## 2 Main Content of the Special Issue  
As explained by [PERSON] [1], we are standing on the shoulders of giants when looking to the development of the research field of Human Health Engineering, i.e., technology for monitoring the physical and/or mental health status of individuals in a variety of applications, as it evolved from seminal work of, among others, [PERSON] [2], [PERSON] [3], and [PERSON] [4]. For more detailed information on the background and history of the field of Human Health Engineering, the reader is referred to the editorial of [PERSON] [1] written for the first volume of the special issue on Human Health Engineering. The 12 presented papers in this second volume are grouped according to their contributions to the main parts of the monitoring and control engineering scheme applied to human health applications, namely papers focusing on measuring/sensing of physiological variables [5, 6, 7, 8], papers describing health monitoring applications [9, 10, 11, 12], and finally, examples of control applications for human health [13, 14, 15, 16]. As indicated by [PERSON] [1], it is envisioned that the field of human health engineering is complementary to the field of biomedical engineering as it not only contributes to developing technology for curing patients or supporting chronically ill people, but also covers applications on healthy humans (e.g., sports, sleep, and stress) and thus also focuses on disease prevention and optimizing human well-being more generally. The first series of articles in this SI describes methods for (improved) measuring and/or sensing of health-related physiological signals. The work of [PERSON] et al. [5] contributes to developing methods for improving the measuring reliability of fetal monitors, used in the case of high-risk pregnancies, on the basis of probabilistic models. [PERSON] et al. [6] demonstrated the feasibility of using a wearable and stretchable inkjet-printed strain gauge sensor for estimating respiratory rate, which is a key vital sign variable in many medical and health applications. In their study, [PERSON] et al. [7] developed an automated data acquisition system for measuring pinch and pulling forces in patients recovering from stroke. [PERSON] et al. [8] investigated a method for quantifying the functional decline in proprioceptors in patients with low back pain using vibrations with sweep frequencies covering the entire range of response frequencies of proprioceptors. The second series of articles describes applications of human health monitoring. In their paper, [PERSON] et al. [9] described a method combining an electroencephalography image-based method with a convolutional neural network to predict drowsiness in drivers, which is a major cause of vehicle accidents. [PERSON] et al. [10] developed a biometrics monitor allowing to verify individuals on the basis of an interval-based linear discriminant analysis algorithm applied to electrocardiogram signals. [PERSON] et al. [11] used linear and non-linear analyses of electrodermal activity signals for quantifying sympathetic dysregulation as a non-invasive potential biomarker for monitoring anorexia nervosa-linked cardiovascular risks. In the paper of [PERSON] et al. [12], a system is described for monitoring gait in (elderly) people using toe-area activity as a predictor for stumbling risk. Finally, the third series of articles in this SI discusses examples of control applications for human health management. [PERSON] et al. [13] developed a prototype of a closed-loop controlled valveless piezoelectric insulin pump for keeping the blood glucose level of Type 1 diabetes mellitus patients within desired ranges. In their paper, [PERSON] et al. [14] developed a system for virtual reality-based exposure therapy for treating people suffering from driving phobia disorder using biresponse measurements to optimise fear-based driving scenarios. [PERSON] et al. [15] reported about a serious game platform with haptic feedback and EMG monitoring developed for upper limb rehabilitation of spinal cord injury patients.