On a Hybrid Preamble/Soft-Output Demapper Approach for Time Synchronization for IEEE 802.15.6 Narrowband WBAN

In this paper, we present a maximum likelihood (ML) based time synchronization algorithm for Wireless Body Area Networks (WBAN). The proposed technique takes advantage of soft information retrieved from the soft demapper for the time delay estimation. This algorithm has a low complexity and is adapted to the frame structure specified by the IEEE 802.15.6 standard for the narrowband systems. Simulation results have shown good performance which approach the theoretical mean square error limit bound represented by the Cramer Rao Bound (CRB)

Vital signs monitoring using Ultra Wide Band pulse radar

The aim of this work is to describe how to realize a measurement setup to detect target heart and breath rate with the use of Ultra Wide Band (UWB) radar technology. Thanks to UWB wireless capabilities the detection is done contactless just standing still at a given distance dT. Contactless heart and breath rate detection can be achieved with the use of currently available commercial UWB radar devices. This is of interest for intensive-care patient monitoring, home monitoring, fast disease screening and remote vital signs monitoring. Our setup is composed by devices provided by PulsON: two PulsON 220RD UWB radars. We encountered an issue with time synchronization that is very critical in UWB detection techniques and therefore a custom built synchronization algorithm has been developedope

A novel haptic model and environment for maxillofacial surgical operation planning and manipulation

This paper presents a practical method and a new haptic model to support manipulations of bones and their segments during the planning of a surgical operation in a virtual environment using a haptic interface. To perform an effective dental surgery it is important to have all the operation related information of the patient available beforehand in order to plan the operation and avoid any complications. A haptic interface with a virtual and accurate patient model to support the planning of bone cuts is therefore critical, useful and necessary for the surgeons. The system proposed uses DICOM images taken from a digital tomography scanner and creates a mesh model of the filtered skull, from which the jaw bone can be isolated for further use. A novel solution for cutting the bones has been developed and it uses the haptic tool to determine and define the bone-cutting plane in the bone, and this new approach creates three new meshes of the original model. Using this approach the computational power is optimized and a real time feedback can be achieved during all bone manipulations. During the movement of the mesh cutting, a novel friction profile is predefined in the haptical system to simulate the force feedback feel of different densities in the bone

Phase Synchronization Operator for On-Chip Brain Functional Connectivity Computation

This paper presents an integer-based digital processor for the calculation of phase synchronization between two neural signals. It is based on the measurement of time periods between two consecutive minima. The simplicity of the approach allows for the use of elementary digital blocks, such as registers, counters, and adders. The processor, fabricated in a 0.18- μ m CMOS process, only occupies 0.05 mm 2 and consumes 15 nW from a 0.5 V supply voltage at a signal input rate of 1024 S/s. These low-area and low-power features make the proposed processor a valuable computing element in closed-loop neural prosthesis for the treatment of neural disorders, such as epilepsy, or for assessing the patterns of correlated activity in neural assemblies through the evaluation of functional connectivity maps.Ministerio de Economía y Competitividad TEC2016-80923-POffice of Naval Research (USA) N00014-19-1-215

Doppler Radar Techniques for Distinct Respiratory Pattern Recognition and Subject Identification.

Ph.D. Thesis. University of Hawaiʻi at Mānoa 2017

A Novel and Low Processing Time ECG Security Method Suitable for Sensor Node Platforms

An anonymisation of electrocardiogram (ECG) signal is essential during the distribution and storage in a public repository. In this paper, we propose a novel low processing time ECG anonymisation method based on the fast Fourier transform (FFT) algorithm that is suitable for sensor node platforms. The proposed framework was developed to address two major constraints in the Internet of Medical Thing environment, i.e., immediate need for securing ECG signal and efficient method for overcoming physical limitation of sensor nodes. Performance evaluation by way of computer simulation over normal and abnormal ECG signals showed that the proposed framework was able to conceal fiducial and non-fiducial features of the ECG signals. Additionally, it showed that the proposed framework offered flexibility in determining the secret key length of the anonymised ECG signal. Strong cross-correlation indicated close similarity between the original and the reconstructed ECG signals implying lossless reconstruction of the original ECG signal. Furthermore, the proposed method achieved a lower processing time security algorithm as compared with the recently proposed wavelet based anonymisation methods

Digital Fixed-Point Low Powered Area Efficient Function Estimation for Implantable Devices

This article introduces a new multiplier-less 32-bit fixed point architecture for estimating complex non-linear functions based on adapted shift only series expansions. This novel hardware structure has been proposed for use as a dedicated core unit in implantable medical devices. Its implementation in FPGA produces a mean squared error of 0.23% over the functions sin(x),cos(x),eix and tan−1(x) when compared to unrestricted CPU implementations. These results are achieved with the use of only 133 sliced registers and 399 Look-up-tables (LUTs). Furthermore, the hardware performs extremely well in our hardware-in-the-loop real use case application for the detection of epilepsy by correctly detecting true positive seizures. When implemented into 130 nm technology via GOOGLE Sky130 PDK and Openlane EDA tools, the ASIC occupies a space of 0.0625 mm2 which represents a 47% reduction when compared to competitors. In addition, its power consumption is reduced to 6.46 mW at 100 MHz fo and just 0.4 μW at 1KHz fo .Universidad Loyola Andaluci

Body sensor network for in-home personal healthcare

A body sensor network solution for personal healthcare under an indoor environment is developed. The system is capable of logging the physiological signals of human beings, tracking the orientations of human body, and monitoring the environmental attributes, which covers all necessary information for the personal healthcare in an indoor environment. The major three chapters of this dissertation contain three subsystems in this work, each corresponding to one subsystem: BioLogger, PAMS and CosNet. Each chapter covers the background and motivation of the subsystem, the related theory, the hardware/software design, and the evaluation of the prototype’s performance