the rehabilitation period.
Ijerph 20 03937 g005
Ijerph 20 03937 g006 550
Figure 6. Smoking status of heart failure patients. HF = heart failure; AG = ambulatory group; EG = experimental group; CG = control group; T0 = before the rehabilitation period; T1 = after the rehabilitation period.
Figure 6. Smoking status of heart failure patients. HF = heart failure; AG = ambulatory group; EG = experimental group; CG = control group; T0 = before the rehabilitation period; T1 = after the rehabilitation period.
Ijerph 20 03937 g006
Ijerph 20 03937 g007 550
Figure 7. VO2max pre- and post-intervention. VO2max = maximal oxygen consumption by the body (measured in mL/kg/min); EG = experimental group; CG = control group; T0 = before the rehabilitation period; T1 = after the rehabilitation period.
Figure 7. VO2max pre- and post-intervention. VO2max = maximal oxygen consumption by the body (measured in mL/kg/min); EG = experimental group; CG = control group; T0 = before the rehabilitation period; T1 = after the rehabilitation period.
Ijerph 20 03937 g007
Ijerph 20 03937 g008 550
Figure 8. LDL-cholesterol values in the ischemic heart disease study group. EG = experimental group; CG = control group; T0 = before the rehabilitation period; T1 = after the rehabilitation period.
Figure 8. LDL-cholesterol values in the ischemic heart disease study group. EG = experimental group; CG = control group; T0 = before the rehabilitation period; T1 = after the rehabilitation period.
Ijerph 20 03937 g008
Ijerph 20 03937 g009 550
Figure 9. HAD scale results for IHD EG and CG at T0 and T1. (a) HAD scale EG. (b) HAD scale CG. HAD = hospital anxiety and depression scale; IHD = ischemic heart disease; EG = experimental group; CG = control group; T0 = before the rehabilitation period; T1 = after the rehabilitation period.
Figure 9. HAD scale results for IHD EG and CG at T0 and T1. (a) HAD scale EG. (b) HAD scale CG. HAD = hospital anxiety and depression scale; IHD = ischemic heart disease; EG = experimental group; CG = control group; T0 = before the rehabilitation period; T1 = after the rehabilitation period.
Ijerph 20 03937 g009
Ijerph 20 03937 g010 550
Figure 10. Smoking status of IHD patients. IHD = ischemic heart disease; EG = experimental group; CG = control group; T0 = before the rehabilitation period; T1 = after the rehabilitation period.
Figure 10. Smoking status of IHD patients. IHD = ischemic heart disease; EG = experimental group; CG = control group; T0 = before the rehabilitation period; T1 = after the rehabilitation period.
Ijerph 20 03937 g010
Ijerph 20 03937 g011a 550Ijerph 20 03937 g011b 550
Figure 11. EuroQol-5D results parameters for the heart failure study groups. (a) Quality of life for HF EG group. (b) Quality of life for HF AG group. (c) Quality of life for HF CG group.
Figure 11. EuroQol-5D results parameters for the heart failure study groups. (a) Quality of life for HF EG group. (b) Quality of life for HF AG group. (c) Quality of life for HF CG group.
Ijerph 20 03937 g011aIjerph 20 03937 g011b
Ijerph 20 03937 g012 550
Figure 12. EQ-VAS results for the heart failure study group.
Figure 12. EQ-VAS results for the heart failure study group.
Ijerph 20 03937 g012
Ijerph 20 03937 g013a 550Ijerph 20 03937 g013b 550
Figure 13. EuroQol-5D results parameters for the ischemic heart disease study group. (a) Quality of life for IHD EG. (b) Quality of life for IHD CG.
Figure 13. EuroQol-5D results parameters for the ischemic heart disease study group. (a) Quality of life for IHD EG. (b) Quality of life for IHD CG.
Ijerph 20 03937 g013aIjerph 20 03937 g013b
Ijerph 20 03937 g014 550
Figure 14. EQ-VAS results for the ischemic heart disease study group.
Figure 14. EQ-VAS results for the ischemic heart disease study group.
Ijerph 20 03937 g014
Table
Table 1. Inclusion and exclusion criteria.
Table 1. Inclusion and exclusion criteria.
Inclusion CriteriaExclusion Criteria
  • Age > 50 years old
  • Unstable condition requiring treatment
  • Heart failure class NYHA II-III
  • Unstable angina
  • History of myocardial infarction
  • Uncontrolled sustained arrhythmias
  • History of unstable/stable angina pectoris
  • Severe uncontrolled arterial hypertension
  • History of percutaneous coronary intervention
  • Active myo-/peri-/endocarditis
  • History of coronary artery by-pass grafting
  • Recent pulmonary embolism
  • History of heart failure and/or ischemic heart disease therapy
  • Inability to understand and comply with protocol and/or give informed consent
Table
Table 2. Questionnaires used for the psychological evaluation of enrolled patients.
Table 2. Questionnaires used for the psychological evaluation of enrolled patients.
Minnesota Living with Heart FailureHADS Scale (Anxiety and in-Hospital Depression)Fagerstrom Test for Nicotine DependenceEuroQol-5D (EQ5D)Health Self-Evaluation Scale (EQ-VAS)
a self-administered, 21-item disease-specific instrument which assesses the quality of life among patients with heart failure; used only for HF use case [20]an assessment tool consisting of a 14-item measure designed to assess anxiety and depression symptoms in medical patients, with an emphasis on reducing the impact of physical illness on the total score [21]a standard assessment tool for the intensity of physical addiction to nicotine; its purpose is to provide an ordinal measure of nicotine dependence related to cigarette smoking [22]a standard assessment quality of life questionnaire which has five dimensions and a score range from zero (no problems) to four (inability to walk, inability to perform daily activities, extreme pain, or extreme anxiety/depression), or related to their perceived health from zero to one hundred percent, with zero representing the worst possible health and one hundred percent the best possible [23]a standard self-evaluation scale of a patient’s health, with two endpoints of‚ “The best health you can imagine’’ and‚ “The worst health you can imagine’’; it is used to reflect the patient’s judgement [24]
Table
Table 3. List of the equipment used in HF and IHD use cases.
Table 3. List of the equipment used in HF and IHD use cases.
DeviceModel
  • Wristband
  • XIAOMI Mi Band 4
  • Weight scale
  • XIAOMI weight scale
  • Blood pressure device
  • Beurer BM85
  • Camera
  • Astra Orbbec camera
  • Software license-camera
  • Nuitrack software version v.0.36.7
  • Tablet
  • Lenovo Tab M10 Full HD Plus
  • Television (TV)
  • Owned by the subject
  • Set top box
  • Android TV BOX X99 4k Ultra HD
Table
Table 4. Monitoring parameters of the devices used.
Table 4. Monitoring parameters of the devices used.
DeviceParameters
  • Wristband
  • Heart rate and number of steps
  • Weight scale
  • Weight
  • Blood pressure device
  • Blood pressure
  • Camera
  • Motion recognition
  • Tablet
  • Interaction with the patient
  • Television (TV)
  • Running of the serious games
  • Set top box
  • Ultra-modern personal computer with component integration role
Table
Table 5. Questionnaires used for the usability perception of the vCare experience.
Table 5. Questionnaires used for the usability perception of the vCare experience.
User Experience Questionnaire (UEQ)System Usability Scale (SUS)Technology Acceptance Model (TAM)
was administered to measure classical usability aspects and user experience aspects. It is a questionnaire composed of 26 items built as pairs of contrasting attributes [25]is a questionnaire that consists of 10 items, with five response options for each item (from “strongly disagree” to “strongly agree”), which allows the subjective evaluation of the usability of the system under examination after the direct interaction of the user with the system [26]is the most popular model among those proposed to explain and predict the acceptance of a system [27]
Table
Table 6. Components of the virtual cardiac rehabilitation program.
Table 6. Components of the virtual cardiac rehabilitation program.
E-learningAerobic Physical ActivityResistance TrainingMedication Intake SupportVital Stats ControlSmoking Cessation ActivityAnxiety and Depression ReductionAlcohol Reduction
Medical educationDaily number of stepsStrengh training with serious gamesInteraction confirming the administration of pharmacological therapyVital parameters monitoringAssessment of the number of cigarettes consumedAssessment of anxiety and depression statusAssessment of the amount of alcohol consumed
Table
Table 7. vCare steps parameter and active weeks for the HF subjects.
Table 7. vCare steps parameter and active weeks for the HF subjects.
Active DaysAdherenceAverage Steps per Active DaysActive WeeksAdherenceAverage Accesses per Active Weeks
Patient138%211472%3
Patient2730%1467391%2
Patient42225%86321079%6
Patient512%704232%5
Patient676%52511380%5
Patient734%524331%2
Patient8310%474493%3
Patient93538%25451493%10
Patient102023%78631380%5
mean10.116%24766.671%4
std120.129934.90.23
Table
Table 8. vCare steps parameter and active weeks for the IHD subjects.
Table 8. vCare steps parameter and active weeks for the IHD subjects.
Active DaysAdherenceAverage Steps per Active DaysActive WeeksAdherenceAverage Accesses per Active Weeks
Patient114%514384%5
Patient2313%3574384%5
Patient436%1093431%2
Patient58391%420815100%13
Patient63134%40491185%2
Patient7922%14516100%5
Patient83033%4860573%9
Patient91227%3000382%7
Patient102130%3930440%4
mean19.326%26686.767.9%5.2
std29.90.315794.60.24
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Lăcraru, A.-E.; Busnatu, Ș.-S.; Pană, M.-A.; Olteanu, G.; Șerbănoiu, L.; Gand, K.; Schlieter, H.; Kyriazakos, S.; Ceban, O.; Andrei, C.L.; et al. Assessing the Efficacy of a Virtual Assistant in the Remote Cardiac Rehabilitation of Heart Failure and Ischemic Heart Disease Patients: Case-Control Study of Romanian Adult Patients. Int. J. Environ. Res. Public Health 2023, 20, 3937. https://doi.org/10.3390/ijerph20053937

AMA Style

Lăcraru A-E, Busnatu Ș-S, Pană M-A, Olteanu G, Șerbănoiu L, Gand K, Schlieter H, Kyriazakos S, Ceban O, Andrei CL, et al. Assessing the Efficacy of a Virtual Assistant in the Remote Cardiac Rehabilitation of Heart Failure and Ischemic Heart Disease Patients: Case-Control Study of Romanian Adult Patients. International Journal of Environmental Research and Public Health. 2023; 20(5):3937. https://doi.org/10.3390/ijerph20053937

Chicago/Turabian Style

Lăcraru, Andreea-Elena, Ștefan-Sebastian Busnatu, Maria-Alexandra Pană, Gabriel Olteanu, Liviu Șerbănoiu, Kai Gand, Hannes Schlieter, Sofoklis Kyriazakos, Octavian Ceban, Cătălina Liliana Andrei, and et al. 2023. "Assessing the Efficacy of a Virtual Assistant in the Remote Cardiac Rehabilitation of Heart Failure and Ischemic Heart Disease Patients: Case-Control Study of Romanian Adult Patients" International Journal of Environmental Research and Public Health 20, no. 5: 3937. https://doi.org/10.3390/ijerph20053937

APA Style

Lăcraru, A.-E., Busnatu, Ș.-S., Pană, M.-A., Olteanu, G., Șerbănoiu, L., Gand, K., Schlieter, H., Kyriazakos, S., Ceban, O., Andrei, C. L., & Sinescu, C.-J. (2023). Assessing the Efficacy of a Virtual Assistant in the Remote Cardiac Rehabilitation of Heart Failure and Ischemic Heart Disease Patients: Case-Control Study of Romanian Adult Patients. International Journal of Environmental Research and Public Health, 20(5), 3937. https://doi.org/10.3390/ijerph20053937

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop