239,741 research outputs found
A comprehensive survey of wireless body area networks on PHY, MAC, and network layers solutions
Recent advances in microelectronics and integrated circuits, system-on-chip design, wireless communication and intelligent low-power sensors have allowed the realization of a Wireless Body Area Network (WBAN). A WBAN is a collection of low-power, miniaturized, invasive/non-invasive lightweight wireless sensor nodes that monitor the human body functions and the surrounding environment. In addition, it supports a number of innovative and interesting applications such as ubiquitous healthcare, entertainment, interactive gaming, and military applications. In this paper, the fundamental mechanisms of WBAN including architecture and topology, wireless implant communication, low-power Medium Access Control (MAC) and routing protocols are reviewed. A comprehensive study of the proposed technologies for WBAN at Physical (PHY), MAC, and Network layers is presented and many useful solutions are discussed for each layer. Finally, numerous WBAN applications are highlighted
A Study of Medium Access Control Protocols for Wireless Body Area Networks
The seamless integration of low-power, miniaturised, invasive/non-invasive
lightweight sensor nodes have contributed to the development of a proactive and
unobtrusive Wireless Body Area Network (WBAN). A WBAN provides long-term health
monitoring of a patient without any constraint on his/her normal dailylife
activities. This monitoring requires low-power operation of
invasive/non-invasive sensor nodes. In other words, a power-efficient Medium
Access Control (MAC) protocol is required to satisfy the stringent WBAN
requirements including low-power consumption. In this paper, we first outline
the WBAN requirements that are important for the design of a low-power MAC
protocol. Then we study low-power MAC protocols proposed/investigated for WBAN
with emphasis on their strengths and weaknesses. We also review different
power-efficient mechanisms for WBAN. In addition, useful suggestions are given
to help the MAC designers to develop a low-power MAC protocol that will satisfy
the stringent WBAN requirements.Comment: 13 pages, 8 figures, 7 table
A Review of Wireless Body Area Networks for Medical Applications
Recent advances in Micro-Electro-Mechanical Systems (MEMS) technology,
integrated circuits, and wireless communication have allowed the realization of
Wireless Body Area Networks (WBANs). WBANs promise unobtrusive ambulatory
health monitoring for a long period of time and provide real-time updates of
the patient's status to the physician. They are widely used for ubiquitous
healthcare, entertainment, and military applications. This paper reviews the
key aspects of WBANs for numerous applications. We present a WBAN
infrastructure that provides solutions to on-demand, emergency, and normal
traffic. We further discuss in-body antenna design and low-power MAC protocol
for WBAN. In addition, we briefly outline some of the WBAN applications with
examples. Our discussion realizes a need for new power-efficient solutions
towards in-body and on-body sensor networks.Comment: 7 pages, 7 figures, and 3 tables. In V3, the manuscript is converted
to LaTe
Mathematical modeling of ultra wideband in vivo radio channel
This paper proposes a novel mathematical model for an in vivo radio channel at ultra-wideband frequencies (3.1–10.6 GHz), which can be used as a reference model for in vivo channel response without performing intensive experiments or simulations. The statistics of error prediction between experimental and proposed model is RMSE = 5.29, which show the high accuracy of the proposed model. Also, the proposed model was applied to the blind data, and the statistics of error prediction is RMSE = 7.76, which also shows a reasonable accuracy of the model. This model will save the time and cost on simulations and experiments, and will help in designing an accurate link budget calculation for a future enhanced system for ultra-wideband body-centric wireless systems
A Link Loss Model for the On-body Propagation Channel for Binaural Hearing Aids
Binaural hearing aids communicate with each other through a wireless link for
synchronization. A propagation model is needed to estimate the ear-to-ear link
loss for such binaural hearing aids. The link loss is a critical parameter in a
link budget to decide the sensitivity of the transceiver. In this paper, we
have presented a model for the deterministic component of the ear-to-ear link
loss. The model takes into account the dominant paths having most of the power
of the creeping wave from the transceiver in one ear to the transceiver in
other ear and the effect of the protruding part of the outer ear called pinna.
Simulations are done to validate the model using in-the-ear (ITE) placement of
antennas at 2.45 GHz on two heterogeneous phantoms of different age-group and
body size. The model agrees with the simulations. The ear-to-ear link loss
between the antennas for the binaural hearing aids in the homogeneous SAM
phantom is compared with a heterogeneous phantom. It is found that the absence
of the pinna and the lossless shell in the SAM phantom underestimate the link
loss. This is verified by the measurements on a phantom where we have included
the pinnas fabricated by 3D-printing
Classification of Humans into Ayurvedic Prakruti Types using Computer Vision
Ayurveda, a 5000 years old Indian medical science, believes that the universe and hence humans are made up of five elements namely ether, fire, water, earth, and air. The three Doshas (Tridosha) Vata, Pitta, and Kapha originated from the combinations of these elements. Every person has a unique combination of Tridosha elements contributing to a person’s ‘Prakruti’. Prakruti governs the physiological and psychological tendencies in all living beings as well as the way they interact with the environment. This balance influences their physiological features like the texture and colour of skin, hair, eyes, length of fingers, the shape of the palm, body frame, strength of digestion and many more as well as the psychological features like their nature (introverted, extroverted, calm, excitable, intense, laidback), and their reaction to stress and diseases. All these features are coded in the constituents at the time of a person’s creation and do not change throughout their lifetime. Ayurvedic doctors analyze the Prakruti of a person either by assessing the physical features manually and/or by examining the nature of their heartbeat (pulse). Based on this analysis, they diagnose, prevent and cure the disease in patients by prescribing precision medicine.
This project focuses on identifying Prakruti of a person by analysing his facial features like hair, eyes, nose, lips and skin colour using facial recognition techniques in computer vision. This is the first of its kind research in this problem area that attempts to bring image processing into the domain of Ayurveda
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