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

Advances in wireless communication technologies, such as wearable and implantable biosensors, along with recent developments in the embedded computing area are enabling the design, development, and implementation of body area networks. This class of networks is paving the way for the deployment of innovative healthcare monitoring applications. In the past few years, much of the research in the area of body area networks has focused on issues related to wireless sensor designs, sensor miniaturization, low-power sensor circuitry, signal processing, and communications protocols. In this paper, we present an overview of body area networks, and a discussion of BAN communications types and their related issues. We provide a detailed investigation of sensor devices, physical layer, data link layer, and radio technology aspects of BAN research. We also present a taxonomy of BAN projects that have been introduced/proposed to date. Finally, we highlight some of the design challenges and open issues that still need to be addressed to make BANs truly ubiquitous for a wide range of applications.

Body Area Networks: A Survey

BACKGROUND The movement of animals makes them fascinating but difficult study subjects. Animal movements underpin many biological phenomena, and understanding them is critical for applications in conservation, health, and food. Traditional approaches to animal tracking used field biologists wielding antennas to record a few dozen locations per animal, revealing only the most general patterns of animal space use. The advent of satellite tracking automated this process, but initially was limited to larger animals and increased the resolution of trajectories to only a few hundred locations per animal. The last few years have shown exponential improvement in tracking technology, leading to smaller tracking devices that can return millions of movement steps for ever-smaller animals. Finally, we have a tool that returns high-resolution data that reveal the detailed facets of animal movement and its many implications for biodiversity, animal ecology, behavior, and ecosystem function. ADVANCES Improved technology has brought animal tracking into the realm of big data, not only through high-resolution movement trajectories, but also through the addition of other on-animal sensors and the integration of remote sensing data about the environment through which these animals are moving. These new data are opening up a breadth of new scientific questions about ecology, evolution, and physiology and enable the use of animals as sensors of the environment. High–temporal resolution movement data also can document brief but important contacts between animals, creating new opportunities to study social networks, as well as interspecific interactions such as competition and predation. With solar panels keeping batteries charged, “lifetime” tracks can now be collected for some species, while broader approaches are aiming for species-wide sampling across multiple populations. Miniaturized tags also help reduce the impact of the devices on the study subjects, improving animal welfare and scientific results. As in other disciplines, the explosion of data volume and variety has created new challenges and opportunities for information management, integration, and analysis. In an exciting interdisciplinary push, biologists, statisticians, and computer scientists have begun to develop new tools that are already leading to new insights and scientific breakthroughs. OUTLOOK We suggest that a golden age of animal tracking science has begun and that the upcoming years will be a time of unprecedented exciting discoveries. Technology continues to improve our ability to track animals, with the promise of smaller tags collecting more data, less invasively, on a greater variety of animals. The big-data tracking studies that are just now being pioneered will become commonplace. If analytical developments can keep pace, the field will be able to develop real-time predictive models that integrate habitat preferences, movement abilities, sensory capacities, and animal memories into movement forecasts. The unique perspective offered by big-data animal tracking enables a new view of animals as naturally evolved sensors of environment, which we think has the potential to help us monitor the planet in completely new ways. A massive multi-individual monitoring program would allow a quorum sensing of our planet, using a variety of species to tap into the diversity of senses that have evolved across animal groups, providing new insight on our world through the sixth sense of the global animal collective. We expect that the field will soon reach a transformational point where these studies do more than inform us about particular species of animals, but allow the animals to teach us about the world.

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Terrestrial animal tracking as an eye on life and planet

Gait analysis using wearable sensors is an inexpensive, convenient, and efficient manner of providing useful information for multiple health-related applications. As a clinical tool applied in the rehabilitation and diagnosis of medical conditions and sport activities, gait analysis using wearable sensors shows great prospects. The current paper reviews available wearable sensors and ambulatory gait analysis methods based on the various wearable sensors. After an introduction of the gait phases, the principles and features of wearable sensors used in gait analysis are provided. The gait analysis methods based on wearable sensors is divided into gait kinematics, gait kinetics, and electromyography. Studies on the current methods are reviewed, and applications in sports, rehabilitation, and clinical diagnosis are summarized separately. With the development of sensor technology and the analysis method, gait analysis using wearable sensors is expected to play an increasingly important role in clinical applications.

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Gait analysis using wearable sensors.

Body area sensors can enable novel applications in and beyond healthcare, but research must address obstacles such as size, cost, compatibility, and perceived value before networks that use such sensors can become widespread.

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Body Area Sensor Networks: Challenges and Opportunities

This work presents TEMPO (Technology-Enabled Medical Precision Observation) 3.1, a third generation body area sensor platform that accurately and precisely captures, processes, and wirelessly transmits six-degrees-of-freedom inertial data in a wearable, non-invasive form factor. TEMPO 3.1 is designed to be usable to both the wearer and researcher, thereby enabling motion capture applications in body area sensor networks (BASNs). A complete system is designed and developed that includes the following: (1) enabling technologies and hardware design of TEMPO 3.1, (2) a custom real-time operating system (TEMPOS) that manages all aspects of signal acquisition, signal processing, data management, peripheral control, and wireless communication on a TEMPO node, and (3) a custom case design. The system is evaluated and compared to existing BASN hardware platforms. TEMPO 3.1 creates new opportunities for wearable, continuous monitoring applications and extends the research space of current efforts.

TEMPO 3.1: A Body Area Sensor Network Platform for Continuous Movement Assessment

A current control circuit for improved power application and control of thermoelectric devices to maintain the temperature of thermoelectric devices at a set point. The circuit includes at least one thermoelectric device, an inductor device, a current sensor and a switch device operatively connected in a series connection across a pair of terminals to allow current to flow therethrough when the switch device is activated to the "on" condition; a temperature sensor operatively positioned to monitor the temperature associated with the at least one thermoelectric device; a comparator device receives an input from the current sensor and provides an output to the switch device; a programmable control device receives an input from the temperature sensor and provides an output to the comparator device, the value of the output is determined by the difference between the sensed temperature of the at least one thermoelectric device and the desired set point temperature of the at least one thermoelectric device. The comparator device activates and deactivates the switch device, determined by the output of the programmable control device, to allow current to flow through the at least one thermoelectric device to achieve the set point temperature.

Current control circuit for improved power application and control of thermoelectric devices

A power control circuit for improved temperature control of thermoelectric devices to maintain the temperature of thermoelectric devices at a set point. The circuit includes a rectifying device to provide rectified alternating current when receiving an input from an electrical power source; a flyback power supply to supply a DC voltage to the thermoelectric device; a switching device to modulate the rectified alternating current across the primary of the flyback transformer; sensor circuitry to monitor the temperature of the thermoelectric device; and a programmable control device to receive an output from the sensor circuitry and provide a control signal to the switching device, the control signal being determined by the difference between the sensed temperature of the thermoelectric device and the desired set point to allow the DC voltage to the thermoelectric device to bring the temperature of the thermoelectric device to the set point and maintain the temperature of the thermoelectric device at the set point.

Power control circuit for improved power application and temperature control of low voltage thermoelectric devices

A control system for a thermoelectric device to maintain the temperature in a storage compartment at a set point. The system includes input terminals for receiving a DC voltage and output terminals for connecting to the thermoelectric device. First and second switches are provided and coupled to the terminals for connection when enabled by the application of the DC voltage. The system further includes a first diode network connected between the first and second switches and enabling the second switch when the first diode network is enabled; a coupling device operatively connected to the first diode network to enable the first diode network when the coupling device is enabled; a sensor device providing an output indicative of the temperature in the storage compartment; a programmable control device receiving the output from the sensor device and providing an output to the coupling device to enable the coupling device, the output from the programmable control device being determined by the amount of deviation of the sensed temperature in the storage compartment from the set point temperature.

Harry C. Powell

Papers

Body Area Sensor Networks: Challenges and Opportunities

TEMPO 3.1: A Body Area Sensor Network Platform for Continuous Movement Assessment

Current control circuit for improved power application and control of thermoelectric devices

Power control circuit for improved power application and temperature control of low voltage thermoelectric devices

Temperature controller for low voltage thermoelectric cooling or warming boxes and method therefor