Wavelet theory is emerging as one of the prevalent tool in signal and image processing applications. However, the most suitable mother wavelet for these applications is still a relative question mark amongst researchers. Selection of best mother wavelet through parameterization leads to better findings for the analysis in comparison to random selection. The objective of this article is to compare the performance of the existing members of mother wavelets and to select the most suitable mother wavelet for accurate infant cry classification. Optimal wavelet is found using three different criteria namely the degree of similarity of mother wavelets, regularity of mother wavelets and accuracy of correct recognition during classification processes. Recorded normal and pathological infant cry signals are decomposed into five levels using wavelet packet transform. Energy and entropy features are extracted at different sub bands of cry signals and their effectiveness are tested with four supervised neural network architectures. Findings of this study expound that, the Finite impulse response based approximation of Meyer is the best wavelet candidate for accurate infant cry classification analysis.
Human brain generates electromagnetic signals during certain activation inside the brain. The localization of the active sources which are responsible for such activation is termed as brain source localization. This process of source estimation with the help of EEG which is also known as EEG inverse problem is helpful to understand physiological, pathological, mental, functional abnormalities and cognitive behaviour of the brain. This understanding leads for the specification for diagnoses of various brain disorders such as epilepsy and tumour. Different approaches are devised to exactly localize the active sources with minimum localization error, less complexity and more validation which include minimum norm, low resolution brain electromagnetic tomography (LORETA), standardized LORETA, exact LORETA, Multiple Signal classifier, focal under determined system solution etc. This paper discusses and compares the ability of localizing the sources for two low resolution methods i.e., sLORETA and eLORETA respectively. The ERP data with visual stimulus is used for comparison at four different time instants for both methods (sLORETA and eLORETA) and then corresponding activation in terms of scalp map, slice view and cortex map is discussed.
This paper describes a discrete wavelet transform-based feature extraction scheme for the classification of EEG signals. In this scheme, the discrete wavelet transform is applied on EEG signals and the relative wavelet energy is calculated in terms of detailed coefficients and the approximation coefficients of the last decomposition level. The extracted relative wavelet energy features are passed to classifiers for the classification purpose. The EEG dataset employed for the validation of the proposed method consisted of two classes: (1) the EEG signals recorded during the complex cognitive task--Raven's advance progressive metric test and (2) the EEG signals recorded in rest condition--eyes open. The performance of four different classifiers was evaluated with four performance measures, i.e., accuracy, sensitivity, specificity and precision values. The accuracy was achieved above 98 % by the support vector machine, multi-layer perceptron and the K-nearest neighbor classifiers with approximation (A4) and detailed coefficients (D4), which represent the frequency range of 0.53-3.06 and 3.06-6.12 Hz, respectively. The findings of this study demonstrated that the proposed feature extraction approach has the potential to classify the EEG signals recorded during a complex cognitive task by achieving a high accuracy rate.
It was the aim of this work to assess and track the workload, working conditions and professional recognition of radiation oncology medical physicists (ROMPs) in the Asia Pacific region over time. In this third survey since 2008, a structured questionnaire was mailed in 2014 to 22 senior medical physicists representing 23 countries. As in previous surveys the questionnaire covered seven themes: 1 education, training and professional certification, 2 staffing, 3 typical tasks, 4 professional organisations, 5 resources, 6 research and teaching, and 7 job satisfaction. The response rate of 100% is a result of performing a survey through a network, which allows easy follow-up. The replies cover 4841 ROMPs in 23 countries. Compared to 2008, the number of medical physicists in many countries has doubled. However, the number of experienced ROMPs compared to the overall workforce is still small, especially in low and middle income countries. The increase in staff is matched by a similar increase in the number of treatment units over the years. Furthermore, the number of countries using complex techniques (IMRT, IGRT) or installing high end equipment (tomotherapy, robotic linear accelerators) is increasing. Overall, ROMPs still feel generally overworked and the professional recognition, while varying widely, appears to be improving only slightly. Radiation oncology medical physics practice has not changed significantly over the last 6 years in the Asia Pacific Region even if the number of physicists and the number and complexity of treatment techniques and technologies have increased dramatically.
The history of medical physics in Asia-Oceania goes back to the late nineteenth century when X-ray imaging was introduced, although medical physicists were not appointed until much later. Medical physics developed very quickly in some countries, but in others the socio-economic situation as such prevented it being established for many years. In others, the political situation and war has impeded its development. In many countries their medical physics history has not been well recorded and there is a danger that it will be lost to future generations. In this paper, brief histories of the development of medical physics in most countries in Asia-Oceania are presented by a large number of authors to serve as a record. The histories are necessarily brief; otherwise the paper would quickly turn into a book of hundreds of pages. The emphasis in each history as recorded here varies as the focus and culture of the countries as well as the length of their histories varies considerably.
This research proposes an exploratory study of a simple, accurate, and computationally efficient movement classification technique for prosthetic hand application. Surface myoelectric signals were acquired from the four muscles, namely, flexor carpi ulnaris, extensor carpi radialis, biceps brachii, and triceps brachii, of four normal-limb subjects. The signals were segmented, and the features were extracted with a new combined time-domain feature extraction method. Fuzzy C-means clustering method and scatter plot were used to evaluate the performance of the proposed multi-feature versus Hudgins' multi-feature. The movements were classified with a hybrid Adaptive Resonance Theory-based neural network. Comparative results indicate that the proposed hybrid classifier not only has good classification accuracy (89.09%) but also a significantly improved computation time.
Memory plays an important role in human life. Memory can be divided into two categories, i.e., long term memory and short term memory (STM). STM or working memory (WM) stores information for a short span of time and it is used for information manipulations and fast response activities. WM is generally involved in the higher cognitive functions of the brain. Different studies have been carried out by researchers to understand the WM process. Most of these studies were based on neuroimaging modalities like fMRI, EEG, MEG etc., which use standalone processes. Each neuroimaging modality has some pros and cons. For example, EEG gives high temporal resolution but poor spatial resolution. On the other hand, the fMRI results have a high spatial resolution but poor temporal resolution. For a more in depth understanding and insight of what is happening inside the human brain during the WM process or during cognitive tasks, high spatial as well as high temporal resolution is desirable. Over the past decade, researchers have been working to combine different modalities to achieve a high spatial and temporal resolution at the same time. Developments of MRI compatible EEG equipment in recent times have enabled researchers to combine EEG-fMRI successfully. The research publications in simultaneous EEG-fMRI have been increasing tremendously. This review is focused on the WM research involving simultaneous EEG-fMRI data acquisition and analysis. We have covered the simultaneous EEG-fMRI application in WM and data processing. Also, it adds to potential fusion methods which can be used for simultaneous EEG-fMRI for WM and cognitive tasks.
This paper reports the novel use of almond gum as a binder in manufacturing Rhizophora spp. particleboard. X-ray fluorescence spectroscopy was employed for analysis under photon energy range of 16.6-25.3 keV. Results showed that almond gum-bonded Rhizophora spp. particleboard can be used as tissue-equivalent phantom in diagnostic radiation. The calculated mass attenuation coefficients of the particleboards were consistent with the values of water calculated using XCOM program for the same photon energies, with p values of 0.056, 0.069, and 0.077 for samples A8, C0, and C8, respectively. However, no direct relationship was found between the percentage of adhesive and the mass attenuation coefficient. The results positively supported the use of almond gum as a binding agent in the fabrication of particleboards, which can be used as a phantom material in dosimetric and quality control applications.
The aim of this paper is to develop a preliminary neurofeedback system to improve the mood of the subjects using audio signals by enhancing their alpha brainwaves. Assessment of the effect of music on the human subjects is performed using three methods; subjective assessment of mood with the help of a questionnaire, the effect on brain by analysing EEG signals, and the effect on body by physiological assessment. In this study, two experiments have been designed. The first experiment was to determine the short-term effect of music on soothing human subjects, whereas the second experiment was to determine its long-term effect. Two types of music were used in the first experiment, the favourite music selected by the participants and a relaxing music with alpha wave binaural beats. The research findings showed that the relaxing music has a better soothing effect on the participants psychologically and physiologically. However, the one-way analysis of variance (ANOVA) results showed that the short-term soothing effect of both favourite music and relaxing music was not significant in changing the mean alpha absolute power and mean physiological measures (blood pressure and heart rate) at the significance level of 0.05. The second experiment was somewhat similar to an alpha neurofeedback training whereby the participants trained their brains to produce more alpha brainwaves by listening to the relaxing music with alpha wave binaural beats for a duration of 30 min daily. The results showed that the relaxing music has a long-term psychological and physiological effect on soothing the participants, as can be observed from the increase in alpha power and decrease in physiological measures after each session of training. The training was found to be effective in increasing the alpha power significantly [F(2,12) = 11.5458 and p = 0.0016], but no significant reduction in physiological measures was observed at the significance level of 0.05.
This study investigates the characteristics and application of the optically-stimulated luminescence dosimeter (OSLD) in cobalt-60 high dose rate (HDR) brachytherapy, and compares the results with the dosage produced by the treatment planning system (TPS). The OSLD characteristics comprised linearity, reproducibility, angular dependence, depth dependence, signal depletion, bleaching rate and cumulative dose measurement. A phantom verification exercise was also conducted using the Farmer ionisation chamber and in vivo diodes. The OSLD signal indicated a supralinear response (R2 = 0.9998). It exhibited a depth-independent trend after a steep dose gradient region. The signal depletion per readout was negligible (0.02%), with expected deviation for angular dependence due to off-axis sensitive volume, ranging from 1 to 16%. The residual signal of the OSLDs after 1 day bleached was within 1.5%. The accumulated and bleached OSLD signals had a standard deviation of ± 0.78 and ± 0.18 Gy, respectively. The TPS was found to underestimate the measured doses with deviations of 5% in OSLD, 17% in the Farmer ionisation chamber, and 7 and 8% for bladder and rectal diode probes. Discrepancies can be due to the positional uncertainty in the high-dose gradient. This demonstrates a slight displacement of the organ at risk near the steep dose gradient region will result in a large dose uncertainty. This justifies the importance of in vivo measurements in cobalt-60 HDR brachytherapy.
Neuroscientists have investigated the functionality of the brain in detail and achieved remarkable results but this area still need further research. Functional magnetic resonance imaging (fMRI) is considered as the most reliable and accurate technique to decode the human brain activity, on the other hand electroencephalography (EEG) is a portable and low cost solution in brain research. The purpose of this study is to find whether EEG can be used to decode the brain activity patterns like fMRI. In fMRI, data from a very specific brain region is enough to decode the brain activity patterns due to the quality of data. On the other hand, EEG can measure the rapid changes in neuronal activity patterns due to its higher temporal resolution i.e., in msec. These rapid changes mostly occur in different brain regions. In this study, multivariate pattern analysis (MVPA) is used both for EEG and fMRI data analysis and the information is extracted from distributed activation patterns of the brain. The significant information among different classes is extracted using two sample t test in both data sets. Finally, the classification analysis is done using the support vector machine. A fair comparison of both data sets is done using the same analysis techniques, moreover simultaneously collected data of EEG and fMRI is used for this comparison. The final analysis is done with the data of eight participants; the average result of all conditions are found which is 65.7% for EEG data set and 64.1% for fMRI data set. It concludes that EEG is capable of doing brain decoding with the data from multiple brain regions. In other words, decoding accuracy with EEG MVPA is as good as fMRI MVPA and is above chance level.
This policy statement, which is the sixth of a series of documents prepared by the Asia-Oceania Federation of Organizations for Medical Physics (AFOMP) Professional Development Committee, gives guidance on how medical physicists in AFOMP countries should conduct themselves in an ethical manner in their professional practice (Ng et al. in Australas Phys Eng Sci Med 32:175-179, 2009; Round et al. in Australas Phys Eng Sci Med 33:7-10, 2010; Round et al. in Australas Phys Eng Sci Med 34:303-307, 2011; Round et al. in Australas Phys Eng Sci Med 35:393-398, 2012; Round et al. in Australas Phys Eng Sci Med 38:217-221, 2015). It was developed after the ethics policies and codes of conducts of several medical physics societies and other professional organisations were studied. The policy was adopted at the Annual General Meeting of AFOMP held in Jaipur, India, in November 2017.
The MOSkin, a metal-oxide semiconductor field-effect transistor based detector, is suitable for evaluating skin dose due to its water equivalent depth (WED) of 0.07 mm. This study evaluates doses received by target area and unavoidable normal skin during a the case of skin brachytherapy. The MOSkin was evaluated for its feasibility as detector of choice for in vivo dosimetry during skin brachytherapy. A high-dose rate Cobalt-60 brachytherapy source was administered to the tumour located at the medial aspect of the right arm, complicated with huge lymphedema thus limiting the arm motion. The source was positioned in the middle of patients' right arm with supine, hands down position. A 5 mm lead and 5 mm bolus were sandwiched between the medial aspect of the arm and lateral chest to reduce skin dose to the chest. Two calibrated MOSkin detectors were placed on the target and normal skin area for five treatment sessions for in vivo dose monitoring. The mean dose to the target area ranged between 19.9 and 21.1 Gy and was higher in comparison with the calculated dose due to contribution of backscattered dose from lead. The mean measured dose at normal skin chest area was 1.6 Gy (1.3-1.9 Gy), less than 2 Gy per fraction. Total dose in EQD2 received by chest skin was much lower than the recommended skin tolerance. The MOSkin detector presents a reliable real-time dose measurement. This study has confirmed the applicability of the MOSkin detector in monitoring skin dose during brachytherapy treatment due to its small sensitive volume and WED 0.07 mm.