# Special Issue \"Body Sensors Networks for E-Health Applications\"
## 5 Review Articles in the Context of BSN  
Finally, some works have carried out reviews of sensor technologies compatible with BSN. In this sense, the authors of Reference [8] carry out a detailed review of the different technologies that have been proposed for the objective evaluation of chronic pain, which is prevalent in multiple pathologies. The chronic pain condition is directly related to the patient's well-being, and also to the psychological state (anxiety, depression, etc.). The standard evaluation methods of chronic pain are subjective and self-reported evaluations performed by the patients, the medical staff or the caregivers. However, due to their subjective nature, these reports are sometimes imprecise and may lead to insufficient or inappropriate therapy. Objective pain assessment is challenging for researchers, and different approaches for pain measurement based on biomedical sensors have been proposed, although to date there is no universal method for the objective pain assessment. The referenced work [8] reviews and comparatively analyzes the different methods described in the literature focusing on chronic non-cancer pain. One of the variables employed in the studies is the heart rate variability (HRV), since pain influences the balance of the autonomic nervous system (ANS), detectable through the analysis of HRV. Commonly, people with chronic pain have a decreased HRV compared to subjects without pain. In addition, the analysis of the spectrum of the HRV also reveals a clear reduction of the high-frequency components. The review work also examines studies that have analyzed the relationships between physical activity and pain, since patients who have chronic musculoskeletal pain are usually less active. It is common that the anxiety derived from pain sensation causes the subjects to acquire a habit of self-protection and avoidance of pain-related movement. Another parameter of interest is skin conductance, since pain can produce an increase in sweat production triggered by the ANS, and consequently, the conductance. Electromyogram (EMG) signals are also related to the presence of pain due to the increase in muscle tension. Other techniques are based on computer vision and image processing, since the facial features associated with pain are highly identifying. However, these methods are complex and expensive, and unsuitable for use during the patient's daily life. The work also reviews other sensor technologies, such as the measurement of respiratory rate since pain can trigger an irregular breathing pattern, blood pressure that can increase in stages of pain, and body temperature that can decrease as a result of vasoconstriction produced by pain, among others. In the review work carried out in Reference [9], different methods for the measurement and evaluation of the pillars that contribute to brain health are analyzed. This work is justified as a consequence of the increase in life expectancy, associated with a higher prevalence and incidence of psychiatric, neurological and cognitive deterioration pathologies. Although age is a risk factor, it is not the trigger factor and interventions based on healthy lifestyle habits can contribute to the preservation of brain integrity, mental well-being, and cognitive function in advanced ages. The factors that most influence the health of the brain are physical exercise, nutrition and adequate sleep, although other factors such as the maintenance of cognitive activity, a vital plan, general health and social interactions are also of importance. Monitoring these pillars is key in identifying factors that may influence the brain health of a particular subject, and in designing personalized interventions to maintain mental well-being and prevent the cognitive decline. Biomedical sensors integrated into BSN can be used for this purpose, since they are small, portable and allow wireless communication with smartphones for the collection of information.