Transversal-load sensor by using local pressure on a chirped fiber bragg grating

A transversal-load sensor based on the local pressure-induced refractive index change in a chirped fiber Bragg grating (CFBG) is proposed. The local pressure induced refractive index change in the touch point can generate a main transmission peak and several subpeaks on the long wavelength side of the reflection band of the CFBG. The difference of the wavelength shifts for the main transmission peak and the first subpeak is used to measure transversal-load with temperature compensation capability.

Embedded multiplexed polymer optical fiber sensor for esophageal manometry

There is a growing interest for esophageal measurements which can provide important and reliable data when diagnosing the motor function of the sphincters and the esophageal body. Biocompatibility, sensing resolution and the comfort of the patient are key parameters for manometric sensing systems. A new sensing approach which could fulfill all these needs is presented in this paper consisting of an embedded polymer fiber sensor, based on multiplexed fiber Bragg gratings. A response to a radial pressure almost 6 times that of a comparable silica fiber based sensor is obtained.

Flexible tactile digital feedback for clinical applications

Trauma and damage to the delicate structures of the inner ear frequently occurs during insertion of electrode array into the cochlea. This is strongly related to the excessive manual insertion force of the surgeon without any tool/tissue interaction feedback. The research is examined tool-tissue interaction of large prototype scale (12.5:1) digit embedded with distributive tactile sensor based upon cochlear electrode and large prototype scale (4.5:1) cochlea phantom for simulating the human cochlear which could lead to small scale digit requirements. This flexible digit classified the tactile information from the digit-phantom interaction such as contact status, tip penetration, obstacles, relative shape and location, contact orientation and multiple contacts. The digit, distributive tactile sensors embedded with silicon-substrate is inserted into the cochlea phantom to measure any digit/phantom interaction and position of the digit in order to minimize tissue and trauma damage during the electrode cochlear insertion. The digit is pre-curved in cochlea shape so that the digit better conforms to the shape of the scala tympani to lightly hug the modiolar wall of a scala. The digit have provided information on the characteristics of touch, digit-phantom interaction during the digit insertion. The tests demonstrated that even devices of such a relative simple design with low cost have potential to improve cochlear implants surgery and other lumen mapping applications by providing tactile feedback information by controlling the insertion through sensing and control of the tip of the implant during the insertion. In that approach, the surgeon could minimize the tissue damage and potential damage to the delicate structures within the cochlear caused by current manual electrode insertion of the cochlear implantation. This approach also can be applied diagnosis and path navigation procedures. The digit is a large scale stage and could be miniaturized in future to include more realistic surgical procedures.

An intrinsic biochemical concentration sensor using a polymer optical fibre Bragg grating

A new type of fibre-optic biochemical concentration sensor based on a polymer optical fibre Bragg grating (POFBG) is proposed. The wavelength of the POFBG varies as a function of analyte concentration. The feasibility of this sensing concept is demonstrated by a saline concentration sensor. When polymer fibre is placed in a water based solution the process of osmosis takes place in this water-fibre system. An osmotic pressure which is proportional to the solution concentration, will apply to the fibre in addition to the hydraulic pressure. It tends to drive the water content out of the fibre and into the surrounding solution. When the surrounding solution concentration increases the osmotic pressure increases to drive the water content out of the fibre, consequently increasing the differential hydraulic pressure and reducing the POFBG wavelength. This process will stop once there is a balance between the osmotic pressure and the differential hydraulic pressure. Similarly when the solution concentration decreases the osmotic pressure decreases, leading to a dominant differential hydraulic pressure which drives the water into the fibre till a new pressure balance is established. Therefore the water content in the polymer fibre - and consequently the POFBG wavelength - depends directly on the solution concentration. A POFBG wavelength change of 0.9 nm was measured for saline concentration varying from 0 to 22%. For a wavelength interrogation system with a resolution of 1 pm, a measurement of solution concentration of 0.03% can be expected.

Dual-parameters sensing based on multimode microfiber with Fresnel reflection

A compact and low cost fiber sensor based on microfiber with Fresnel reflection is proposed and demonstrated for simultaneous measurement of refractive index (RI) and temperature with high sensitivities. © OSA 2015.

Highly sensitive liquid level sensor using a polymer optical Bragg grating for industrial applications

A novel and highly sensitive liquid level sensor based on a polymer optical fiber Bragg grating (POFBG) is reported for the first time. The sensitivity of the sensor is found to be 57 pm/cm of liquid, enhanced by more than a factor of 5 when compared to an equivalent sensor based on silica fiber. © 2015 OSA.

Sensitivity-enhanced fiber optic temperature sensor with strain response suppression

A temperature sensor based on a multimode-singlemode-multimode (MSM) fiber structure has been proposed and experimentally demonstrated. By utilizing the interference between fiber core and cladding modes, temperature measurement is exploited by monitoring the selected resonant dips shift of the transmission spectrum. A high temperature sensitivity of 50.65 pm/ºC is achieved at a certain resonant dip, accompanied by a suppressed strain sensitivity of only 0.587 pm/με. The sensor reveals the advantages of easy fabrication and interrogation, low cost and small axial strain response. © 2013 Elsevier Inc. All rights reserved.

Graphene coated microfiber for temperature sensor

A temperature sensor based on graphene coated microfiber is proposed and demonstrated. By depositing graphene onto the microfiber, the transmission optical power changes linearly along the temperature with a sensitivity of 0.03 dB / C°7. © OSA 2014.

Machine learning for large-scale wearable sensor data in Parkinson disease:concepts, promises, pitfalls, and futures

For the treatment and monitoring of Parkinson's disease (PD) to be scientific, a key requirement is that measurement of disease stages and severity is quantitative, reliable, and repeatable. The last 50 years in PD research have been dominated by qualitative, subjective ratings obtained by human interpretation of the presentation of disease signs and symptoms at clinical visits. More recently, “wearable,” sensor-based, quantitative, objective, and easy-to-use systems for quantifying PD signs for large numbers of participants over extended durations have been developed. This technology has the potential to significantly improve both clinical diagnosis and management in PD and the conduct of clinical studies. However, the large-scale, high-dimensional character of the data captured by these wearable sensors requires sophisticated signal processing and machine-learning algorithms to transform it into scientifically and clinically meaningful information. Such algorithms that “learn” from data have shown remarkable success in making accurate predictions for complex problems in which human skill has been required to date, but they are challenging to evaluate and apply without a basic understanding of the underlying logic on which they are based. This article contains a nontechnical tutorial review of relevant machine-learning algorithms, also describing their limitations and how these can be overcome. It discusses implications of this technology and a practical road map for realizing the full potential of this technology in PD research and practice. © 2016 International Parkinson and Movement Disorder Society.

Mitigating inconsistencies by coupling data cleaning, filtering, and contextual data validation in wireless sensor networks

With the advent of peer to peer networks, and more importantly sensor networks, the desire to extract useful information from continuous and unbounded streams of data has become more prominent. For example, in tele-health applications, sensor based data streaming systems are used to continuously and accurately monitor Alzheimer's patients and their surrounding environment. Typically, the requirements of such applications necessitate the cleaning and filtering of continuous, corrupted and incomplete data streams gathered wirelessly in dynamically varying conditions. Yet, existing data stream cleaning and filtering schemes are incapable of capturing the dynamics of the environment while simultaneously suppressing the losses and corruption introduced by uncertain environmental, hardware, and network conditions. Consequently, existing data cleaning and filtering paradigms are being challenged. This dissertation develops novel schemes for cleaning data streams received from a wireless sensor network operating under non-linear and dynamically varying conditions. The study establishes a paradigm for validating spatio-temporal associations among data sources to enhance data cleaning. To simplify the complexity of the validation process, the developed solution maps the requirements of the application on a geometrical space and identifies the potential sensor nodes of interest. Additionally, this dissertation models a wireless sensor network data reduction system by ascertaining that segregating data adaptation and prediction processes will augment the data reduction rates. The schemes presented in this study are evaluated using simulation and information theory concepts. The results demonstrate that dynamic conditions of the environment are better managed when validation is used for data cleaning. They also show that when a fast convergent adaptation process is deployed, data reduction rates are significantly improved. Targeted applications of the developed methodology include machine health monitoring, tele-health, environment and habitat monitoring, intermodal transportation and homeland security.

Novel online data cleaning protocols for data streams in trajectory, Wireless Sensor Networks

The promise of Wireless Sensor Networks (WSNs) is the autonomous collaboration of a collection of sensors to accomplish some specific goals which a single sensor cannot offer. Basically, sensor networking serves a range of applications by providing the raw data as fundamentals for further analyses and actions. The imprecision of the collected data could tremendously mislead the decision-making process of sensor-based applications, resulting in an ineffectiveness or failure of the application objectives. Due to inherent WSN characteristics normally spoiling the raw sensor readings, many research efforts attempt to improve the accuracy of the corrupted or "dirty" sensor data. The dirty data need to be cleaned or corrected. However, the developed data cleaning solutions restrict themselves to the scope of static WSNs where deployed sensors would rarely move during the operation. Nowadays, many emerging applications relying on WSNs need the sensor mobility to enhance the application efficiency and usage flexibility. The location of deployed sensors needs to be dynamic. Also, each sensor would independently function and contribute its resources. Sensors equipped with vehicles for monitoring the traffic condition could be depicted as one of the prospective examples. The sensor mobility causes a transient in network topology and correlation among sensor streams. Based on static relationships among sensors, the existing methods for cleaning sensor data in static WSNs are invalid in such mobile scenarios. Therefore, a solution of data cleaning that considers the sensor movements is actively needed. This dissertation aims to improve the quality of sensor data by considering the consequences of various trajectory relationships of autonomous mobile sensors in the system. First of all, we address the dynamic network topology due to sensor mobility. The concept of virtual sensor is presented and used for spatio-temporal selection of neighboring sensors to help in cleaning sensor data streams. This method is one of the first methods to clean data in mobile sensor environments. We also study the mobility pattern of moving sensors relative to boundaries of sub-areas of interest. We developed a belief-based analysis to determine the reliable sets of neighboring sensors to improve the cleaning performance, especially when node density is relatively low. Finally, we design a novel sketch-based technique to clean data from internal sensors where spatio-temporal relationships among sensors cannot lead to the data correlations among sensor streams.

Mitigating Inconsistencies by Coupling Data Cleaning, Filtering, and Contextual Data Validation in Wireless Sensor Networks

With the advent of peer to peer networks, and more importantly sensor networks, the desire to extract useful information from continuous and unbounded streams of data has become more prominent. For example, in tele-health applications, sensor based data streaming systems are used to continuously and accurately monitor Alzheimer's patients and their surrounding environment. Typically, the requirements of such applications necessitate the cleaning and filtering of continuous, corrupted and incomplete data streams gathered wirelessly in dynamically varying conditions. Yet, existing data stream cleaning and filtering schemes are incapable of capturing the dynamics of the environment while simultaneously suppressing the losses and corruption introduced by uncertain environmental, hardware, and network conditions. Consequently, existing data cleaning and filtering paradigms are being challenged. This dissertation develops novel schemes for cleaning data streams received from a wireless sensor network operating under non-linear and dynamically varying conditions. The study establishes a paradigm for validating spatio-temporal associations among data sources to enhance data cleaning. To simplify the complexity of the validation process, the developed solution maps the requirements of the application on a geometrical space and identifies the potential sensor nodes of interest. Additionally, this dissertation models a wireless sensor network data reduction system by ascertaining that segregating data adaptation and prediction processes will augment the data reduction rates. The schemes presented in this study are evaluated using simulation and information theory concepts. The results demonstrate that dynamic conditions of the environment are better managed when validation is used for data cleaning. They also show that when a fast convergent adaptation process is deployed, data reduction rates are significantly improved. Targeted applications of the developed methodology include machine health monitoring, tele-health, environment and habitat monitoring, intermodal transportation and homeland security.

Performance of a single liquid column damper for the control of dynamic responses of a tension leg platform

Tuned liquid column dampers have been proved to be successful in mitigating the dynamic responses of civil infrastructure. There have been some recent applications of this concept on wind turbines and this passive control system can help to mitigate responses of offshore floating platforms and wave devices. The control of dynamic responses of these devices is important for reducing loads on structural elements and facilitating operations and maintenance (O&M) activities. This paper outlines the use of a tuned single liquid column damper for the control of a tension leg platform supported wind turbine. Theoretical studies were carried out and a scaled model was tested in a wave basin to assess the performance of the damper. The tests on the model presented in this paper correspond to a platform with a very low natural frequency for surge, sway and yaw motions. For practical purposes, it was not possible to tune the liquid damper exactly to this frequency. The consequent approach taken and the efficiency of such approach are presented in this paper. Responses to waves of a single frequency are investigated along with responses obtained from wave spectra characterising typical sea states. The extent of control is quantified using peak and root mean squared dynamic responses respectively. The tests present some guidelines and challenges for testing scaled devices in relation to including response control mechanisms. Additionally, the results provide a basis for dictating future research on tuned liquid column damper based control on floating platforms.

Towards optical polarization control of laser-driven proton acceleration in foils undergoing relativistic transparency

Control of the collective response of plasma particles to intense laser light is intrinsic to relativistic optics, the development of compact laser-driven particle and radiation sources, as well as investigations of some laboratory astrophysics phenomena. We recently demonstrated that a relativistic plasma aperture produced in an ultra-thin foil at the focus of intense laser radiation can induce diffraction, enabling polarization-based control of the collective motion of plasma electrons. Here we show that under these conditions the electron dynamics are mapped into the beam of protons accelerated via strong charge-separation-induced electrostatic fields. It is demonstrated experimentally and numerically via 3D particle-in-cell simulations that the degree of ellipticity of the laser polarization strongly influences the spatial-intensity distribution of the beam of multi-MeV protons. The influence on both sheath-accelerated and radiation pressure-accelerated protons is investigated. This approach opens up a potential new route to control laser-driven ion sources.

The spatial character of sensor technology

By considering the spatial character of sensor-based interactive systems, this paper investigates how discussions of seams and seamlessness in ubiquitous computing neglect the complex spatial character that is constructed as a side-effect of deploying sensor technology within a space. Through a study of a torch (`flashlight') based interface, we develop a framework for analysing this spatial character generated by sensor technology. This framework is then used to analyse and compare a range of other systems in which sensor technology is used, in order to develop a design spectrum that contrasts the revealing and hiding of a system's structure to users. Finally, we discuss the implications for interfaces situated in public spaces and consider the benefits of hiding structure from users.