EghiFit: Smartphone based Behaviour Monitoring and Health Recommendation in a Weight Loss Intervention Study

Ivezić D, Keppel J, Horneber D, Becker C, Laumer S, Walle H, Schneegass S, Amft O (2024)


Publication Type: Journal article

Publication year: 2024

Journal

Book Volume: 13

Pages Range: 1347

DOI: 10.12688/f1000research.157584.1

Abstract

Background

Current health recommender systems lack interactivity that relates to the current situation.


Methods

We designed and implemented an intervention study for obese patients that incorporates context information obtained from smartphone and smartwatch sensors, gamification, as well as joint goal management of patients and health coaches. We developed a health behaviour recommendation system comprising of a smartphone application, cloud platform for data management, and a data dashboard for coaches.


Results

We conducted a three months long study and analysed data from eight patients, focusing on system function, patient adherence, satisfaction and overall impact of the proposed system on changing health-related habits. Along with data analysis, we also provide patient feedback collected during interview round after the end of the study.


Conclusion

Patients could successfully implement the goals using the EghiFit app. Challenges regarding the data collection, recommendation synthesis, and patient engagement persist. Furthermore, reliable sensor data processing on current smartphone platforms is difficult due to system restrictions. Future research should further integrate sensor data, gaming, and health behaviour intervention design using smart devices.

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How to cite

APA:

Ivezić, D., Keppel, J., Horneber, D., Becker, C., Laumer, S., Walle, H.,... Amft, O. (2024). EghiFit: Smartphone based Behaviour Monitoring and Health Recommendation in a Weight Loss Intervention Study. F1000Research, 13, 1347. https://doi.org/10.12688/f1000research.157584.1

MLA:

Ivezić, Dijana, et al. "EghiFit: Smartphone based Behaviour Monitoring and Health Recommendation in a Weight Loss Intervention Study." F1000Research 13 (2024): 1347.

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