Showing papers by "Nigel H. Lovell published in 2008"

Novel neural interface for implant electrodes: improving electroactivity of polypyrrole through MWNT incorporation.

Abstract: Multi-walled carbon nanotubes (MWNTs) can be incorporated into conductive polymers to produce superior materials for neural interfaces with high interfacial areas, conductivity and electrochemical stability. This paper explores the addition of MWNTs to polypyrrole (PPy) through two methods, layering and codeposition. Conductivity of PPy doped with polystyrene sulfonate (PSS), a commonly used dopant, was improved by 50% when MWNTs were layered with PPy/PSS. The film electrochemical stability was improved from 38% activity to 66% activity after 400 cycles of oxidation and reduction. Growth inhibition assays indicated that MWNTs are not growth inhibitory. The electroactive polymer-MWNT composites produced demonstrate properties that suggest they are promising candidates for biomedical electrode coatings.

ECG quality measures in telecare monitoring

Abstract: We analyze the use of unsupervised ECG acquisition in the home environment. An algorithm for automatically marking ECG recordings for sections of obvious artifact is described. The algorithm was validated against a set of 150 records randomly chosen from a database of ECGs and manually annotated to identify sections of artifact. Using this algorithm 4751 single lead-I ECG recordings from 24 home-dwelling patients were examined. The ECGs were collected using a remote home monitoring system. The participant ages (N=24) ranged from 54–92 years and were suffering either chronic obstructive pulmonary disease and/or congestive heart failure. Percentages of amplifier saturation, high frequency artifact, low signal power and the maximum continuous section of useable ECG are quoted. 1344 records were found to contain no artifact, while 3506 records contained 10 seconds or more of uninterrupted ECG (including the 1344 with no artifact). The results show that in the majority of cases, the capture of ECG in an unsupervised home environment is achievable.

Spectral analysis of finger photoplethysmographic waveform variability in a model of mild to moderate haemorrhage.

Abstract: Slow fluctuations in cardiovascular signals such as heart rate variability (HRV) are believed to carry important clinical information. This study investigated whether frequency spectrum analysis of the finger photoplethysmographic waveform variability (PPGV) could characterize a hypovolaemic response by using a blood donation as a model of controlled mild to moderate haemorrhage. This was a prospective, observational study carried out in a convenience sample of blood donors. Spectral analysis was performed on the finger infrared photoplethysmographic waveform and on the electrocardiogram- derived R–R intervals obtained from 43 healthy volunteers during blood donation. Spectral powers were calculated from low frequency (LF), mid frequency (MF) and high frequency (HF) bands of the spectrum of HRV and the coherence-weighted cross-spectrum of PPGV. Comparison was made between the four stages of blood donation: pre-donation (PRE), first half of donation (FIRST), second half of donation (SECOND) and post-donation (POST). A significant increase in the sum of the sympathetic-related MF and respiratory HF powers of finger PPGV (in mean-scaled units) was observed in SECOND and POST (P < 0.01). The post-donation increase in this PPGV spectral measure occurred in 77% of the subjects, which was higher than the percentage of subjects experiencing a blood pressure drop (71% or below). Normalized LF power of HRV showed a significant rise in SECOND (P < 0.01) but not in POST. Spectral analysis of finger PPGV may provide valuable information in addition to vital sign measurements in characterizing a hypovolaemic response. Given the limitations of the current blood loss model, further studies are required to assess the usefulness of finger PPGV for early haemorrhage detection in the clinical setting.

Accelerometry based classification of gait patterns using empirical mode decomposition

Abstract: This paper describes accelerometry based classification of walking patterns. A feature extraction technique based on empirical mode decomposition (EMD) is proposed for the classification of unsupervised walking activities from accelerometry data. The front-end 20 dimensional features representing the gait patterns were obtained from the first three modes of decomposition of the acceleration data in anterior-posterior, medio-lateral, and vertical direction. The back-end of the system was a 64-mixture Gaussian Mixture Model (QMM) classifier. Overall classification accuracy of 96.02% was achieved for the five different human gait patterns including walking on flat surfaces, walking up and down paved ramps and walking up and down stairways.

A wearable triaxial accelerometry system for longitudinal assessment of falls risk

Abstract: Falls-related injuries in the elderly population are a major cause of morbidity and represent one of the most significant contributors to hospitalizations and rising health care expense in developed countries. Many laboratory-based studies have described falls detection systems using wearable accelerometry. However, only a limited number of reports have tried to address the difficult issues of falls detection and falls prevention in unsupervised or free-living environments. We describe a waist-mounted triaxial accelerometry (Triax) system with a remote data collection capability to provide unsupervised monitoring of the elderly. The basis of the monitoring is a self-administered directed-routine (DR) comprising three separate tests measured by way of the Triax. We present an initial evaluation of the DR results in 36 patients to detect early changes in functional ability and facilitate falls risk stratification. Extracted features considered alone show a correlation with falls risk of approximately ρ=0.5. Estimation of falls risk using a linear least squares model provides a root-mean-squared error of 0.69 (ρ=0.58, p<0.0002).

Noninvasive Average Flow and Differential Pressure Estimation for an Implantable Rotary Blood Pump Using Dimensional Analysis

Abstract: Accurate noninvasive average flow and differential pressure estimation of implantable rotary blood pumps (IRBPs) is an important practical element for their physiological control. While most attempts at developing flow and differential pressure estimate models have involved purely empirical techniques, dimensional analysis utilizes theoretical principles of fluid mechanics that provides valuable insights into parameter relationships. Based on data obtained from a steady flow mock loop under a wide range of pump operating points and fluid viscosities, flow and differential pressure estimate models were thus obtained using dimensional analysis. The algorithm was then validated using data from two other VentrAssist IRBPs. Linear correlations between estimated and measured pump flow over a flow range of 0.5 to 8.0 L/min resulted in a slope of 0.98 (R 2 = 0.9848). The average flow error was 0.20 plusmn 0.14 L/min (mean plusmn standard deviation) and the average percentage error was 5.79%. Similarly, linear correlations between estimated and measured pump differential pressure resulted in a slope of 1.027 (R 2 = 0.997) over a pressure range of 60 to 180 mmHg. The average differential pressure error was 1.84 plusmn 1.54 mmHg and the average percentage error was 1.51%.

Gait patterns classification using spectral features

Abstract: Accelerometry has been shown to be a good tool for ambulatory activity monitoring This paper describes the use of spectral features for classification of gait activities based on accelerometric data The classification is performed by a Gaussian mixture model (GMM) based statistical classifier at the back end Fifty subjects participated in the experiment and an overall classification accuracy of 86% was achieved using the proposed 25 dimensional features for five different human gait patterns including walking on level surfaces, walking up and down stairs and walking up and down ramps

Electrode multiplexing method for retinal prosthesis

Abstract: A method is disclosed for efficient multiplexing of a plurality of electrodes in a nerve stimulator using improved, predetermined, regular, repeatable geometric patterns arranged in a predetermined mosaic to form a desired array. Multiple electrodes within said array are addressed by the nerve stimulator as being a stimulating electrode by an instruction specifying a single identifier, indicating a position within each regular geometric pattern. As such, each electrode within the array, maintaining the specified position within its respective repeatable geometric pattern, becomes a stimulating electrode and is connected to the appropriate electronic circuit for subsequent, potential use in nerve stimulation.

Hermetic Encapsulation of an Implantable Vision Prosthesis – Combining Implant Fabrication Philosophies

Abstract: The design of an implantable neurostimulator for the restoration of visual percepts to the blind is discussed in terms of combining two engineering philosophies derived from different origins, yet sharing a common objective. We describe the production of a very small (12 mm diameter) nerve stimulator that exclusively utilises materials with a previous history of not only biological compatibility, but also regulatory approval and clinical application. The fabrication steps that involve laser micromachining, screen-printing, and material cofiring phenomena are illustrated via the example of a substrate for a hermetic electrical neurostimulation device for long-term implantation.

Noninvasive detection of suction in an implantable rotary blood pump using neural networks

Abstract: Granting those heart failure patients who are recipients of an implantable rotary blood pump (iRBP) greater functionality in daily activities is a key long-term strategy currently being pursued by many research groups. A reliable technique for noninvasive detection of the various pumping states, most notably that of ventricular collapse or suction, is an essential component of this strategy. Presented in this study is such a technique, whereby various indicators are derived from the noninvasive pump feedback signals, and a suitable computational methodology developed to classify the pumping states of interest. Clinical telemetry data from ten implant recipients was categorized (with the aid of trans-oesophageal echocardiography) into the normal and suction states. These data are used to develop a pumping state classifier based on an artificial neural network (ANN). Nine indices, derived from the noninvasive impeller speed signal, form the inputs to this ANN classifier. During validation, the resulting ANN classifier achieved a maximum sensitivity of 98.54% (609/618 samples of 5 s in length) and specificity of 99.26% (12,123/12,213 samples) for correct detection of the suction state. The ability to detect the suction state with such a high degree of accuracy provides a critical parameter both for control strategy development, and for clinical care of the implant recipient.

Efficacy of supra-choroidal, bipolar, electrical stimulation in a vision prosthesis

Abstract: The key to successful, clinical application of therapeutic neurostimulators lies primarily with the safety and efficacy of their electrode-tissue interfaces. The authors posit that for electrical stimulation of the visual system, supra-choroidal electrode placement provides a safe, stable and readily-accessible site for implantation and the provision of electrical stimulation. The present paper explores the efficacy of supra-choroidal electrical stimulation of retinal neurons. Based upon recordings made with surface electrodes placed on the primary visual cortex, areas of activation in the cortex were shown to change when different areas on the supra-choroidal space were stimulated. Finally, the threshold to elicit a response from neurons in the visual cortex, was found to be 77.55 ± 29.85 nC.

Image Analysis for Microelectronic Retinal Prosthesis

Abstract: By way of extracellular, stimulating electrodes, a microelectronic retinal prosthesis aims to render discrete, luminous spots-so-called phosphenes-in the visual field, thereby providing a phosphene image (PI) as a rudimentary remediation of profound blindness. As part thereof, a digital camera, or some other photosensitive array, captures frames, frames are analyzed, and phosphenes are actuated accordingly by way of modulated charge injections. Here, we present a method that allows the assessment of image analysis schemes for integration with a prosthetic device, that is, the means of converting the captured image (high resolution) to modulated charge injections (low resolution). We use the mutual-information function to quantify the amount of information conveyed to the PI observer (device implantee), while accounting for the statistics of visual stimuli. We demonstrate an effective scheme involving overlapping, Gaussian kernels, and discuss extensions of the method to account for short-term visual memory in observers, and their perceptual errors of omission and commission.

Gait pattern classification using compact features extracted from intrinsic mode functions

Abstract: Recent research work indicates that gait patterns are both non-linear and non-stationary signals and they can be analyzed using empirical mode decomposition. This paper describes gait pattern classification using features that are obtained by performing discrete cosine transforms (DCT) on intrinsic mode functions of five different human gait patterns. The DCT provides a compact 8-dimensional feature vector for gait pattern classification. Fifty two subjects participated in the experiment. The classification was performed using a Gaussian mixture model and an overall accuracy of 90.2% was achieved.

Implant electronics for intraocular epiretinal neuro-stimulators

Abstract: In this paper, we discuss system architectures, design challenges and circuit implementation principles for intraocular epiretinal neuro-stimulators to be used as part of vision prostheses in partially restoring vision to the blind. Our unique hexagonal electrode placement allows focused simultaneous stimulation which allow the electrode count to scale. A new dual-channel transcutaneous inductive link is used to transfer power and data efficiently to the implant, and a new dual-voltage power rectifier provides two implant supplies without the need for a DC-DC converter. Low-power designs of current stimulators and ECAP amplifiers are also outlined in the paper.

Detecting change in left ventricular ejection time during head-up tilt-induced progressive central hypovolemia using a finger photoplethysmographic pulse oximetry wave form.

Abstract: Background: Change in cardiac preload caused by mild hypovolemia can alter left ventricular ejection time (LVET) without noticeable change in blood pressure (BP). Previously our group has explored a novel method of LVET monitoring using a noninvasive finger photoplethysmographic pulse oximetry wave form. The current study investigated the ability of photoplethysmographic pulse oximetry wave form-derived LVET (LVETp) to identify progressive central hypovolemia induced by head-up tilt and evaluated the potential use of LVETp as an early noninvasive indicator of blood loss. Methods: Thirteen healthy subjects underwent graded head-up tilt from 0 degrees to 80 degrees. The response of LVETp to tilt was compared with that of interbeat heart interval (RR) and BP. Least-squares linear regression analysis was performed on an intrasubject basis between various physiologic variables and sine of the tilt angle (which is associated with the decrease in central blood volume). Results: During graded tilt, LVETp had a very strong negative linear correlation with sine of the tilt angle, with correlation coefficients (r) ranging from 0.961 to 0.985. At a very mild hypovolemic state (10 degrees), there was a significant decrease in LVETp compared with baseline (0 degrees) but without a significant change in RR and BP. Gradient analysis showed that LVETp was sensitive to central volume loss at all volume states (0 degrees–80 degrees), whereas RR was only responsive at mild-to-moderate and moderate hypovolemic states (20 degrees–80 degrees) but not mild hypovolemic state (0 degrees–20 degrees). Conclusions: LVETp has a strong association with the change in central blood volume and may be a sensitive early marker of nonhypotensive progressive central hypovolemia. Joint interpretation of LVETp and RR trends may help to characterize the extent of blood volume loss.

Charge recovery during concurrent stimulation for a vision prosthesis

Abstract: Parallel or concurrent stimulation in an epiretinal neuroprosthesis is likely necessary in order to deliver sufficient phosphenes for effective vision. Important issues with concurrent stimulation are the effect of current distribution which introduces current leakage or ‘cross talk’ between adjacent electrodes and charge recovery which determines balanced charge being delivered/recovered at each electrode from the previous phase. In this paper, we present the effect of concurrent stimulation of two hexagonally arranged platinum electrode arrays on charge recovery. Balanced and imbalanced (unequal) currents were delivered to the hexagonal arrays when they were immersed in physiological saline. Both simulation and experimental results revealed that charge was not recovered at individual electrodes, particularly when imbalanced currents were delivered. However, total charge injected to both hexagonal arrays was recovered.

Feature extraction using an AM-FM model for gait pattern classification

Abstract: This paper describes classification of gait patterns from a waist-mounted triaxial accelerometer. A feature extraction technique using empirical mode decomposition (EMD) and an amplitude/frequency modulation (AM-FM) model is proposed for the classification of walking activities from accelerometry data. A set of novel features, including AM, instantaneous frequency (IF) and instantaneous amplitude (IA), representing the walking patterns were obtained based on a second-order all-pole resonator. The back-end of the system was a 32-mixture Gaussian Mixture Model (GMM) classifier. An overall classification error rate of 4.88% was achieved for the five different human gait patterns referring to walking on flat levels, walking up and down paved ramps and walking up and down stairways.

Finite element analysis of a tactile sensor for a robotic hand

Abstract: Using a bioinspired design approach, we describe the development of a tactile sensor for a robotic hand, based on the mechanoreceptors in the glabrous skin of the human, able to replicate the sensory function of both slow adapting and fast adapting receptors. Slow adapting receptors respond to initial contact and maintain firing throughout the contact period, whereas fast adapting receptors primarily respond during contact onset and offset. Strain gauges are used to emulate the slow adapting receptors, and polyvinylidene fluoride (PVDF) film is used to replicate the function of the fast adapting receptor. Finite element analysis is used to investigate the behaviour of the strain gauges and PVDF film embedded in a silicone elastomer, modelled as a hyperelastic material. One unit sensor consists of four strain gauges and a PVDF film, embedded underneath a square protrusion. The protrusion localises the applied force onto the region or dasiareceptive fieldpsila of the sensing unit. The strain gauges are arranged in an orientation to enable a unit sensor to identify the tri-axial force components. The PVDF film is used to measure vibration. Simulated random forces were applied to the sensor, and a regression model was developed based on the modelled strain gauge outputs. Simulations were also undertaken on the PVDF film to examine the load response to cyclical loads.

A health monitoring and evaluation system for assessing care needs of residents in aged-care facilities

Abstract: The design and implementation of a health monitoring and evaluation system based upon wireless technologies is described. The system is specifically targeted to providing a means of objectively classifying the care needs and requirements of residents in aged care facilities. The system architecture is designed for extensibility and provides a wide range of possible monitoring approaches from direct health monitoring by way of physiological measurement equipment, to unobtrusive monitoring of resident's environments and their interactions to infer functional health status. The system architecture encompasses the abilities to collect multiple types of data from both static and mobile sensors, transfer such data over either a homogeneous or hybrid wireless network to a central server, and perform data fusion with computer-based decision support to extract vital information about the health status of the person being monitored. The major benefits of such a system beyond the principal improvement in management of a resident's disease and wellness, include its ubiquitous and unobtrusive nature and an elevated objectivity in performing functional health assessment.