# Smart Clothing Framework for Health Monitoring Applications
## 1 Introduction  
Smart wearables, such as fitness bands and smart watches, and sensor-integrated smart clothing are gaining fast popularity, particularly in the sectors of fitness, personalized healthcare and sports. However, the ergonomic issues with their frequent donning and doffing within short intervals are deemed an extra burden for the users, especially the elderly, infants and young children. The prevailing wearable devices suffer from a poor ergonomic design and thus fail to cover the human body efficiently to ensure uninterrupted and noise-free data gathering as well as to provide the expected level of wearer comfort when used on a long-term basis [1].  
However, the popularity of wearable technologies has instigated the rapid growth of smart clothing [2]. The idea of smart clothing is based on the integration of wearable microelectronic technologies in clothes, such as coats, pants, shirts and leggings, which cover a major part of the human body, wrapping around the wearer in order to monitor their health conditions for identifying the need for a clinical intervention and/or improving physical fitness. Such products are already becoming available on the market, for example, smart shirts from Hexoskin, Athos, OM signal, etc.; compression sleeves from Komodotec; leggings from Wearable X; and so on [2, 3, 4, 5, 6, 7, 8]. It is expected that they must be flexible, foldable, washable, self-cleanable, breathable and stretchable in order to be worn for longer periods.  
The market for smart clothing is estimated to reach a value of USD 8.8 billion by 2024. The demand for smart clothes is growing rapidly in many industries, from retail to military and sports to healthcare [3].  
Ongoing research efforts are focusing either on developing smart clothes or monitoring and analysing health for decision-support systems. However, there is still a lack of a comprehensive framework that can combine both the smart clothes development part and decision-making part. This work proposes a novel smart clothes framework, suggesting the best textile and sensor materials for monitoring and analysing diverse health-related parameters using modern technologies (AI, machine learning and edge computing) to make appropriate decisions for enhancing the quality of human life, principally that of elderly people, athletes and sportsmen.  
The aim of this work is to develop a comprehensive and complete smart clothes framework, combining both the smart clothes development side and data analytics side to monitor health conditions accurately. The following contributions have been made in this work:  
1. Identify potential textile and sensors materials for smart clothes design requirements;
2. Identify suitable sensing mechanisms;
3. Investigate state-of-the-art sensor integration techniques;
4. Suggest appropriate techniques for data collection and analysing with a smartphone and IoT-based cloud system;
5. Suggest advanced data analytics with AI techniques to make decisions for healthcare.  
This paper is organized as follows: Key points on wearable technology and information on smart clothing, including application areas, categories, advantages and current advancements, are presented in Section 2. A novel framework for developing smart clothing (e.g., leggings) with conceptual design specifications, selection criteria of suitable sensor and textile materials with their integration techniques is provided in Section 3. Data collection from smart clothing, data processing and decision making are also presented within the framework. The overall challenges of health monitoring using smart clothing in terms of sensor integration with textiles (fibre, yarn and fabric) and data communication technology are reported in Section 4. Finally, conclusions are drawn in Section 5.