Characterisation of adventitious lung sounds in people with dementia

Introduction: Lower Respiratory Tract Infections (LRTIs) are highly prevalent in institutionalised people with dementia, constituting an important cause of morbidity and mortality. Computerised auscultation of Adventitious Lung Sounds (ALS) has shown to be objective and reliable to assess and monitor respiratory diseases, however its application in people with dementia is unknown. Aim: This study characterised ALS (crackles and wheezes) in institutionalised people with dementia. Methods: An exploratory descriptive study, including 6 long-term care institutions was conducted. The sample included a dementia group (DG) of 30 people with dementia and a match healthy group (HG) of 30 elderly people. Socio-demographic and anthropometric data, cognition, type and severity of dementia, cardio-respiratory parameters, balance, mobility and activities and participation were collected. Lung sounds were recorded with a digital stethoscope following Computerised Respiratory Sound Analysis (CORSA) guidelines. Crackles’ location, number (N), frequency (F), two-cycle duration (2CD), initial deflection width (IDW) and largest deflection width (LDW) and wheezes’ number (N), ratio (R) and frequency (F) were analysed per breathing phase. Statistical analyses were performed using PASW Statistics(v.19). Results: There were no significant differences between the two groups in relation to the mean N of crackles during inspiration and expiration in both trachea and thorax. DG trachea crackles had significant higher F during inspiration and lower IDW, 2CD and LDW during expiration when compared with HG. At the thorax, the LDW during inspiration was also significantly lower in the DG. A significant higher N of inspiratory wheezes was found in the HG. Both groups had a low ratio of high frequency wheezes. Conclusion: Computerised analyses of ALS informed on the respiratory system and function of people with dementia and elderly people. Hence, this could be the step towards prevention, early diagnosis and continuous monitoring of respiratory diseases in people with cognitive impairment.

Multiple Roots of Systems of Equations by Repulsion Merit Functions

In this paper we address the problem of computing multiple roots of a system of nonlinear equations through the global optimization of an appropriate merit function. The search procedure for a global minimizer of the merit function is carried out by a metaheuristic, known as harmony search, which does not require any derivative information. The multiple roots of the system are sequentially determined along several iterations of a single run, where the merit function is accordingly modified by penalty terms that aim to create repulsion areas around previously computed minimizers. A repulsion algorithm based on a multiplicative kind penalty function is proposed. Preliminary numerical experiments with a benchmark set of problems show the effectiveness of the proposed method.