# Data Gathering Techniques in WSN: A Cross-Layer View
## 6 Wearables and Wireless Body Area Networks (WBAN)
### Technological Advances  
WBAN utilization is penetrating new domains, spanning a wide variety of sensors, each providing a different aspect of the monitored subject. For example, healthcare applications are expected to provide a wide span of indicators from various physiological parameters. Specifically, to provide a comprehensive status of the examinee, it requires, in addition to the standard indicators such as heart rate and physical activity that many of us already have integrated in our watch, information at a deeper level and molecular level insight into the dynamics of the wearer. To cope with the growing popularity of wearables and their expansion to a broader scope of applications, especially in healthcare systems, with the increasing demand to improve quality of service (QoS) and quality of experience (QoE), a new generation of wearables has emerged. This generation relies on several technological advances in both the device and cloud realms. The novel device technology utilizes new soft-sensing technologies, including innovative wearable materials such as conducting polymers, rigid forms of hydrogel, gold and silver nanowires (to create nanowired tattoos as stretchable sensors), carbon nanotubes, liquid metals, ionic liquids, and others. These materials give rise to novel sensor families, such as electro-physiological (acting on the electric potential difference) physical and chemical sensors. See the latest advances in the following related works [198; 199; 200]. For example, besides reviewing the key developments in sweat-sensing technology, [PERSON] et al. [198] examine the requirements of the underlying components embedded in sweat-based wearable sensors and discuss challenges for integrating wearable sweat sensors in the development of personalized healthcare. Sweat-sensing technology has been described earlier; see, for example, [PERSON] et al. [201], where a device containing two humidity sensors located at different heights from the skin is designed in a way that allows one to measure the sweat rate by the difference in readings of these two sensing sub-units. Thermal comfort control by calculating the relation between the vapor pressure and the temperature is designed into watch-type sweat sensors by [PERSON] et al. [202]. Sweat measurement by sweat biomarkers (in particular, pH and Na\({}^{+}\)) is implemented by [PERSON] et al. [203]. In short, the biomarkers cause a change in electric potential near the measuring device, allowing for accurate sweat measurement during physical activity. The authors also note that the change in electrical potential allows for energy harvesting, which can be effectively managed to self-power the device and thus allow for a battery-free design. In general, the material imprinted into the working reacting electrode determines which substance (i.e., a chemical component present in the sweat) it will react with. For example, an application of electrochemical differential pulse voltammetry to sense the sweat to measure the level of caffeine is devised by [PERSON] et al. [204]. The main challenge in the devices is to implement capabilities of effective data gathering, filtering, and transmission within microscopic computing units. Some biometric sensing (especially made by specific configurations of adjacent sensor sets) produces large amounts of data (as in ECG sensing) that should undergo an appropriate local density reduction. To ensure conformity with the sensing devices, paper lithium batteries are proposed (see, e.g., [205]). In addition, many sensors are configured only to transmit following special hazards. For example, ECG sensors should trigger an alarm in case the heartbeat is abnormal. This local data processing is a preliminary phase that facilitates the more intensive data analyses in the intermediate data collection unit (the smartphone), and finally, the destination server.