The design and development of wearable biosensor systems for health monitoring has garnered lots of attention in the scientific community and the industry during the last years. Mainly motivated by increasing healthcare costs and propelled by recent technological advances in miniature biosensing devices, smart textiles, microelectronics, and wireless communications, the continuous advance of wearable sensor-based systems will potentially transform the future of healthcare by enabling proactive personal health management and ubiquitous monitoring of a patient's health condition. These systems can comprise various types of small physiological sensors, transmission modules and processing capabilities, and can thus facilitate low-cost wearable unobtrusive solutions for continuous all-day and any-place health, mental and activity status monitoring. This paper attempts to comprehensively review the current research and development on wearable biosensor systems for health monitoring. A variety of system implementations are compared in an approach to identify the technological shortcomings of the current state-of-the-art in wearable biosensor solutions. An emphasis is given to multiparameter physiological sensing system designs, providing reliable vital signs measurements and incorporating real-time decision support for early detection of symptoms or context awareness. In order to evaluate the maturity level of the top current achievements in wearable health-monitoring systems, a set of significant features, that best describe the functionality and the characteristics of the systems, has been selected to derive a thorough study. The aim of this survey is not to criticize, but to serve as a reference for researchers and developers in this scientific area and to provide direction for future research improvements.

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A Survey on Wearable Sensor-Based Systems for Health Monitoring and Prognosis

Recent developments and technological advancements in wireless communication, MicroElectroMechanical Systems (MEMS) technology and integrated circuits has enabled low-power, intelligent, miniaturized, invasive/non-invasive micro and nano-technology sensor nodes strategically placed in or around the human body to be used in various applications, such as personal health monitoring. This exciting new area of research is called Wireless Body Area Networks (WBANs) and leverages the emerging IEEE 802.15.6 and IEEE 802.15.4j standards, specifically standardized for medical WBANs. The aim of WBANs is to simplify and improve speed, accuracy, and reliability of communication of sensors/actuators within, on, and in the immediate proximity of a human body. The vast scope of challenges associated with WBANs has led to numerous publications. In this paper, we survey the current state-of-art of WBANs based on the latest standards and publications. Open issues and challenges within each area are also explored as a source of inspiration towards future developments in WBANs.

Wireless Body Area Networks: A Survey

Wireless sensor networks for healthcare: A survey

Power consumption is forecast by the International Technology Roadmap of Semiconductors (ITRS) to pose long-term technical challenges for the semiconductor industry. The purpose of this paper is threefold: (1) to provide an overview of strategies for powering MEMS via non-regenerative and regenerative power supplies; (2) to review the fundamentals of piezoelectric energy harvesting, along with recent advancements, and (3) to discuss future trends and applications for piezoelectric energy harvesting technology. The paper concludes with a discussion of research needs that are critical for the enhancement of piezoelectric energy harvesting devices.

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Powering MEMS portable devices—a review of non-regenerative and regenerative power supply systems with special emphasis on piezoelectric energy harvesting systems

Skin is the largest organ of the human body, and it offers a diagnostic interface rich with vital biological signals from the inner organs, blood vessels, muscles, and dermis/epidermis. Soft, flexible, and stretchable electronic devices provide a novel platform to interface with soft tissues for robotic feedback and control, regenerative medicine, and continuous health monitoring. Here, we introduce the term “lab-on-skin” to describe a set of electronic devices that have physical properties, such as thickness, thermal mass, elastic modulus, and water-vapor permeability, which resemble those of the skin. These devices can conformally laminate on the epidermis to mitigate motion artifacts and mismatches in mechanical properties created by conventional, rigid electronics while simultaneously providing accurate, non-invasive, long-term, and continuous health monitoring. Recent progress in the design and fabrication of soft sensors with more advanced capabilities and enhanced reliability suggest an impending t...

Lab-on-Skin: A Review of Flexible and Stretchable Electronics for Wearable Health Monitoring

We propose a new EEG-based wireless brain computer interface (BCI) with which subjects can "mind-type" text on a computer screen. The application is based on detecting P300 event-related potentials in EEG signals recorded on the scalp of the subject. The BCI uses a simple classifier which relies on a linear feature extraction approach. The accuracy of the presented system is comparable to the state-of-the-art for on-line P300 detection, but with the additional benefit that its much simpler design supports a power-efficient on-chip implementation.

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P300 detection based on feature extraction in on-line brain-computer interface

The estimation of systolic time intervals (STIs) is done using continuous wave (CW) radar at 2.45 GHz with an on-body antenna. Motivation : In the state of the art, typically bioimpedance, heart sounds and/or ultrasound are used to measure STIs. All three methods suffer from insufficient accuracy of STI estimation due to various reasons. CW radar is investigated for its ability to overcome the deficiencies in the state of the art. Methods : Ten healthy male subjects aged 25–45 were asked to lie down at a 30 $^{\circ }$ incline. Recordings of 60 s were taken without breathing and with paced breathing. Heart sounds, electrocardiogram, respiration, and impedance cardiogram were measured simultaneously as reference. The radar antennas were placed at two positions on the chest. The antennas were placed directly on the body as well as with cotton textile in between. The beat to beat STIs have been determined from the reference signals as well as CW radar signals. Results: The results indicate that CW radar can be used to estimate STIs in ambulatory monitoring. Significance: The results pave way to a potentially more compact method of estimating STIs, which can be integrated into a wearable device.

Systolic Time Interval Estimation Using Continuous Wave Radar With On-Body Antennas

A robust wireless system for capacitive ECG is presented, which measures electrode-body capacitive impedance, acceleration, and gyroscope signals from the electrodes to be used in motion artifact reduction algorithms. The system dynamically adapts its robustness and signal quality according to the environmental conditions. Optimizations including bias resistance and cancellation of common mode signals are discussed, and an office chair implementation is presented. An example of motion artifact compensation by means of an adaptive filter that uses the recorded signals is shown; and the dynamic adaptation to prevent front-end saturation is demonstrated and validated.

Robust wireless capacitive ECG system with adaptive signal quality and motion artifact reduction

We present the first measurement results from hybrid AlGaN-on-Si-based Extreme Ultraviolet (EUV) imagers with 10 µm pixel-to-pixel pitch. The 256×256 backside illuminated Focal Plane Arrays (FPAs) were hybridized to dedicated Si-based CMOS Readouts (ROICs). The AlGaN active layer with 40% Al concentration provides an intrinsic rejection of wavelengths larger than 280 nm (solar blindness), together with enhanced radiation hardness (1). Sensitivity in Deep UV (DUV), Far UV (FUV) and Extreme UV (EUV) was verified using synchrotron radiation down to a wavelength of 1 nm.

10 µm pixel-to-pixel pitch hybrid backside illuminated AlGaN-on-Si imagers for solar blind EUV radiation detection

In this work, we discuss why classical thermoelectric theory is not enough to design an optimized energy harvester. Then, the general conditions are defined, which are required to make a thermoelectric converter effective in such application. The necessity of the work has been prompted by the fact that while modeling the harvesters neither the constant temperature difference, nor the heat flow cannot be assumed. We show that simple equations obtained using electro-thermal analogy allow optimization of energy harvesters to reach their top performance characteristics. Thermal matching in MEMS thermopiles is discussed then. The examples of application thermally matched thermopiles for powering state-of-the-art wearable wireless sensors are discussed in the end.

Tom Torfs

Papers

P300 detection based on feature extraction in on-line brain-computer interface

Systolic Time Interval Estimation Using Continuous Wave Radar With On-Body Antennas

Robust wireless capacitive ECG system with adaptive signal quality and motion artifact reduction

10 µm pixel-to-pixel pitch hybrid backside illuminated AlGaN-on-Si imagers for solar blind EUV radiation detection

Thermal matching of a thermoelectric energy harvester with the environment and its application in wearable self-powered wireless medical sensors