Browsing by Author "Fourie, David"

Now showing 1 - 2 of 2
  • Thumbnail Image
    Item
    The effectiveness of a hospital-based intervention for patients with substance-use problems in the Western Cape
    (HMPG, 2012-06) Sorsdahl, Katherine; Stein, Dan J.; Weich, Lize; Fourie, David; Myers, Bronwyn
    ENGLISH ABSTRACT: District hospitals regularly experience a high incidence of substanceuse disorders, but rarely provide interventions. We describe the effectiveness of an intervention developed and implemented by a Western Cape hospital. Patients with probable substance use were referred to an on-site social worker for an alcohol, smoking and substance involvement screening test (ASSIST), a brief motivational intervention and referral to specialist care. At the 3-month followup, the ASSIST was re-administered telephonically. An intervention was received by 127 patients. A significant reduction in substance use was reported in 92 patients who completed a 3-month followup evaluation (p<0.001). Of the 60 patients referred to further care, half entered treatment. We conclude that, with minimal resourcing, it is feasible to administer a brief substance-use intervention for patients attending district hospitals.
  • Thumbnail Image
    Item
    Real time segmentation of heart sounds
    (Stellenbosch : Stellenbosch University, 2015-12) Fourie, David; Booysen, M. J.; Stellenbosch University. Faculty of Engineering. Dept. of Electrical and Electronic Engineering.
    ENGLISH ABSTRACT: The poor state of the healthcare system in South Africa has resulted in unacceptable high levels of infant mortality. Congenital heart disease is one of the main contributions to these high rates of mortality, with the cost of treatment and the availability of specialists being the driving factors. Computer aided auscultation is a technological solution to assist with the diagnosis of the disease. In its current form, computer aided auscultation is unsuitable for continuous patient monitoring. The aim of this thesis is to develop an algorithm that will allow the existing methods of computer aided auscultation to work in real time so they can be used in patient monitoring. Existing methods of identifying the first and second heart sound are limited to offline processing. The algorithm developed in this thesis uses the correlation of the time-frequency coefficients of individual heart sounds to generate a feature vector for each heart sound that can be used to separate the sounds into different groups. To test the performance of the algorithm, 230 heart sounds from normal patients were first manually segmented and then processed with the algorithm. The noise sensitivity of the algorithm was also tested using generated heart sounds. Finally, the real time capability of the algorithm was tested. The testing against sounds for normal patients resulted in a 84.2 % accuracy and an 84.4% hit rate. The synthetic testing showed the system starts to perform badly with a signal to noise ratio lower than -10db. The real time testing of the system showed that the algorithm is fast enough to be used in a real time environment. This thesis concludes that proposed algorithm is suitable for the detection of the first and second heart sounds in real time.