Abstract
Wearable Health Devices (WHDs) are increasingly helping people to better monitor their health status both at an activity/fitness level for self-health tracking and at a medical level providing more data to clinicians with a potential for earlier diagnostic and guidance of treatment. The technology revolution in the miniaturization of electronic devices is enabling to design more reliable and adaptable wearables, contributing for a world-wide change in the health monitoring approach. In this paper we review important aspects in the WHDs area, listing the state-of-the-art of wearable vital signs sensing technologies plus their system architectures and specifications. A focus on vital signs acquired by WHDs is made: first a discussion about the most important vital signs for health assessment using WHDs is presented and then for each vital sign a description is made concerning its origin and effect on heath, monitoring needs, acquisition methods and WHDs and recent scientific developments on the area (electrocardiogram, heart rate, blood pressure, respiration rate, blood oxygen saturation, blood glucose, skin perspiration, capnography, body temperature, motion evaluation, cardiac implantable devices and ambient parameters). A general WHDs system architecture is presented based on the state-of-the-art. After a global review of WHDs, we zoom in into cardiovascular WHDs, analysing commercial devices and their applicability versus quality, extending this subject to smart t-shirts for medical purposes. Furthermore we present a resumed evolution of these devices based on the prototypes developed along the years. Finally we discuss likely market trends and future challenges for the emerging WHDs area.

Abstract
In this work we propose a regression approach based on separability maximization (RASMa) for modeling a continuous-valued estimate of the stress level (we called it stress index) using some features extracted from electrocardiogram (ECG) data. Since no objective measure of the actual stress level (output) is available, finding the stress index cannot be addressed as a classical regression problem. Instead, the proposed approach finds the linear combination of features that maximizes the separability of stress index values for non-stress and stress events. In short, RASMa combines linear discriminant analysis with the Bhattacharyya distance, embedded in a leave-one-subject-out cross-validation scheme. A 26-case pilot study using 17 heart rate variability (HRV) features was conducted as a proof of concept. A near real-time application tool for monitoring stress level over time was also implemented based on the model obtained from the pilot study.

Abstract
Skin temperature regulation is dependent on the autonomic nervous system function, which may be impaired in patients with neuropathy. Literature reporting thermographic assessment of patients with established diagnosis of Diabetic Foot (DF) is scarce, but this information is completely absent in patients suffering from Transthyretin Familial Amyloid Polyneuropathy (TTR-FAP). The aim of this study is to compare skin temperature distribution in patients with DF and TTR-FAP. Thermograms of the dorsal and plantar surfaces of twelve neuropathic patients, six with DF and six with TTR-FAP, were assessed and compared. Skin temperature was significantly higher in the diabetic foot group, in both regions of interest. Thermal symmetry values were high, but similar in both groups. The bias between the right and left foot was smaller, with smaller limits of agreement in TTR-FAP patients, suggesting a lower agreement between the temperature of the right and left feet in DF patients.

Abstract
Firefighting is a hazardous profession commonly exposed to high stress that can interfere with firefighter's health and performance. Nevertheless, on-duty stress levels quantitative evaluations are very rare in the literature. In order to investigate firefighters' occupational health in terms of stress perceptions, symptoms, and quantified physiological reactions under real-world conditions, an ambulatory assessment protocol was developed. Therefore, cardiac signal from firefighters (N =6) was continuously monitored during two shifts within a working week with a medical clinically certified equipment (VitalJacket®), allowing continuous electrocardiogram (ECG) and actigraphy measurement. Psychological data were collected with an android application, collecting potential stressful events, stress symptoms, and stress appraisal. A total of 130 hours of medical-quality ECG were collected, from which heart rate variability (HRV) metrics were extracted and analyzed. Statistical significant differences were found in some HRV metrics - AVNN, RMSSD, pNN50 and LF/HF - between events and non-events, showing higher levels of physiological stress during events (p<0.05). Stress symptoms increase from the beginning to the end of the shift (from 1.54 ± 0.52 to 2.01 ± 0.73), however the mean stress self-perception of events was very low (3.22 ± 2.38 in a scale ranging from 0 to 10). Negative and strong correlations were also found between stress symptoms and some time-domain ECG measures (AVNN, SDNN and pNN50). It can be concluded that stress may not always be detected when using merely self-reports. These results enhance the importance of combining both self-report and ambulatory high-quality physiological stress measures in occupational health settings. Future studies should investigate not only what causes stress but also its impact on health and well-being of these professionals, in order to contribute to the design of efficient stress-management interventions. © 2018 IEEE.

Abstract
Background. Stress at work has been broadly acknowledged as a worldwide problem and has been the focus of concern for many researchers. Firefighting, in particular, is frequently reported as a highly stressful occupation. In order to investigate firefighters' occupational health in terms of stress events, perceptions, symptoms, and physiological reactions under real-world conditions, an ambulatory assessment protocol was developed. Methods. Seventeen firefighters' cardiac signal was continuously monitored during an average of three shifts within a working week with medical clinically certified equipment (VitalJacket (R)), which allows for continuous electrocardiogram (ECG) and actigraphy measurement. Psychological data were collected with a software application running on smartphones, collecting potential stressful events, stress symptoms, and stress appraisal. Results. A total of 450.56 h of medical-quality ECG were collected, and heart rate variability (HRV) analysis was performed. Findings suggest that although 'fire' situations are more common, 'accidents' are more stressful. Additionally, firefighters showed high levels of physiological stress (based on AVNN and LF/HF HRV metrics) when compared to normative healthy population values that may not be diagnosed using merely self-reports. Discussion. The proposed ambulatory study seems to be useful for the monitoring of stress levels and its potential impact on health of first responders. Additionally, it could also be an important tool for the design and implementation of efficient interventions and informed management resolutions in real time. Potential applications of this research include the development of quantified occupational health (qOHealth) devices for real life monitoring of emergency personnel stress reactions.

Abstract
Human gait analysis is of utmost importance in understanding several aspects of human movement. In clinical practice, characterizing movement in order to obtain accurate and reliable information is a major challenge, and physicians usually rely on direct observation in order to evaluate a patient's motor abilities. In this contribution, a system that can objectively analyze the patients gait and generate an on the fly, targeted and optimized gait analysis report is presented. It is an extension to an existing system that could be used without interfering with the healthcare environment, which did not provide any on the fly feedback to physicians. Patient data are acquired using Kinect v2, followed by data processing, gait specific feature extraction, ending with the generation of a quantitative on the fly report. To the best of our knowledge, the complete system fills the gap as a proper gait analysis system, i.e., a low-cost tool that can be applied without interfering with the healthcare environment, provide quantitative gait information and on the fly feedback to physicians through a motion quantification report that can be useful in multiple areas. © 2018 IEEE.