Using Continuous Data Tracking Technology to Study Exercise Adherence in Pulmonary Rehabilitation

Rizk, Amanda; Wardini, Rima; Chan-Thim, Emilie; Trutschnigg, Barbara; Forget, Amélie; Pepin, Véronique

doi:10.3791/50643

Cited by 7 publications

(4 citation statements)

References 18 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Sensing platforms such as the use of IMUs or motion capture camera are rapidly advancing and could be an opportunity to make a more objective assessment of adherence, continuously tracking motion data obtained from an individual [ 22 , 23 ]. However, the use of these devices to measure adherence is questionable as they arguably influence/enhance adherence itself by means of the user knowing that they are being recorded.…”

Section: Adherence To Exercise Programsmentioning

confidence: 99%

Patient Involvement With Home-Based Exercise Programs: Can Connected Health Interventions Influence Adherence?

Argent¹,

Daly²,

Caulfield³

2018

JMIR Mhealth Uhealth

221

174

View full text Add to dashboard Cite

Adherence to home exercise in rehabilitation is a significant problem, with estimates of nonadherence as high as 50%, potentially having a detrimental effect on clinical outcomes. In this viewpoint, we discuss the many reasons why patients may not adhere to a prescribed exercise program and explore how connected health technologies have the ability to offer numerous interventions to enhance adherence; however, it is hard to judge the efficacy of these interventions without a robust measurement tool. We highlight how well-designed connected health technologies, such as the use of mobile devices, including mobile phones and tablets, as well as inertial measurement units, provide us with the opportunity to better support the patient and clinician, with a data-driven approach that incorporates features designed to increase adherence to exercise such as coaching, self-monitoring and education, as well as remotely monitor adherence rates more objectively.

show abstract

Section: Adherence To Exercise Programsmentioning

confidence: 99%

Patient Involvement With Home-Based Exercise Programs: Can Connected Health Interventions Influence Adherence?

Argent¹,

Daly²,

Caulfield³

2018

JMIR Mhealth Uhealth

221

174

View full text Add to dashboard Cite

show abstract

“…Meanwhile mHealth has been explored in many diseases and patient groups, for example, in cardiovascular diseases [ 19 ], mental disorders [ 20 , 21 ], obese people [ 22 ], hemodialysis patients [ 23 ], chronic pain [ 24 ], children with cerebral palsy [ 25 ], pulmonary rehabilitation [ 26 ], Parkinson’s disease [ 27 ], and stressed persons [ 28 ]. Also, the collection of patient subjective reported outcome using mHealth is already established in oncology and yet has been proven feasible in palliative care patients of different age groups [ 29 - 33 ].…”

Section: Introductionmentioning

confidence: 99%

mHealth Technologies for Palliative Care Patients at the Interface of In-Patient to Outpatient Care: Protocol of Feasibility Study Aiming to Early Predict Deterioration of Patient’s Health Status

Theile¹,

Tröster²,

Gückenberger³

2017

JMIR Res Protoc

View full text Add to dashboard Cite

BackgroundPalliative care patients are a particularly vulnerable population and one of the critical phases in patients’ trajectories is discharge from specialized in-patient palliative care into outpatient care, where availability of a palliative care infrastructure is highly variable. A relevant number of potentially avoidable readmissions and emergency visits of palliative patients is observed due to rapid exacerbation of symptoms indicating the need for a closer patient monitoring. In the last years, different mHealth technology applications have been evaluated in many different patient groups.ObjectiveThe aim of our study is to test feasibility of a remote physical and social tracking system in palliative care patients.MethodsA feasibility study with explorative, descriptive study design, comprised of 3 work packages. From the wards of the Clinic of Radiation-Oncology at the University Hospital Zurich, including the specialized palliative care ward, 30 patients will be recruited and will receive a mobile phone and a tracking bracelet before discharge. The aim of work package A is to evaluate if severely ill patients accept to be equipped with a tracking bracelet and a mobile phone (by semiquantitative questionnaires and guideline interviews). Work package B evaluates the technical feasibility and quality of the acquired electronic health data. Work package C will demonstrate whether physical activity parameters, such as step count, sleep duration, social activity patterns like making calls, and vital signs (eg, heart rate) do correlate with subjective health data and can serve as indicator to early detect and predict changes in patients’ health status. Activity parameters will be extracted from the mobile phone’s and wristband’s sensor data using signal processing methods. Subjective health data is captured via electronic version of visual analog scale and Distress Thermometer as well as the European Organization for Research and Treatment of Cancer – Quality of Life Questionnaire C30 in paper version.ResultsEnrollment began in February 2017. First study results will be reported in the middle of 2018.ConclusionsOur project will deliver relevant data on patients’ acceptance of activity and social tracking and test the correlation between subjective symptom assessment and objective activity in the vulnerable population of palliative care patients. The proposed study is meant to be preparatory work for an intervention study to test the effect of wireless monitoring of palliative care patients on symptom control and quality of life.

show abstract

“…A detailed description of this methodology has been published. 32 Since subjects undergoing IT were expected to spend 50% of their time in their target HR range (during high intervals), adherence to the target training intensity was obtained by multiplying time spent within the target HR range by two up to a maximum of 100%.…”

Section: Methodsmentioning

confidence: 99%

Acute responses to exercise training and relationship with exercise adherence in moderate chronic obstructive pulmonary disease

et al. 2015

Self Cite

View full text Add to dashboard Cite

The objectives of our study were to (i) compare, in chronic obstructive pulmonary disease (COPD) patients, acute responses to continuous training at high intensity (CTHI), continuous training at ventilatory threshold (CTVT) and interval training (IT); (ii) examine associations between acute responses and 12-week adherence; and (iii) investigate whether the relationship between acute responses and adherence is mediated/moderated by affect/vigour. Thirty-five COPD patients (forced expiratory volume in 1 second = 60.2 ± 15.8% predicted), underwent baseline assessments, were randomly assigned to CTHI, CTVT or IT, were monitored throughout about before training, and underwent 12 weeks of exercise training during which adherence was tracked. Compared with CTHI, CTVT was associated with lower respiratory exchange ratio, heart rate and respiratory rate (RR), while IT induced higher [Formula: see text], [Formula: see text]maximal voluntary ventilation, RR and lower pulse oxygen saturation. From pre- to post-exercise, positive affect increased (F = 9.74, p < 0.001) and negative affect decreased (F = 6.43, p = 0.005) across groups. CTVT reported greater end-exercise vigour compared to CTHI (p = 0.01) and IT (p = 0.02). IT exhibited lowest post-exercise vigour (p = 0.04 versus CTHI, p = 0.02 versus CTVT) and adherence rate (F = 6.69, p = 0.004). Mean [Formula: see text] (r = -0.466, p = 0.007) and end-exercise vigour (r = 0.420, p = 0.017) were most strongly correlated with adherence. End-exercise vigour moderated the relationship between [Formula: see text] and adherence (β = 2.74, t(32) = 2.32, p = 0.03). In summary, CTHI, CTVT and IT improved affective valence from rest to post-exercise and induced a significant 12-week exercise training effect. However, they elicited different acute physiological responses, which in turn were associated with differences in 12-week adherence to the target training intensity. This association was moderated by acute end-exercise vigour.

show abstract

Using Continuous Data Tracking Technology to Study Exercise Adherence in Pulmonary Rehabilitation

Cited by 7 publications

References 18 publications

Patient Involvement With Home-Based Exercise Programs: Can Connected Health Interventions Influence Adherence?

Patient Involvement With Home-Based Exercise Programs: Can Connected Health Interventions Influence Adherence?

mHealth Technologies for Palliative Care Patients at the Interface of In-Patient to Outpatient Care: Protocol of Feasibility Study Aiming to Early Predict Deterioration of Patient’s Health Status

Acute responses to exercise training and relationship with exercise adherence in moderate chronic obstructive pulmonary disease

Contact Info

Product

Resources

About