Big Data-Driven New Health Economy:Forecasting the Market Size of Wearable Medical Devices

Project: Other

Project Details

Project Title (In Chinese)

大数据驱动的新健康经济:全球可穿戴医疗设备的市场规模预测

Description

In the context of the COVID-19 pandemic and the growing aging population, wearable devices such as smartwatches and smart patches have gained importance in health monitoring. These devices offer a new medical technology that has found widespread use in daily health monitoring, early detection of diseases, and telemedicine. As a result, the demand for wearable medical devices has surged, leading to significant market expansion?and intensified competition. In this context, it is crucial to understand the future market size of wearable medical devices and the underlying factors that drive this growth. However, despite?the growing interest in this area, most existing studies are?qualitative and rely on secondary market data sources. Consequently, there needs to be a more?quantitative analysis of?the market size of wearable medical devices.This study employs a mixed-methods approach to examine wearable medical devices’?applications, current market situation, and development?trends. Through literature analysis, expert interviews, and data analysis, this study explores the application, current market situation, and development trend of wearable medical devices. It clarifies?the factors affecting the future market size of wearable medical devices. Specifically, the study focuses on four major influencing factors: population composition, chronic disease prevalence, healthcare expenditure, and technological innovation. The study establishes a quantitative prediction model using regression analysis and SPSS software to support the analysis. By integrating qualitative and quantitative data, this study provides a comprehensive understanding of the market dynamics of wearable medical devices and sheds light on their prospects.?Based on the findings, this study proposes several recommendations to promote the use of wearable medical devices among older adults, including increasing awareness, enhancing technological innovation, developing legal and regulatory frameworks, and improving safety and security measures. These recommendations aim to support the growth of the wearable medical device market and promote the adoption of these devices in healthcare settings. The main contribution of this study lies in its quantitative exploration and analysis of the factors that influence the size of the wearable medical device market. This study offers theoretical and practical guidance for future research by comprehensively understanding the market dynamics. It helps?suppliers and investors better understand market trends and business opportunities. Additionally, the study’s findings can help businesses develop more effective market strategies and business models to meet the needs of healthcare providers and patients.The contribution of this study lies in the quantitative exploration and analysis?of the factors that influence the size of the wearable medical device market. This study offers theoretical and practical guidance for future research by comprehensively understanding the market dynamics. It helps?suppliers and investors better understand market trends and business opportunities. Additionally, the study’s findings can help businesses develop more effective market strategies and business models to meet the needs of healthcare providers and patients.

Key findings

This study clarified wearable medical devices' application and the current market through
literature, expert interviews, and data analysis. In addition, the study explored factors that
influenced the future market size of wearable medical devices and established a
quantitative model through regression analysis using data from authoritative institutions
such as the World Bank and WHO, with the help of SPSS software.
Project CategoryFYP Undergraduate
AcronymFYP 23
StatusFinished
Effective start/end date1/01/2330/06/23

Keywords

  • Wearable medical devices
  • New health economy
  • Market analysis
  • Big data
  • mHealth

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