Application of wearables for remote monitoring of oncology patients: A scoping review

Mobile/wearable digital devices for care of active cancer patients: a survey from the ESC Council of Cardio-Oncology

Aims

The Council of Cardio-Oncology of the European Society of Cardiology developed an on-line anonymous survey to provide an overall picture of the current practice on the use of mobile and wearable digital devices in cardio-oncology and the potential barriers to their large-scale applicability.

Methods and results

Between June 2023 and January 2024, an online anonymous questionnaire was completed by 220 healthcare professionals from 55 countries. The greatest number of respondents reported that mobile/wearable digital devices have a role in all active cancer patients for measuring heart rate (33.9%), blood pressure (34.4%), body temperature (32.0%), physical activity (42.4%), and sleep (31.2%). In the setting of atrial fibrillation detection, respondents were evenly split between applying these technologies in all patients (33.0%) or only in selected patients (33.0%). Regarding QTc interval monitoring, 30.6% reported that mobile/wearable digital devices play a role only in selected patients. The decision to use the device was taken by the patient in 56.6% of cases and the physician in 43.4%. The most important barrier reported to mobile/wearable device implementation in the setting of cardiac rhythm monitoring and QTc measurement was their cost (weighted average: 3.38 and 3.39, respectively).

Conclusion

Mobile/wearable digital devices are considered to play an important role in different settings of cardio-oncology, including monitoring of patients' parameters and arrhythmia detection. Their role in monitoring physical activity and QTc interval appears more nuanced. The most important perceived barrier to mobile/wearable digital device implementation is considered their high cost.

Current State of Connected Sensor Technologies Used During Rehabilitation Care: Protocol for a Scoping Review

BACKGROUND

Connected sensor technologies can capture raw data and analyze them using advanced statistical methods such as machine learning or artificial intelligence to generate interpretable behavioral or physiological outcomes. Previous research conducted on connected sensor technologies has focused on design, development, and validation. Published review studies have either summarized general technological solutions to address specific behaviors such as physical activity or focused on remote monitoring solutions in specific patient populations.

OBJECTIVE

This study aimed to map research that focused on using connected sensor technologies to augment rehabilitation services by informing care decisions.

METHODS

The Population, Concept, and Context framework will be used to define inclusion criteria. Relevant articles published between 2008 to the present will be included if (1) the study enrolled adults (population), (2) the intervention used at least one connected sensor technology and involved data transfer to a clinician so that the data could be used to inform the intervention (concept), and (3) the intervention was within the scope of rehabilitation (context). An initial search strategy will be built in Embase; peer reviewed; and then translated to Ovid MEDLINE ALL, Web of Science Core Collection, and CINAHL. Duplicates will be removed prior to screening articles for inclusion. Two independent reviewers will screen articles in 2 stages: title/abstract and full text. Discrepancies will be resolved through group discussion. Data from eligible articles relevant to population, concept, and context will be extracted. Descriptive statistics will be used to report findings, and relevant outcomes will include the type and frequency of connected sensor used and method of data sharing. Additional details will be narratively summarized and displayed in tables and figures. Key partners will review results to enhance interpretation and trustworthiness.

RESULTS

We conducted initial searches to refine the search strategy in February 2024. The results of this scoping review are expected in October 2024.

CONCLUSIONS

Results from the scoping review will identify critical areas of inquiry to advance the field of technology-augmented rehabilitation. Results will also support the development of a longitudinal model to support long-term health outcomes.

TRIAL REGISTRATION

Open Science Framework jys53; https://osf.io/jys53.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/60496.