ORCID Profile
0000-0003-0932-5306
Current Organisation
University of Western Sydney Parramatta Campus
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Publisher: MDPI AG
Date: 15-11-2021
DOI: 10.3390/S21227586
Abstract: Triage is the first interaction between a patient and a nurse aramedic. This assessment, usually performed at Emergency departments, is a highly dynamic process and there are international grading systems that according to the patient condition initiate the patient journey. Triage requires an initial rapid assessment followed by routine checks of the patients’ vitals, including respiratory rate, temperature, and pulse rate. Ideally, these checks should be performed continuously and remotely to reduce the workload on triage nurses optimizing tools and monitoring systems can be introduced and include a wearable patient monitoring system that is not at the expense of the patient’s comfort and can be remotely monitored through wireless connectivity. In this study, we assessed the suitability of a small ceramic piezoelectric disk submerged in a skin-safe silicone dome that enhances contact with skin, to detect wirelessly both respiration and cardiac events at several positions on the human body. For the purposes of this evaluation, we fitted the sensor with a respiratory belt as well as a single lead ECG, all acquired simultaneously. To complete Triage parameter collection, we also included a medical-grade contact thermometer. Performances of cardiac and respiratory events detection were assessed. The instantaneous heart and respiratory rates provided by the proposed sensor, the ECG and the respiratory belt were compared via statistical analyses. In all considered sensor positions, very high performances were achieved for the detection of both cardiac and respiratory events, except for the wrist, which provided lower performances for respiratory rates. These promising yet preliminary results suggest the proposed wireless sensor could be used as a wearable, hands-free monitoring device for triage assessment within emergency departments. Further tests are foreseen to assess sensor performances in real operating environments.
Publisher: MDPI AG
Date: 22-10-2019
DOI: 10.3390/S19204596
Abstract: Upper limb utation is a condition that significantly restricts the utees from performing their daily activities. The myoelectric prosthesis, using signals from residual stump muscles, is aimed at restoring the function of such lost limbs seamlessly. Unfortunately, the acquisition and use of such myosignals are cumbersome and complicated. Furthermore, once acquired, it usually requires heavy computational power to turn it into a user control signal. Its transition to a practical prosthesis solution is still being challenged by various factors particularly those related to the fact that each utee has different mobility, muscle contraction forces, limb positional variations and electrode placements. Thus, a solution that can adapt or otherwise tailor itself to each in idual is required for maximum utility across utees. Modified machine learning schemes for pattern recognition have the potential to significantly reduce the factors (movement of users and contraction of the muscle) affecting the traditional electromyography (EMG)-pattern recognition methods. Although recent developments of intelligent pattern recognition techniques could discriminate multiple degrees of freedom with high-level accuracy, their efficiency level was less accessible and revealed in real-world ( utee) applications. This review paper examined the suitability of upper limb prosthesis (ULP) inventions in the healthcare sector from their technical control perspective. More focus was given to the review of real-world applications and the use of pattern recognition control on utees. We first reviewed the overall structure of pattern recognition schemes for myo-control prosthetic systems and then discussed their real-time use on utee upper limbs. Finally, we concluded the paper with a discussion of the existing challenges and future research recommendations.
Publisher: MDPI AG
Date: 03-11-2022
DOI: 10.3390/S22218444
Abstract: Epilepsy is a severe neurological disorder that is usually diagnosed by using an electroencephalogram (EEG). However, EEG signals are complex, nonlinear, and dynamic, thus generating large amounts of data polluted by many artefacts, lowering the signal-to-noise ratio, and h ering expert interpretation. The traditional seizure-detection method of professional review of long-term EEG signals is an expensive, time-consuming, and challenging task. To reduce the complexity and cost of the task, researchers have developed several seizure-detection approaches, primarily focusing on classification systems and spectral feature extraction. While these methods can achieve high/optimal performances, the system may require retraining and following up with the feature extraction for each new patient, thus making it impractical for real-world applications. Herein, we present a straightforward manual/automated detection system based on the simple seizure feature lification analysis to minimize these practical difficulties. Our algorithm (a simplified version is available as additional material), borrowing from the telecommunication discipline, treats the seizure as the carrier of information and tunes filters to this specific bandwidth, yielding a viable, computationally inexpensive solution. Manual tests gave 93% sensitivity and 96% specificity at a false detection rate of 0.04/h. Automated analyses showed 88% and 97% sensitivity and specificity, respectively. Moreover, our proposed method can accurately detect seizure locations within the brain. In summary, the proposed method has excellent potential, does not require training on new patient data, and can aid in the localization of seizure focus/origin.
Publisher: MDPI AG
Date: 23-04-2022
DOI: 10.3390/SU14095098
Abstract: This paper investigates the impact of construction activity and associated parking on the overall parking behaviour of a rapidly changing metropolitan city. The study adopted the modelling and simulation of baseline and impact scenarios of increasing demand, changing parking infrastructure and limited on-street parking supply. Results indicate that construction and population growth, as well as limited parking capacities, will have a significant impact on overall parking behaviour. Furthermore, the proximity to the construction site was identified as an important consideration in carpark location choice. These findings suggest that decisions on capacity and locations should be based on critical factors, including the behaviour of various users and loads. This study has implications for policymakers on the provision and selection of parking infrastructure for a range of users. Outcomes of this research have directly influenced the planning framework for the Parramatta Light Rail project, future zoning, and infrastructure development in Parramatta. These findings can be used for recommendations on developing travel demand management (TDM) strategies for various stakeholders, depending on the context of parking demand, supply, and future changes. However, the study is limited to surveys of actual parking demand without considering latent demand during the peak period of the day.
Publisher: MDPI AG
Date: 10-02-2023
DOI: 10.3390/SU15043301
Abstract: The main purpose of this research is to investigate the effect of kerbside parking demand and provision on short-term parking (STP) and freight activity space (FAS) as a benchmark for infrastructure planning, considering the impacts of expected future growth and capacity changes. In this study, we adopted a mixed-methods approach of quantitative analysis including a spatial view of parking using manual and video-captured camera data from the majority of STP and FAS parking bays covering a erse range of loads/tasks with different levels of elasticity and substitutes, as well as simulation of current demand influenced by various factors, as a basis for the development of strategies and prioritisation of the allocation of limited kerbside spaces in Parramatta, a rapidly transforming/growing CBD city centre environment. Parking demand consisted of a erse range of FAS and STP categories. Spatial analysis showed a non-homogeneous distribution of parking demand and loads across several sections of the city. A large proportion of short-term parking spaces is attributed to two peak periods during the day and increased traffic volumes at peak times. Comparatively lower average parking times in the northern and western regions compared to those in the city centre indicate the potential to reduce peak parking periods and therefore traffic congestion in the city centre by changing parking limits. The presented simulation model can be used as a reliable benchmarking model for the simulation of future impact scenarios and to make recommendations with respect to infrastructure planning and to develop travel demand management strategies. This research is based on a case study and is therefore subject to limitations in its applications in other contexts. Extension of the baseline simulation with future impact scenarios is planned for the next stage of this research. A simulation model is presented and illustrated as a reliable benchmarking tool for the simulation of future impact scenarios through a case study of a rapidly changing city environment.
Publisher: MDPI AG
Date: 25-08-2023
DOI: 10.3390/S23177401
Abstract: This study proposes a novel method for obtaining the electrocardiogram (ECG) derived respiration (EDR) from a single lead ECG and respiration-derived cardiogram (RDC) from a respiratory stretch sensor. The research aims to reconstruct the respiration waveform, determine the respiration rate from ECG QRS heartbeat complexes data, locate heartbeats, and calculate a heart rate (HR) using the respiration signal. The accuracy of both methods will be evaluated by comparing located QRS complexes and inspiration maxima to reference positions. The findings of this study will ultimately contribute to the development of new, more accurate, and efficient methods for identifying heartbeats in respiratory signals, leading to better diagnosis and management of cardiovascular diseases, particularly during sleep where respiration monitoring is paramount to detect apnoea and other respiratory dysfunctions linked to a decreased life quality and known cause of cardiovascular diseases. Additionally, this work could potentially assist in determining the feasibility of using simple, no-contact wearable devices for obtaining simultaneous cardiology and respiratory data from a single device.
Publisher: MDPI AG
Date: 19-02-2021
DOI: 10.3390/ACT10020038
Abstract: Biomimicry is a field of research that uses the functional and structural components of nature, at macroscopic and microscopic scales, to inspire solutions to problems in our industrial world. Soft robotics is an area of research that uses biomimicry, in this case, mimicking skeletal muscles (referred to in this field as “muscle-mimicking actuators”, to perform task of high difficulty, that can be operated in a harmlessly in different environments. One of the most recent advancements to develop from this field is the “Hydraulically lified self-healing electrostatics (HASEL) actuator”. However, this method also brings many of the issues associated with the geometry of its design, especially with respect to the efficiency of the system. Though this system mimics the functionality of the skeletal muscle, there is room to adjust the existing electrostatic mechanisms, that distribute the locally produced force, to mimic the structure of the mechanism that distributes the force to the skeletal muscular, which is also locally produced. In this paper, we show that the current electrostatic parallel electrodes, as well as the zipping mechanisms, can be replaced with the sliding mechanism. This eliminates issues associated with compartmentalizing of the primary electrostatic force and the secondary hydraulic forces leading to a more efficient and controlled transmission electrostatic and hydrostatic forces to the load compared to current iterations and their geometric components.
Publisher: Hindawi Limited
Date: 04-10-2018
DOI: 10.1155/2018/9634184
Abstract: In developing countries, due to the high cost involved, utees have limited access to prosthetic limbs. This constitutes a barrier for this people to live a normal life. To break this barrier, we are developing ultra-low-cost closed-loop myoactivated prostheses that are easy to maintain manufacture and that do not require electrodes in contact with the skin to work effectively. In this paper, we present the implementation for a simple but functional hand prosthesis. Our simple design consists of a low-cost embedded microcontroller (Arduino), a wearable stretch sensor (adapted from electroresistive bands normally used for “insulation of gaskets” against EM fields), to detect residual muscle contraction as direct muscle volumetric shifts and a handful of common, not critical electronic components. The physical prosthesis is a 3D printed claw-style two-fingered hand (PLA plastic) directly geared to an inexpensive servomotor. To make our design easier to maintain, the gears and mechanical parts can be crafted from recovered materials. To implement a closed loop, the amount of closure of prosthesis is fed back to the user via a second stretch sensor directly connected to claw under the form of haptic feedback. Our concept design comprised of all the parts has an overall cost below AUD 30 and can be easily scaled up to more complicated devices suitable for other uses, i.e., multiple in idual fingers and wrist rotation.
Location: United States of America
Location: United States of America
No related grants have been discovered for Upul Gunawardana.