# Smart Textiles: A Review and Bibliometric Mapping
## 3 Results and Discussion
### Clusters of KW as indicators of research areas
This cluster presents products at a cross-section of wearables (a broader term for all items that can be worn) and smart textiles, as reflected in typical keywords with high occurrence (>10): wearable devices, wearable system, flexible electronics, smart shirt, smart socks, textile sensors, flexible sensors, temperature sensors, biosensors, fabric sensors, optical sensors, piezoresistive sensors, capacitive sensors, stretch sensors, strain sensing, textile pressure sensors, FBGs (Fibre Bragg gratings), health monitoring, m-health (mobile health), electromyography (EMG), rehabilitation, monitoring, respiratory monitoring, respiratory rate, heart rate variability, vital signs, gait analysis, and sports. The wearables cluster contains publications on various sensors and other devices that can detect physiological changes and are used in close contact with the body in smart clothing such as shirts, socks, sportswear, belts, etc. Ideally, wearable sensors should be resistant to mechanical, chemical, and thermal impacts. Sensor concepts based on chemical, physical, and thermal mechanisms of action are suitable for application in smart textiles to detect various parameters such as forces, displacements, thermal energy, humidity, chemicals, UV radiation, etc. Stretch sensors are used to monitor body parameters because the fabric is in direct contact with the skin over a large area of the body. Therefore, monitoring occurs at several points on the body. Pressure sensors are used either as switches and interfaces to electronic devices or also to monitor the user's vital signs. Textile piezoelectric resistance sensors are used to detect movement and respiration. Fabric biosensors can be used to record the electrical signal from the heart--electrocardiogram (ECG); muscle response or electrical activity in response to stimulation of the muscle by a nerve (EMG), brain activity--electroencephalography (EEG); and general vital signs such as heart rate, blood pressure, body and skin temperature, respiratory rate, and oxygen saturation. Constant control over an individual's health and fitness through daily monitoring of vital signs can contribute to proactive care for healthy living in the treatment of chronic diseases, rehabilitation after surgery, progress in sports training, or simply for general preventive monitoring of the user's condition. Cluster 5 (Violet) is grouped around the keyword Wearable Technologies (occurrence 124), with 89 links and a total link strength of 104. The cluster presents electronic technologies that are integrated into textiles to be worn on the body. Among the keywords with the highest occurrence (>25) in this cluster are intelligent textiles, ECG, electrodes, textile electrodes, textile antennas, wearable antennas, pressure sensors, printed electronics, and screen printing. Other specific terms with occurrence >10 include dry electrodes, sensing, wireless communications, structural health monitoring, conductive ink, melt spinning, multi-material fibres, composite materials, and ergonomics. Although the fourth and fifth clusters are closely related, the fifth cluster focuses more on technologies that support the production of wearables. These are electronic devices embedded into textile clothing worn by individuals that are responsible for collecting, analysing, and transmitting personal data, usually with the specific aim of providing healthcare. The production of robust and rigid sensors is now being replaced by new materials that are stretchable, flexible, and resistant to chemicals, so new materials and new technologies are receiving more attention. Printed electronics are made with screen or inkjet printing of conductive inks. Melt spinning is often used to spin highly stretchable and electrically conductive filaments. Composites and multi-material fibres are gaining acceptance in the manufacture of sensors due to their specific advantages over single fibres/materials.