Introduction

Heart failure (HF) is a common health problem in developed countries worldwide [1,2]. HF is considered to be a medical diagnosis, and there are often complications related to this diagnosis in terms of patient health problems that are of concern to nurses, also referred to as ‘nursing diagnoses’ or ‘related health problems’. Patients with heart failure usually experience reduced physical activity tolerance, as well as symptoms such as fatigue and shortness of breath (dyspnoea) that may lead to an excessive amount of physical inactivity and resultant physical deconditioning. Despite the positive effect, physical activity is known to have on the risk factors and symptoms of HF, the majority of HF patients are physically inactive [3]. Consequently, Sedentary Lifestyle and Activity Intolerance are common nursing diagnoses for people with HF [4,5]. They are characterised by a preference for daily activities without physical effort, which in turn results in diminished physical wellbeing and health status [5-10]. The impact of technology on healthcare has been enormous, and new devices are constantly being developed to assist people in measuring their own health. Wearables devices such as activity trackers (ATs) are being used by an increasing number of people, and they appear to contribute to health improvements in patients with a sedentary lifestyle [7].

Background

Park et al. (2018) [6] state in their study that health care providers play an important role in emphasising the importance of physical activity and in insisting that the physical activity of patients be assessed. Health care providers can educate patients with heart failure about the relationship between sedentary behaviour and negative health outcomes. They can also provide practical tools and interventions to promote physical activity (e.g. the use of digital technology) [6,11].

Sedentary Lifestyle is a nursing diagnosis for patients who demonstrate the following characteristics: physical deconditioning, reporting preferences for minimal physical activity, and choosing a daily routine lacking in physical exercise5. There are common related factors such as insufficient knowledge about the benefits that are associated with exercise, insufficient interest, or insufficient motivation. Common expected outcomes are written in a nursing care plan and relate to knowledge, prescribed activity, and physical fitness. The nursing care plan also provides ongoing assessments [5,12]. Nursing objectives are to assist patients to find a way to personalise their own healthy behaviour, and to advise and support patients in the process of increasing their physical activity and self-management skills (i.e. by monitoring their physical activity to ensure it is increased safely)[13,14].

Activity trackers (ATs) are small, user-friendly devices that are typically worn on the wrist. They register the user’s physical activity behaviour by measuring the number of steps users take, along with other health measures. Combined with the use of an associated mobile application, this provides the patient with insight into their own health behaviour. Examples of widely used activity trackers are the Fitbit Charge and the Garmin Vivosmart [15].

ATs are able to track and analyse data, enabling patients to monitor their own progress. Additionally, other individuals such as friends and health care providers are able to monitor and support the patient if access is permitted. In this way, the AT can be used as a tool for nurses to encourage patients to develop a healthier lifestyle, as well as to engage them in an effort to understand and improve their chronic disease [7,16,17].

This study focuses on the nursing diagnosis of ‘Sedentary Lifestyle in HF Patients’, with the aim of examining how the functions and possibilities of activity trackers in this patient category can be beneficial in the nursing process.

All of the aforementioned evidence suggests that ATs may be useful tools in all of the different steps of the nursing process. During the assessment, an AT provides the nurse and the patient with a more complete overview of the situation by providing additional objective data. This information may be useful as an input for diagnosing an inactive lifestyle and could also be helpful for formulating personalised goals when attempting to change activity behaviour. The AT can then be used as a tool both when implementing the goals and when evaluating whether the goals have been met [18].

The primary reason for undertaking this review was to test the hypothesis that the use of an AT is a simple, non-invasive way to obtain essential data about the condition of a person with cardiac disease. It was also judged that the current generation of ATs are sufficiently reliable to be recommended by a nursing professional. However, we had no adequate scientific basis for this assumption. Another central reason for undertaking this study was that if nurses do not incorporate new applications of technology into the nursing process, use of such technology cannot become part of their daily routines, and so cannot be incorporated into the training curriculum. It is precisely the examination both of statements regarding the scientific reliability of the technology involved and of the possibilities of incorporating the use of such technology into the theoretical framework of the nursing process that makes this review of practical value for both everyday nursing practice and nursing education [7,17,18].

Aim

The aim of this scoping review was to identify the functions and purposes of activity trackers that contribute to nurses’ recognition and treatment of the diagnosis of Sedentary Lifestyle in patients with heart failure, and to explore how these functions can be used in the nursing process.

The research question was: Which functions and purposes of activity trackers can contribute to the phases of the nursing process for the diagnosis of Sedentary Lifestyle?

Design

To answer the research question, a scoping review was performed using the electronic databases MEDLINE/PubMed, CINAHL, and the Cochrane library. As a theoretical framework, the NANDA classification system was employed to determine the characteristics of the nursing diagnosis of Sedentary Lifestyle [12]. The Nursing Interventions Classification (NIC) and the Nursing Outcomes Classification (NOC) [10,11] were used to describe possible interventions and patient outcomes. The description of the theoretical background of the concepts, published in the aforementioned nursing classification systems, was considered to be potentially helpful for making a sound case for the usability of activity trackers in the nursing process of HF patients.

Method

MEDLINE/PubMed, CINAHL, and the Cochrane library electronic databases were used to search for the functions and possible applications of ATs. Due to the increase in popularity of wearable sensors such as ATs over the past decade, the search period was set to include dates ranging from January 2010 to January 2020. Articles written in either English or Dutch were included. Only studies looking at populations aged 18 years or older were included. The search terms used were: activity tracker(s), activity sensor(s), fitness tracker(s), wearable(s), wearable technology, accelerometer(s), Fitbit(s), Garmin, Jawbone, Misfit, Samsung, Nike, Polar, health behaviour, sedentary lifestyle, inactive lifestyle, physical inactivity, physical activity, physical exercise(s), heart failure, myocardial failure, heart decompensation, congestive heart failure, and cardiac disease(s). Specific brands were used in the search strategy because of several validation studies in which these trackers were involved. Included in this review were studies with a Level of Evidence (LOE) of I–IV according to the Oxford levels of evidence [19]. The main subjects of the review were the potential uses of an AT when it comes to supporting HF patients with a sedentary lifestyle and supporting nurses in the nursing process involved in caring for HF patients with a sedentary lifestyle.

All studies with an LOE from I–IV were used; these included systematic reviews, studies with an experimental design (such as randomized controlled trials and quasi-controlled trials), as well as cohort and validation studies. LOE VI (expert opinions) was excluded.

This study focuses primarily on patients with HF; however, in the inclusion criteria, the term “cardiovascular disease” was also used. Included articles were required to also have specified at least which diagnostics were or could be performed with the ATs, as well as other potential specifications related to the steps in the nursing process.

The articles were assessed according to the inclusion criteria by two researchers working independently. Disagreements were discussed until a consensus was reached.

Search outcome

A total of 876 articles were identified (Figure 1). After removal of duplicates and independent screening of all titles and abstracts by two researchers, 28 studies were retrieved for full text analysis and further screening. When studies were excluded, the reasons for exclusion were noted. The most common reason for exclusion was that no relevant information was provided regarding the functions and purposes of the AT, resulting in the article not being useful for answering the research question. A full article assessment was subsequently performed on 13 studies (Figure 1).

Figure 1: Search strategy and number of articles identified.

Quality appraisal

The included articles were systematically and independently reviewed by two reviewers using the PRISMA review protocol [20]. The reviews focused on the type of study, population and sample size, data analysis, and general findings concerning the functions of the AT related to the nursing diagnosis. Additionally, the reviewers assessed the methodology of each study according to the altered guidelines provided by Cochrane, which depend on the type of study. The EQUATOR resources were used for choosing the critical appraisal instruments (see Supplementary File 1). Systematic reviews were assessed according to the guidelines of the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta Analyses) statement [20]. For single studies, for example, randomized controlled trials were assessed according to the recommendations of the CONSORT (Consolidated Standards of Reporting Trials) statement [21] The STROBE (STrengthening The Reporting of OBservational studies in Epidemiology) statement was used to assess observational and cohort studies [22]. The SRQR (Standards for Reporting Qualitative Research) were used to assess the qualitative studies [23].

Data abstraction and synthesis

Data were extracted by both independent reviewers by assessing the authors’ names and the studies’ years of publication, study type, patient group and age, sample size, name and type of the AT used, functions and possibilities of the AT used, and other relevant information. The data were used to answer the research questions related to the validity and reliability of ATs, the weaknesses of ATs, and the possibilities presented by ATs when used as part of an intervention.

Data were compared and discussed, and disagreements were resolved by consensus. The data were categorized according to a matrix, the design of which was guided by the several steps of the nursing process. In this way, for each step of the nursing process, the features and possibilities of the AT that were relevant to the nursing diagnosis of Sedentary Lifestyle were shown.

Results

Of the 13 selected articles, five were systematic reviews, three were RCT studies, two were validation studies, two were qualitative studies, and one was a cohort study. The systematic reviews are shown in (Table 1a), while the additional single studies are shown in (Table 1b).

Table 1a: Selected systematic reviews on AT and functions (n=5).

Table 1b: Selected single studies on AT and functions (n=8).

Several functions of the ATs are documented in the selected articles. The main function of all ATs is the registration of steps. Most ATs that were mentioned in the articles also measure active and sedentary time and the calories burnt during the day. The more recent ATs are also able to register heart frequency and sleep pattern, just like several types of Fitbit and Garmin.

The following functions of ATs were mentioned: data collection, monitoring/self-monitoring, feedback, assisting in goal setting, improving awareness of own behaviour, improving motivation, and providing social support due to the sharing of data.

The qualitative studies offered information regarding the usefulness of an AT in healthcare settings. An AT can be beneficial as a tool to enhance physical activity; however, it is advised to use the AT in combination with coaching to achieve better results [24-31].

In a few studies, non-consumer-based ATs such as the Actigraph, Caltrac, and ActivPal were used [26-29]. These devices are only used in laboratory or research settings.

The ATs mentioned in (Table 2) demonstrate acceptable validity for laboratory and field settings (ICC of .90 or higher and 96% CI of .83 and higher).

In (Table 2), the functions and purposes of ATs are shown and related to the steps of the nursing process for the nursing diagnosis of Sedentary Lifestyle. The nursing process functions as a systematic guide to client-centered care, with five sequential steps. These are assessment, diagnosis, planning of outcomes, implementation of interventions, and evaluation.

Table 2: Functions of AT related to the nursing diagnosis Sedentary Lifestyle following NANDA-NIC-NOC and the nursing.

Table 2 shows the functions of ATs and in which step of the nursing process they can contribute to the diagnosis and treatment of a sedentary lifestyle. The gathering of objective data can raise clients’ awareness regarding their own physical activity patterns [32]. Gualtieri et al. (2016) [27] reported that participants did not expect their physical activity patterns to be as low as they were. For the participants, this realisation provided extra motivation to be more physically active.

When a sedentary lifestyle is diagnosed, an AT can help in setting individual goals. The increased awareness that clients gain from using the AT in combination with motivation or support can help them to achieve their goals [26,33].

All selected articles stated that an AT can play an important role in this context. The client can monitor physical activity levels; they can take initiative to achieve their goals once they see that those goals have not yet been met. Additionally, participants reported that they felt safer being physically active because their heart rates were being measured [32]. Having such data also provides health professionals with feedback about their clients, allowing them to provide better individual coaching on the basis of their assessments [25].

Discussion

Wearable technology is making a move toward tracking physical activity in a more adequate way while providing extra monitoring functions for the user [26].

Although the literature shows accurate counting of steps in activity trackers like Fitbit, Jawbone, Withings, and Garmin with ICC’s of .90 and higher in an experimental setting such as in field settings [34], validity and reliability are dependent on walking speed [35]. Step counts were slightly underestimated at slower walking speeds, while free-living circumstances and accuracy improved at higher walking speeds [36,38-40]. Despite apparent underestimations of indicators such as heart rate frequency and energy expenditure compared to laboratory measures, based on the literature we can conclude that measurements can be estimated in a manner that is safe, accurate and useful in the nursing process, helping nurses support patients with heart failure and a sedentary lifestyle.

The implementation of wearables requires nurses’ engagement. Therefore, knowledge and skills are needed. Nurses should be educated regarding the circumstances in which wearables can be useful in the nursing process and what they might add for both the patient and the health professional.

Nursing students are already engaging with wearable technology to gain an understanding of patients’ conditions[36,37,40]. However, the attitude of manufacturers towards developing wearables for nursing care is also important. It is essential that nurses are involved in the development and testing of wearables so that they will have confidence in the applicability of this new technology and the usefulness of the data that is aggregated [36-41].

Examining the possibilities presented by ATs in the nursing process for the nursing diagnosis of Sedentary Lifestyle, as well as the effects ATs tend to have on activity levels, the use of ATs appears to be a promising nursing intervention and thus should be part of the Nursing Intervention Classification. There is also existing evidence that ATs may contribute to the improved health of other patient groups, so the use of ATs should not only focus on patients with heart failure. Therefore, the usefulness of these devices to other patient groups needs to be explored in more depth.

For ATs to become part of the nursing process, it essential that they become part of evidence-based protocols; guidelines are needed to arrive at efficient and accurate interventions on the basis of accurate assessments.

Another important subject is the need for better compatibility of the data extracted by ATs with other systems, such as electronic patient record systems. Interdisciplinary coordination of care related to lifestyle interventions can lead to better involvement of patients and their family members in shared decision-making processes [37].

Considering the heterogeneous nature of the studies included in this review, the findings must be interpreted with caution. This study included research outcomes based on different levels of evidence. In addition to systematic reviews, RCTs, cohort studies, validation studies, and qualitative studies were also included. Although some of these studies have lower levels of evidence, most of them provide beneficial information about the strengths and weaknesses of the functions of ATs in health care settings and so can be used when considering practical questions regarding where and how to use ATs in the nursing process.

Most studies used consumer-based ATs such as Fitbit and Polar. However, non-consumer-based ATs (ActiGraph) or step counters (Yamax) were also sometimes used. These last two types afford fewer possibilities related to their usefulness in the nursing process. They are more beneficial in experimental settings; furthermore, as a step counter, Yamax lacks functions like monitoring and distance support in comparison to more recently developed activity trackers.

We considered making concrete general recommendations for the choice of certain ATs in nursing practice. A concrete choice may eventually have to be made by the patients themselves in coordination. Based on the data gathered from this review, either Fitbit Charge HR or Polar Loop could be considered in the nurse's advice to the patient. Nevertheless, personal preferences related to wearing comfort or compatibility with other systems can play a role in the final decision and must be taken into consideration as well.

Conclusion

Results show that ATs may be a promising addition to the nursing process. The authors’ findings indicate useful functions of ATs in every step in the nursing process for assessing and enhancing the physical activity patterns of heart failure patients. Using ATs, nurses are equipped with a tool to deliver tailored treatment to patients. For ATs to be an effective tool in treating patients and enhancing their capacity for self-management, nurses should be involved in implementing ATs in standard patient care.

Relevance to clinical practice

Science and the publication of articles are always behind the times due to the fast innovation involved in the development of wearables related to healthcare. Therefore, the most recent studies may not be included in the current study. It can be stated that the studies included in this review offer generally acceptable, reliable, and valid data. However, the studies do not always fully describe how their results were obtained. They also frequently examine a “healthy context” (i.e. one in which measurements were made of relatively vital target groups). It is recommended that studies include vulnerable groups along with other, more heterogeneous caloric, conditional backgrounds in this type of reliability study as well, and that studies state more precisely how their sample was selected.

This could lead to adjustments of more defined algorithms based on which the current generation of ATs function. This could usher in a new generation of ATs that are more precisely tailored to users’ backgrounds.

It is suggested that further research also include other measurements that can be made by ATs, such as measurements of sleep patterns and heart rate. Furthermore, pilot studies should be conducted in which ATs are used as part of an intervention (i.e., with patients using an AT in their treatment). It is important to investigate the attitude of patients towards the use of ATs in their treatment and daily life. Nurses should be involved from the beginning because they play a key role in supporting patients by providing instructions, support, and interventions.

References

1. Go AS, Mozaffarian D, Roger VL, Benjamin EJ, Berry JD, et al. (2013) On behalf of the American Heart Association Statistics Committee and Stroke Statistics Subcommittee. Heart disease and stroke statistics, 2013 update: a report from the American Heart Association. Circulation 127: e6-e245.
2. Ponikowski P, Anker SD, AlHabib KF, Cowie MR, Force TL, et al. (2014) Heart failure: preventing disease and death worldwide. ESC Heart Failure 1: 4-25.
3. Hansen BH, Kolle E, Dyrstad SM, Holme I, Anderssen SA (2012) Accelerometer-determined physical activity in adults and older people. Med Sci Sports Exerc 44: 266-272.
4. Park H (2013) Identifying Core NANDA‐I Nursing Diagnoses, NIC Interventions, NOC Outcomes, and NNN Linkages for Heart Failure. Int J Nur knowl 25: 30-38.
5. Park H, Tucker DA (2017) Capturing Key NANDA-I Nursing Diagnoses. From Actual Clinical Data for Patients with Heart Failure. Int J Nurs Knowl 28: 30-36.
6. French DP, Olander EK, Chisholm A, McSharry J (2014) Which behaviour change techniques are most effective at increasing older adults' self-efficacy and physical activity behaviour? A systematic review. Ann Behav Med 48: 225-234.
7. Wevers C, Gijsbers G (2016) TNO Nederlandse Organisatie voor Toegepast Natuurwetenschappelijk Onderzoek); Innoveren voor gezondheid. / TNO Dutch Organization for Applied Scientific Research Innovation for Health, TNO.
8. Stamp K, Prasun M, Lee CS, Jaarsma T, Piano M (2018) Nursing research in heart failure care: a position statement of the American association of heart failure nurses (AAHFN). Heart Lung 47: 169-175.
9. Linhares JCC, Orlandin L, Aliti GB, Rabelo-Silva ER (2016) Applicability of nursing outcomes in patients with heart failure and fluid volume excessive. Rev Gaúcha Enferm 37: e61554.
10. Azolin K, Mussi CM, Ruschel KB, Nogueira Souza E, Lucena AF (2013) Effectiveness of nursing interventions in heart failure patients in home care using NANDA-I, NIC, and NOC. Appl Nurs Res 26: 239-244.
11. Souza Carneiro de C, Dias de Oliveira AP, Lima Lopes de J, Bachion MM, Herdman TH, et al. (2015) Outpatient Clinic for Health Education: Contribution to Self-management and Self-care for People with Heart Failure. Int J Nurs Knowl 27: 49-55.
12. Herdman H, Kamitsuru S (2020) NANDA International Nursing Diagnoses: Definitions & Classification, 2018-2020, NANDA International, 11th edn, Thieme.
13. Bots ML, Buddeke J, Dis I, van Vaartjes I, Visseren FLJ (2015) Nederlandse hartstichting. Hart- en vaatziekten in Nederland 2015. / Dutch Heart Foundation. ‘Cardiovascular diseases in the Netherlands. 2020.
14. Lee CS, Vellone E, Lyons KS, Cocchieri A, Bidwell JT (2015) Patterns and predictors of patient and caregiver engagement in heart failure care: A multi-level dyadic study. Int J Nur Stud 52: 588-597.
15. Henriksen A, Haugen Mikalsen M, Woldaregay AZ, Muzny M, Hartvigsen G, et al. (2018) Using Fitness Trackers and Smartwatches to Measure Physical Activity in Research: Analysis of Consumer Wrist-Worn Wearables J Med Internet Res 20: e110.
16. Milani RV, Bober RM, Lavie CJ (2016) The Role of Technology in Chronic Disease Care. Prog Cardiovasc Dis 58: 579-583.
17. Ackley BJ, Ladwig GB (2019)Nursing diagnosis handbook: An evidence-based guide to planning care (11th. ed.). St. Louis: Mosby/Elsevier.
18. Zhu X, Cahan A (2016) Wearable Technologies and Telehealth in Care Management for Chronic Illness. Healthcare Information Management Systems. Health Informatics. Springer,Cham.
19. Howick J, Chalmers I, Glasziou P, Greenhalgh T, Heneghan C, et al. (2011)Explanation of the 2011 Oxford Centre for Evidence-Based Medicine (OCEBM) Levels of Evidence (Background Document). Oxford Centre for Evidence-Based Medicine.
20. Moher D, Shamseer L, Clarke M, Ghersi D, Liberati A, et al. (2015) Preferred reporting items for systematic review and meta-analysis protocols (PRISMA-P) 2015 statement. Syst Rev 4:1.
21. Schulz KF, Altman DG, Moher D (2010) CONSORT 2010 statement: updated guidelines for reporting parallel group randomised trials. BMC medicine 8: 18.
22. Elm EV, Altman DG, Egger M, Pocock SJ, Gotzsche PC, et al. (2008) The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) Statement: guidelines for reporting observational studies. J Clin Epidemiol 61: 344-349.
23. O’Brien BC, Harris IB, BeckmanTJ, Reed DA, CookDA (2014) Standards for Reporting Qualitative Research: a synthesis of recommendations. Acad Med 89: 1245-1251.
24. Mercer K, Giangregorio L, Schneiders E, Chilana P, Li M, et al. (2016) Acceptance of commercially available wearable among adults aged over 50 and with chronic illness: A mixed-methods evaluation. JMIR Mhealth Uhealth 4: e7.
25. Vogel J, Auinger A, Riedl R, Kindermann H, Helfert M, et al. (2017) Digitally enhanced recovery: Investigating the use of digital self-tracking for monitoring leisure time physical activity of cardiovascular disease (CVD) patients undergoing cardiac rehabilitation. PloS one 12: e0186261.
26. Kirk MA, Amiri M, Pirbaglou M, Ritvo P (2019) Wearable Technology and Physical Activity Behavior Change in Adults with Chronic Cardiometabolic Disease: A Systematic Review and Meta-Analysis. Am J Health Promot 33: 778-791.
27. Gualtieri L, Rosenbluth S, Phillips J (2016) Can a free wearable activity tracker change behaviour? The impact of trackers on adults in a physician-led wellness group. JMIR Res protoc 5: e237.
28. Allet L, Knols RH, Shirato K, Bruin ED (2010) Wearable systems for monitoring mobility-related activities in chronic disease: a systematic review. Sensors(Basel) 10: 9026-9052.
29. Gal R, May AM, Overmeeren EJ.van, Simons M, Monninkhof EM (2018) The effect of physical activity interventions comprising wearables and smartphone applications on physical activity: a systematic review and meta-analysis. Sports Medicine 4: 42-43.
30. Jefferis BJ, Sartini C, Lee IM, Choi M, Amuzu A, et al. (2014) Adherence to physical activity guidelines in older adults, using objectively measured physical activity in a population-based study. BMC public health 14-1: 382.
31. Tudor-Locke C, Craig CL, Brown W, Clemes S, De Cocker K (2014) How many steps are enough? For adults. The international journal of behavioural nutrition and physical activity 8: 79.
32. Deka P, Pozehl B, Williams MA, Norman JF, Khazanchi D, et al. (2019) MOVE-HF: an internet-based pilot study to improve adherence to exercise in patients with heart failure. Eur J Cardiovasc Nurs 18: 122-131.
33. Sanders JP, Loveday A, Pearson N, Edwardson C, Yates T, et al. (2016) Devices for self-monitoring sedentary time or physical activity: a scoping review. J Med Internet Res 18: e90.
34. Kooiman TJM, Dontje ML, Sprenger SR, Krijnen WP, Schans Van der CP, et al. (2015) Reliability and validity of ten consumer activity trackers. BMC Sports Sci Med Rehabil 7: 24.
35. Fokkema T, Kooiman TJM, Krijnen WP, Schans van der CP, Groot de M (2017) Reliability and Validity of Ten Consumer Activity Trackers Depend on Walking Speed, Med Sci Sports Exerc 49: 793-800.
36. Bunn JA, Navalta JW, Fountaine CJ, Reece JD (2018) Current state of commercial wearable technology in physical activity monitoring 2015–2017. Int J Exerc Sci 11: 503-515.
37. Ngangue PA, Forgues C, Nguyen T, Gallagher F, Loignon C, et al. (2020) Patients, caregivers and health‐care professionals’ experience with an interdisciplinary intervention for people with multimorbidity in primary care: A qualitative study. Health Expect 23: 318-327.
38. Cupples M, Dean A, Tully MA, Taggart M, McCorkell G, et al. (2013) Using pedometer step-count goals to promote physical activity in cardiac rehabilitation: a feasibility study of a controlled trial. Int J Phys Med Rehabil 1: 157.
39. Thorup C, Hansen J, Grønkjær M, Andreasen JJ, Nielsen G, et al. (2016) Cardiac patients’ walking activity determined by a step counter in cardiac telerehabilitation: Data from the intervention arm of a randomized controlled trial. Journal of medical Internet research 18: e69.
40. Alharbi M, Bauman A, Neubeck L,Gallagher R (2016) Validation of Fitbit-Flex as a measure of free-living physical activity in a community-based phase III cardiac rehabilitation population. Eur J prev cardiol 23: 1476-1485.
41. Tan MKH, Wong JKL, Bakrania K, Abdullahi Y, Harling L, et al (2019) Can activity monitors predict outcomes in patients with heart failure? A systematic review, Eur Heart J Qual Care Clin Outcomes 5: 11-21.