The Analysis of Remote Vital Signs and Health Condition Monitoring by Integrating Wearable Medical Devices and Mobile Phones
In recent years, the number of patients with chronic diseases has been steadily increasing. Among these conditions, some require real-time monitoring systems to track vital signs and ensure timely interventions in critical situations. However, many patients with chronic diseases are elderly and may live alone, making it difficult for them to receive immediate medical attention. This delay has resulted in numerous families losing their loved ones. Since 2020, wearable medical monitoring devices have experienced rapid development. These devices provide an effective solution for remotely monitoring patients while alleviating the burden on healthcare systems. This study reviews authoritative reports, surveys, and research articles to first explore various sensors used for monitoring vital signs, as well as data processing architectures and transmission methods, including their integration with smartphones. By utilizing wearable remote medical monitoring devices, the response time for patients to receive medical assistance in emergencies can be significantly reduced. Furthermore, these devices can also provide timely intervention during unexpected medical incidents in daily life, helping to prevent tragedies. However, analysis reveals that further optimization is needed for both the sensors themselves and the overall system. In particular, there is a need for in-depth research into optimizing algorithm architectures to balance real-time responsiveness and energy efficiency in data transmission. Additionally, the large-scale application of these devices in societal and clinical settings remains insufficient, requiring further experimental efforts to address these challenges.
Authors
- Chenxi Yang (ORCID: https://orcid.org/0000-0001-5058-5404)
Publication Details
- Journal
- Theoretical and Natural Science
- Published
- 2025-01-15
- DOI
- https://doi.org/10.54254/2753-8818/2025.20125
- Primary Topic
- IoT and Edge/Fog Computing
- Type
- article
- Field-Weighted Citation Impact
- 0.00