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An Application for Pairing with Wearable Devices to Monitor Personal Health Status
Published on: February 3, 2022
Quantified Self-Using Consumer Wearable Device: Predicting Physical and Mental Health.
Bens Pardamean1,2, Haryono Soeparno1,2, Arif Budiarto2,3
1Computer Science Department, BINUS Graduate Program - Master of Computer Science Program, Bina Nusantara University, Jakarta, Indonesia.
Consumer wearable devices show promise for improving physical activity and mental health. However, ensuring the accuracy and validity of these devices remains a critical challenge for widespread adoption.
Area of Science:
- Health Informatics
- Biomedical Engineering
- Digital Health
Background:
- Consumer wearable devices are increasingly popular for promoting healthy lifestyles.
- Research is actively exploring the health and wellbeing benefits of wearable technology.
- This review focuses on recent studies (post-2018) examining wearable devices for health.
Purpose of the Study:
- To summarize recent research on consumer wearable devices.
- To analyze the impact of wearables on physical activity, mental health, and health consciousness.
- To identify key challenges and future directions in wearable device research.
Main Methods:
- A comprehensive literature search was conducted in major scientific databases (PubMed, Scopus, etc.).
- The search keyword was "wearable device research", with a focus on studies published since 2018.
- 25 relevant papers were selected, covering literature reviews, accuracy studies, data collection tools, and interventions.
Main Results:
- Wearable devices are utilized for general wellbeing and in clinical contexts like cardiovascular disorder management and post-stroke treatment.
- Studies analyzed wearable device types, data sources, study designs, and processing methods.
- Evidence suggests wearables can validate benefits for general health and specific medical conditions.
Conclusions:
- Wearable device accuracy and validity are paramount for clinical adoption.
- Future research should integrate traditional study designs with advanced statistical and machine learning methods.
- This review offers insights for researchers in the field of wearable technology.
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