Mobile middleware for wireless body area network.

This paper presents a flexible, efficient and lightweight Wireless Body Area Network (WBAN) Middleware. The Middleware is developed to bridge the communication between mobile device as a gateway and the sensor nodes, and therefore it shields the underlying sensor and OS/protocol stack away from the WBAN application layer. The middleware is coded in the form of lightweight dynamic link library, which allows the application developer to simply incorporate the middleware resource dynamic link library into their application and call the required functions (i.

Motion-based wake-up scheme for ambulatory monitoring in wireless body sensor networks.

Given that wearable sensors that are attached on patients for the purpose of continuous real-time medical monitoring typically need to remain operational for periods of up to 24 hours before a battery change or recharge, power preservation schemes play a critical role in minimizing any possible disruption to a patient's daily activities. In this paper, we propose a motion-based wake-up scheme, a feature which combines motion detection with existing power preservation schemes in order to achieve a balance between energy saving and data timeliness, particularly in critical situations. As a showcase, we have integrated this feature with a healthcare application and demonstrate the capability of the scheme to deal with critical events, e.

Footpaths: Fusion of mObile OuTdoor Personal Advisor for walking rouTe and Health fitnesS.

This paper is mainly concerned with the integration of wireless body sensor network and walking route navigation system in order to provide the most suitable walking path to the wearer following the wearer's health condition. A novel system called Footpaths is proposed. Footpaths is designed to facilitate the measurement of the user's cardio-respiratory fitness level (CRF), through the use of a wearable wireless sensor network, in which the result is used as a key factor in determining the most suitable walking route.

Ambulatory monitoring of human posture and walking speed using wearable accelerometer sensors.

This paper describes a new classification system for real-time monitoring of physical activity, which is able to detect body postures (lying, sitting, and standing) and walking speed with data acquired from three wearable biaxial accelerometer sensors deployed in a wireless body sensor network. One sensor is waist-mounted while the remaining two are attached to the respective thighs. Two studies were conducted for the evaluation of the system, with each study involving five human subjects.

SLIM: a Secured Lightweight Interactive Middleware for wireless body area network.

Advances in wireless sensor technology have introduced a new dimension in healthcare computing. With miniaturized sensor devices, continuous medical monitoring of patients to detect transient life threatening conditions from daily activities has been made possible. This phenomenon will certainly improve the quality of life for a majority of people.

Modeling and Identification of practical ultrasound transducers in ultrasound imaging systems.

This paper provides linear analysis for a practical ultrasound imaging system with single-element transducers. A proper eighth-order linear ARMA model with inputs and outputs of voltage traces is given to present the transfer characteristics of such a practical system, so that echo signals containing tissue information can be collected and analyzed more properly.

An iterative constrained least squares filter for ultrasound image deconvolution.

This paper describes how the recently developed constrained least squares (CLS) filtering algorithm can be made iterative to improve the resolution gain (RG) of medical ultrasound images. We propose the use of the iterative CLS (ICLS) filter, by incorporating the recently proposed ultrasound tissue model, to account for the random fluctuations of the tissue signal within the received ultrasound radio frequency (RF) echo signal. The resulting improvement in RG is demonstrated by eight different abdomen ultrasound images where progressive improvements in both the axial and lateral directions can be observed.

The modified convolution models of ultrasound echo signal.

The ultrasound convolution model is addressed in this paper. Image formation process in the traditional model is expressed as a spatial-temporal convolution between the tissue signal and the ultrasonic system response. However, with the understanding of the existing widely-applied convolution model, we present modification since it omits the acoustical interactions inside the tissue.

Constrained least squares filtering for ultrasound image deconvolution.

This paper uses a new tissue model, which incorporates random fluctuations of the tissue signal within the received ultrasound radio frequency (RF) echo signal, to propose an ultrasound image deconvolution algorithm for improving the quality of ultrasound images. Using this model, we propose a modified version of the classical regularization method which combines optimal Wiener filter and constrained least squares (LS) filtering algorithm for estimation of the tissue signal. The performance of the algorithm is evaluated by simulation.

Constrained least squares filtering algorithm for ultrasound image deconvolution.

A new medical ultrasound tissue model is considered in this paper, which incorporates random fluctuations of the tissue response and provides more realistic interpretation of the received pulse-echo ultrasound signal. Using this new model, we propose an algorithm for restoration of the degraded ultrasound image. The proposed deconvolution is a modification of the classical regularization technique which combines Wiener filter and the constrained least squares (LS) algorithm for restoration of the ultrasound image.