## 5 Applications of BSNs
### State-of-the-Art Research on BSN Applications  
#### 5.1.1 Medical Field  
BSN is mostly used in medical field and has a widespread applicability for many kinds of diseases. Traditional clinical monitoring is generally carried out in hospitals, where patients' condition may be affected by the clinical environment and monitoring frequency. In contrast, monitoring based on BSNs can be carried out in a family environment, which makes the results closer to reality. Cardiac disease diagnosis by ECG signals monitoring is a common application of BSNs. In Reference [1], researchers present a wearable ECG acquisition system. The system adopts the Planar-Fashionable Circuit Board (P-FCB) technique, and screen-prints the electrodes directly on fabric, which enables long-term monitoring without skin irritation. The electrodes have high conductivity and adhesiveness, and can be attached on the skin surface. Another kind of monitoring method is to integrate sensors into an adhesive plaster. The plaster can be attached on the skin, which has the advantages of convenience and low cost. For example, Reference [131] suggests integrating all the sensors on one plaster, achieving a smart poultice with a reconfigurable sensor array. A thin flexible battery is integrated on the plaster, which improves wearability. However, this kind of power supply mode leads to great reduction of the plaster's lifetime. Reference [132] proposes a method  
Figure 4: Application fields of BSNs. utilizing wireless power technology on sensor nodes, which can remove batteries and solve the lifetime problem, and further improve the wearability of the monitoring system. In addition to cardiac disease diagnosis, Parkinson's disease (PD) monitoring is also one of the main applications of the BSN technique in the medical field. Because the behavioral recognition techniques of BSN can provide long-term monitoring and credible data, it is more persuasive than the monitoring by clinical observation. Meanwhile, the monitoring can be carried out continuously during daily life, so the patients' information is collected in real time. It is helpful to judge the severity of disease and provide scientific support for therapy. Behavioral recognition techniques have been widely used in many of the existing PD monitoring systems. For example, in Reference [133], researchers identify movement characteristics associated with Parkinson's patients by wearable sensors, and achieve real-time monitoring with high accuracy. In recent years, many studies have shown the connection between PD and speech impairment. Some researchers have proposed a wide range of speech signal processing algorithms (dysphonia measures), which has become a new trend for predicting the severity of PD symptoms. In Reference [134], researchers investigated the accuracy of speech signal processing algorithms which are used to discriminate Parkinson's suffers. Result shows that the classification accuracy can reach almost 99% based on only ten dysphonia features. Respiratory disease treatment can also be implemented with the help of BSN technology. It utilizes a respiratory sensor for monitoring depth and frequency of breathing, so as to guide patients to take correct breathing training, which plays a very important role in respiratory disease rehabilitation [49, 50]. In addition, [3] studies the condition of patients recovering from surgery, employing an ear-worn sensor for post-operative monitoring of patients both in terms of their respiratory function (oxygen saturation and heart rate), as well as their mobility (accelerometer data), to judge whether patients have abnormal symptoms. This application reduces the risk of complications of operation patients during the rehabilitation period. In Reference [135], researchers study lung disease by integrating sensors on a shirt. They measure trans-thoracic bioimpedance outside the body by an electrical impedance tomography technique, thereby measuring lung liquid volume.