Detection and Classification of Whale Acoustic Signals

This dissertation focuses on two vital challenges in relation to whale acoustic signals: detection and classification.

In detection, we evaluated the influence of the uncertain ocean environment on the spectrogram-based detector, and derived the likelihood ratio of the proposed Short Time Fourier Transform detector. Experimental results showed that the proposed detector outperforms detectors based on the spectrogram. The proposed detector is more sensitive to environmental changes because it includes phase information.

In classification, our focus is on finding a robust and sparse representation of whale vocalizations. Because whale vocalizations can be modeled as polynomial phase signals, we can represent the whale calls by their polynomial phase coefficients. In this dissertation, we used the Weyl transform to capture chirp rate information, and used a two dimensional feature set to represent whale vocalizations globally. Experimental results showed that our Weyl feature set outperforms chirplet coefficients and MFCC (Mel Frequency Cepstral Coefficients) when applied to our collected data.

Since whale vocalizations can be represented by polynomial phase coefficients, it is plausible that the signals lie on a manifold parameterized by these coefficients. We also studied the intrinsic structure of high dimensional whale data by exploiting its geometry. Experimental results showed that nonlinear mappings such as Laplacian Eigenmap and ISOMAP outperform linear mappings such as PCA and MDS, suggesting that the whale acoustic data is nonlinear.

We also explored deep learning algorithms on whale acoustic data. We built each layer as convolutions with either a PCA filter bank (PCANet) or a DCT filter bank (DCTNet). With the DCT filter bank, each layer has different a time-frequency scale representation, and from this, one can extract different physical information. Experimental results showed that our PCANet and DCTNet achieve high classification rate on the whale vocalization data set. The word error rate of the DCTNet feature is similar to the MFSC in speech recognition tasks, suggesting that the convolutional network is able to reveal acoustic content of speech signals.

Adaptive Brain-Computer Interface Systems For Communication in People with Severe Neuromuscular Disabilities

Brain-computer interfaces (BCI) have the potential to restore communication or control abilities in individuals with severe neuromuscular limitations, such as those with amyotrophic lateral sclerosis (ALS). The role of a BCI is to extract and decode relevant information that conveys a user's intent directly from brain electro-physiological signals and translate this information into executable commands to control external devices. However, the BCI decision-making process is error-prone due to noisy electro-physiological data, representing the classic problem of efficiently transmitting and receiving information via a noisy communication channel.

This research focuses on P300-based BCIs which rely predominantly on event-related potentials (ERP) that are elicited as a function of a user's uncertainty regarding stimulus events, in either an acoustic or a visual oddball recognition task. The P300-based BCI system enables users to communicate messages from a set of choices by selecting a target character or icon that conveys a desired intent or action. P300-based BCIs have been widely researched as a communication alternative, especially in individuals with ALS who represent a target BCI user population. For the P300-based BCI, repeated data measurements are required to enhance the low signal-to-noise ratio of the elicited ERPs embedded in electroencephalography (EEG) data, in order to improve the accuracy of the target character estimation process. As a result, BCIs have relatively slower speeds when compared to other commercial assistive communication devices, and this limits BCI adoption by their target user population. The goal of this research is to develop algorithms that take into account the physical limitations of the target BCI population to improve the efficiency of ERP-based spellers for real-world communication.

In this work, it is hypothesised that building adaptive capabilities into the BCI framework can potentially give the BCI system the flexibility to improve performance by adjusting system parameters in response to changing user inputs. The research in this work addresses three potential areas for improvement within the P300 speller framework: information optimisation, target character estimation and error correction. The visual interface and its operation control the method by which the ERPs are elicited through the presentation of stimulus events. The parameters of the stimulus presentation paradigm can be modified to modulate and enhance the elicited ERPs. A new stimulus presentation paradigm is developed in order to maximise the information content that is presented to the user by tuning stimulus paradigm parameters to positively affect performance. Internally, the BCI system determines the amount of data to collect and the method by which these data are processed to estimate the user's target character. Algorithms that exploit language information are developed to enhance the target character estimation process and to correct erroneous BCI selections. In addition, a new model-based method to predict BCI performance is developed, an approach which is independent of stimulus presentation paradigm and accounts for dynamic data collection. The studies presented in this work provide evidence that the proposed methods for incorporating adaptive strategies in the three areas have the potential to significantly improve BCI communication rates, and the proposed method for predicting BCI performance provides a reliable means to pre-assess BCI performance without extensive online testing.

The Barriers to the Integration of the Uterine Balloon Tamponade into South Africa and Ghana's Health Systems for the Management of Postpartum Hemorrhage

Background

Postpartum hemorrhage is the most significant contributor to maternal mortality globally, claiming 140,000 lives annually. Postpartum hemorrhage is a leading cause of maternal death in South Africa, with the literature indicating that 80 percent of the postpartum hemorrhage deaths in South Africa are avoidable. Ghana, as of 2010, witnesses 2700 maternal deaths annually, primarily because of poor quality of care in health facilities and services being difficult to access. As per WHO recommendations, uterotonics are integral to treating postpartum hemorrhage as soon as it is diagnosed. In case of persistent bleeding or limited availability of uterotonics, the uterine balloon tamponade (UBT) can be used as a second line of defense. If both these measures are unable to counter the bleeding, providers must perform surgical interventions. Literature on the UBT, as one tool in the protocol to address postpartum hemorrhage, has shown it to have success rates ranging from 60 to 100 percent. Despite the potential to lower the number of postpartum hemorrhage deaths in South Africa and Ghana, the UBT has not been incorporated widely in South Africa and Ghana. The aim of this study is to describe the barriers involved with integrating the UBT into South Africa and Ghana’s health systems to address postpartum hemorrhage.

Methods

The study took place in multiple sites in South Africa (Cape Town, Johannesburg, Durban and Mpumalanga) and in Accra, Ghana. South Africa and Ghana were selected because postpartum hemorrhage contributes greatly to their maternal mortality numbers and there is potential in both countries to lower those rates through greater use of the UBT. A total of 25 participants were interviewed through purposive sampling, snowball sampling and participant referrals, and included various categories of stakeholders integral to the integration process of a medical device. Individual in-depth interviews were used for data collection, with interview questions being tailored to each stakeholder category. The focus of the interviews was on the protocol used to counter postpartum hemorrhage, the frequency with which the UBT is used as part of the protocol, and the process of integrating it into the South Africa and Ghana’s health systems. The data collected were coded using NVivo and analyzed using content analysis.

Results

The barriers to integration of the uterine balloon tamponade to address postpartum hemorrhage in South Africa and Ghana were evident on the political, economic and health delivery levels. The results indicated that the barriers to integration in South Africa included the low recognition of postpartum hemorrhage as a problem, the lack of clarity surrounding the role of the Medicines Control Council as a regulatory body for medical devices, and low awareness of the UBT as an intervention to control postpartum hemorrhage. The barriers in Ghana were the cash constraints experienced by the Ghana Health Services to fund medical devices, a heavy reliance on donors for funding, and the lack of consistent knowledge on processes involving clinical trials for new medical devices in Ghana.

Conclusion

Existing literature on methods to counter postpartum hemorrhage to reduce maternal mortality has focused on and emphasized the efficacy of the UBT. Despite overwhelming evidence supporting the use of the UBT, many health systems across the world, particularly low-income countries, do not have access to the device owing to numerous barriers in integrating the device into obstetric care. This study illustrates the need to focus on incorporating the UBT into health systems for greater availability to health workers and its use as standard of care. Ultimately, this study can be used as a stepping-stone for more research on this subject, providing evidence to influence policymakers to integrate the UBT into their protocols for postpartum hemorrhage response.