## 3 Results and Discussion
#### 3.1.2 Wearable Devices
Its properties, such as electrical conductivity, mechanical strength, flexibility, healing abilities, and strain-sensing capabilities, make it suitable for exercise posture assessment, personalized guidance, and injury prevention. It also offers solutions for sustainable e-waste disposal in wearable electronics. Regarding clothing, in [89], the system integrated a single piece of clothing consisting of two separate T-shirts: the first T-shirt serves as a mounting surface for the sensors, while the second shirt provides weather protection and an aesthetic cover. In [71], the authors designed a T-shirt connected to the server ThingSpeak; in addition to this, biomedical sensors were deployed on the patient's clothing or body with a body area network (BAN) to capture vital signs such as the blood pressure, heart rate, oxygen saturation, blood sugar, and other physiological data [90]. Lastly, another group developed smart clothing capable of collecting physiological signals via a biosensor, with precise measurements; it was elastic and designed to be close-fitting [91]. Some systems have been developed taking advantage of commercial devices such as smartwatches and providing infrastructure for the comprehensive monitoring of vital signs. These include the BITalino (PLUX Biosignals, Lisboa, Portugal) wearable device used along with the ATHENA I system in [92]. The study in [93] used the TicWatchPro (Mobvoi, Beijing, China) to create a Web3-type monitoring system, which reduces the burden on healthcare providers and maintains a sustainable health status by establishing mutual oversight among the elderly. [PERSON] et al. used a smartwatch to connect to a data platform named COMES. This integration platform provides a holistic view of data parameters, enabling the recognition of correlations without manual data analysis and offering immediate feedback to users [40]. The work in [94] employed the TicWatch, based on the Snapdragon 410c platform, for data collection and analysis in healthcare monitoring. The authors in [95] compared the accuracy of two all-in-one monitoring devices: the BodiMetrics (Shenzhen Viatom Technology Co., Ltd., Shenzhen, China) performance monitor and the Everlast TR10 (Everlast, Hong Kong, China)smartwatch; additionally, the system developed in [49] requires the user to wear a unique smartwatch or smart band to connect to a multi-tier remote health monitoring system designed for smart cities. [PERSON] et al. simultaneously used the Polar H10 (Polar Electro, Kempele, Finland) and James One (MindProber Labs, Porto, Portugal) heart rate sensors to measure the heart rate variability (HRV) during various tasks, and they transmitted the data from both devices to a computer for analysis [96]. The home-based system in [42] collects data from commercial smartwatches to perform a robust analysis for the understanding of activities towards improved care and safety at home; furthermore, the research outlined in [97] compared the accuracy of blood oxygen in consumer smartwatches. Moreover, the Empatica E4 (Empatica, Milan, Italy) was used in the mHealth system to gather stress scale (SC) data during daily activities in [98]. The research in [99] presents a comparison between three prototypes of PPG sensors and two wearables; the study suggests that PPG signals can be successfully recorded and analyzed in real time, even in a weak-magnetic-field environment, with negligible pressure effects on the signal. Table 3 summarizes the studies discussed in this subsection. A detailed description of each listed work can be found in Table 11, which is organized by year of publication.