John Vaughan

Intelligent Carpet System, Based on Photonic Guided-Path Tomography, for Gait and Balance Monitoring in Home Environments

We report on the photonic variant of the previously introduced guided-path tomography (GPT), by demonstrating a system for footstep imaging using plastic optical fiber (POF) sensors. The 1 m × 2 m sensor head is manufactured by attaching 80 POF sensors on a standard commercial carpet underlay. The sensing principle relies on the sensitivity of POF to bending, quantified by measuring light transmission. The photonic GPT system, comprising the sensor head with processing hardware and software, covered by a mass-production general-purpose carpet top, successfully performs footstep imaging and correctly displays the position and footfall of a person walking on the carpet in real time. We also present the implementation of fast footprint center of mass calculations, suitable for recording gait and footfall. A split-screen movie, showing the frame-by-frame camera-captured action next to the reproduced footprints, can be downloaded at http://ieeexplore.ieee.org.

Polymer optical fibre sensor to monitor skin moisture

We present a polymer optical fibre sensor to sense skin moisture and droplet formation when sweating occurs. The sensor used evanescent field attenuation, by exploiting a moisture sensitive cladding with moisture indicator (fluorescein) contained within a porous cladding (HEMA). The sensor was designed to be comfortable to wear and unobtrusive, hygienic, with sterilised interchangeable sensing elements. It had maximum sensitivity between 98% and 100% humidity, and response time of 24 seconds.

Femtosecond laser induced refractive index structures in polymer optical fibre (POF) for sensing

Techniques to directly write localised refractive index structures in polymer optical fibres (POF) are presented, using UV (400nm) ultrafast laser with pulse lengths of 100 fs to create in-fibre gratings for sensing. No doping is necessary for photosensitisation so commercially available POF is used. An in-fibre grating consisting of a 1.8 μm wide refractive index structure with a periodicity of 189 nm was demonstrated in single mode polymer fibre with optimised laser processing parameters.

Polymer optical coatings for moisture monitoring

Polymer optical coatings to detect moisture were developed to clad polymer optical fibres (POF). These claddings were sensitized to moisture to affect the evanescent field and thus the light guided within the fibre, forming POF sensors to continuously monitor human perspiration in response to changes in environmental conditions, physical and mental activity, medical condition or psychological stress.

The characterization of photographic materials as substrates for surface enhanced Raman spectroscopy

In this study, five types of photographic materials were obtained from commercial sources and characterized for use as substrates for surface enhanced Raman spectroscopy. The substrates are photographic emulsions coated on glass or paper support. The emulsions were developed to maximize the amount of metallic silver aggregated into clusters. The test analyte, Cresyl Violet, was deposited directly onto the substrate surface. The permeable nature of the supporting gelatin matrix enables the interaction between the target analyte and the solid silver clusters. The surface enhanced Raman spectra of a 2.75 × 10−7 M concentration of Cresyl Violet in ethanol were obtained using these photographic substrates. The Raman and resonant Raman enhancement of Cresyl Violet varies from substrate to substrate, as does the ratio of Raman to resonant Raman peak heights.

Photonic Guided-Path Tomography sensor for deformation in a non-planar surface

We introduce theoretically and demonstrate experimentally the performance of a Guided-Path Tomography sensor head and a complete system for imaging of physical parameters on non-planar and possibly flexible surfaces. Novel in our approach is to employ waveguiding sensor elements, strategically arranged on the imaged surface, to allow tomography measurements and the inverse problem solution. In the reported particular implementation we image deformation over similar to 1sq.m., which is achieved by sensitizing the sensor elements to bending. The problem of severely limited number of measurements is addressed by an original method for sinogram recovery, followed by the application of well established methods for solving the hard-field tomography inverse problem. We show that the sensor is capable of distinguishing objects of different mass and shape of footprint. It also calculates the coordinates of the centre of mass of the imaged objects, which facilitates integration with control systems.

Evaluation of supervised classification algorithms for human activity recognition with inertial sensors

The main aim of this work is to compare the performance of different algorithms for human activity recognition by extracting various statistical time domain and frequency domain features from the inertial sensor data. Our results show that Support Vector Machines with quadratic kernel classifier (accuracy: 93.5%) and Ensemble classifier with bagging and boosting (accuracy: 94.6%) outperforms other known activity classification algorithms. A parallel coordinate plot based on visualization of features is used to identify useful features or predictors for separating classes. This enabled exclusion of features that contribute least to classification accuracy in a multi-sensor system (five in our case), made the classifier lightweight in terms of number of useful features, training time and computational load and lends itself to real-time implementation.