Haghi M, et al. Healthc Inform Res. 2017 Jan;23(1):4-15. https://doi.org/10.4258/hir.2017.23.1.4

The concentration in the new era of healthcare is medical Internet of things according to preventive and prediction (p2Health). In large scale and general perspective, the effective parameters from behavioral, ambient, and physiological domains as the most influencing fields of interest in healthcare, must be monitored. In personalized healthcare monitoring, wearables are playing an important role in terms of data measurement and collection. We aim at creating a configurable and adaptable platform for comprehensive parameters monitoring, according to convenient mode of wearability. Hence, we develop an innovative wrist-worn prototype for ambient monitoring, and a flexible IoT-gateway. The prototype measures the most critical parameters from ambient domain. In this platform, via IoT-gateway as an intermediate hub between wearables and IoT-server, bidirectional communication between the end-user and medics is established in real-time. In addition, physician as the real-time observer of patients are given the possibility to set up the required parameters for measurement through the IoT-gateway and activate/deactivate the sensors on the wearables. Therefore, depending on the target investigation, status of patients, requirements, and demands, medics can determine the setup parameters for measurement. Thus, the application of this platform is not limited to specific groups, but widely may be applied whether in daily routine or medical research investigation. Under the flexible IoT-gateway, the new wearables can readily be integrated and synchronized into the platform. The users are not restricted to select only one specific product but there are alternatives as well. To support the solution, experimental results are provided.

With the advances in sensor technology, big data, and artificial intelligence, unobtrusive in-home health monitoring has been a research focus for decades. Following up our research on smart vehicles, within the framework of unobtrusive health monitoring in private spaces, this work attempts to provide a guide to current sensor technology for unobtrusive in-home monitoring by a literature review of the state of the art and to answer, in particular, the questions: (1) What types of sensors can be used for unobtrusive in-home health data acquisition? (2) Where should the sensors be placed? (3) What data can be monitored in a smart home? (4) How can the obtained data support the monitoring functions? We conducted a retrospective literature review and summarized the state-of-the-art research on leveraging sensor technology for unobtrusive in-home health monitoring. For structured analysis, we developed a four-category terminology (location, unobtrusive sensor, data, and monitoring functions). We acquired 912 unique articles from four relevant databases (ACM Digital Lib, IEEE Xplore, PubMed, and Scopus) and screened them for relevance, resulting in $n=55$ papers analyzed in a structured manner using the terminology. The results delivered 25 types of sensors (motion sensor, contact sensor, pressure sensor, electrical current sensor, etc.) that can be deployed within rooms, static facilities, or electric appliances in an ambient way. While behavioral data (e.g., presence ($n=38$), time spent on activities ($n=18$)) can be acquired effortlessly, physiological parameters (e.g., heart rate, respiratory rate) are measurable on a limited scale ($n=5$). Behavioral data contribute to functional monitoring. Emergency monitoring can be built up on behavioral and environmental data. Acquired physiological parameters allow reasonable monitoring of physiological functions to a limited extent. Environmental data and behavioral data also detect safety and security abnormalities. Social interaction monitoring relies mainly on direct monitoring of tools of communication (smartphone; computer). In summary, convincing proof of a clear effect of these monitoring functions on clinical outcome with a large sample size and long-term monitoring is still lacking.

The World Health Organization (WHO) recognizes the environmental, behavioral, physiological, and psychological domains that impact adversely human health, well-being, and quality of life (QoL) in general. The environmental domain has significant interaction with the others. With respect to proactive and personalized medicine and the Internet of medical things (IoMT), wearables are most important for continuous health monitoring. In this work, we analyze wearables in healthcare from a perspective of innovation by categorizing them according to the four domains. Furthermore, we consider the mode of wearability, costs, and prolonged monitoring. We identify features and investigate the wearable devices in the terms of sampling rate, resolution, data usage (propagation), and data transmission. We also investigate applications of wearable devices. Web of Science, Scopus, PubMed, IEEE Xplore, and ACM Library delivered wearables that we require to monitor at least one environmental parameter, e.g., a pollutant. According to the number of domains, from which the wearables record data, we identify groups: G1, environmental parameters only; G2, environmental and behavioral parameters; G3, environmental, behavioral, and physiological parameters; and G4 parameters from all domains. In total, we included 53 devices of which 35, 9, 9, and 0 belong to G1, G2, G3, and G4, respectively. Furthermore, 32, 11, 7, and 5 wearables are applied in general health and well-being monitoring, specific diagnostics, disease management, and non-medical. We further propose customized and quantified output for future wearables from both, the perspectives of users, as well as physicians. Our study shows a shift of wearable devices towards disease management and particular applications. It also indicates the significant role of wearables in proactive healthcare, having capability of creating big data and linking to external healthcare systems for real-time monitoring and care delivery at the point of perception.

Unobtrusive in-vehicle health monitoring has the potential to use the driving time to perform regular medical check-ups. This work intends to provide a guide to currently proposed sensor systems for in-vehicle monitoring and to answer, in particular, the questions: (1) Which sensors are suitable for in-vehicle data collection? (2) Where should the sensors be placed? (3) Which biosignals or vital signs can be monitored in the vehicle? (4) Which purposes can be supported with the health data? We reviewed retrospective literature systematically and summarized the up-to-date research on leveraging sensor technology for unobtrusive in-vehicle health monitoring. PubMed, IEEE Xplore, and Scopus delivered 959 articles. We firstly screened titles and abstracts for relevance. Thereafter, we assessed the entire articles. Finally, 46 papers were included and analyzed. A guide is provided to the currently proposed sensor systems. Through this guide, potential sensor information can be derived from the biomedical data needed for respective purposes. The suggested locations for the corresponding sensors are also linked. Fifteen types of sensors were found. Driver-centered locations, such as steering wheel, car seat, and windscreen, are frequently used for mounting unobtrusive sensors, through which some typical biosignals like heart rate and respiration rate are measured. To date, most research focuses on sensor technology development, and most application-driven research aims at driving safety. Health-oriented research on the medical use of sensor-derived physiological parameters is still of interest.

This paper introduces a new dual-input non-isolated zero-voltage switching (ZVS) dc-dc boost converter. The proposed converter hybridizes two bidirectional and unidirectional boost converters, to harvest energy from a rechargeable energy storage element and a clean energy dc generator, respectively. Hence, the proposed circuit utilizes three power switches, one power diode, two inductors and an output filtering capacitor. The ZVS of the all power switches and ZCS for the power diode is realized without any auxiliary circuit. The soft-switching performance is designed to be valid for the whole power ranges of the converter input sources and the output load. The converter power switches are switched in PWM manner with two individual duty ratios, allowing to regulate the converter output voltage and control the extracted power from the input unidirectional port through a simple and useful control system. Depending on the converter duty ratios, its basic operation principle is analyzed in two different operation cases. The proposed converter benefits from simple and compact structure, minimum number of power switches and magnetic elements and high efficiency. The behavior of the proposed converter is analytically investigated, and a low-power laboratory prototype is designed and fabricated to evaluate the converter performance in different operation conditions.