2 resultados para 730110 Respiratory system and diseases (incl. asthma)

em Instituto Politécnico do Porto, Portugal


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This paper presents the measurement, frequency-response modeling and identification, and the corresponding impulse time response of the human respiratory impedance and admittance. The investigated adult patient groups were healthy, diagnosed with chronic obstructive pulmonary disease and kyphoscoliosis, respectively. The investigated children patient groups were healthy, diagnosed with asthma and cystic fibrosis, respectively. Fractional order (FO) models are identified on the measured impedance to quantify the respiratory mechanical properties. Two methods are presented for obtaining and simulating the time-domain impulse response from FO models of the respiratory admittance: (i) the classical pole-zero interpolation proposed by Oustaloup in the early 90s, and (ii) the inverse discrete Fourier Transform (DFT). The results of the identified FO models for the respiratory admittance are presented by means of their average values for each group of patients. Consequently, the impulse time response calculated from the frequency response of the averaged FO models is given by means of the two methods mentioned above. Our results indicate that both methods provide similar impulse response data. However, we suggest that the inverse DFT is a more suitable alternative to the high order transfer functions obtained using the classical Oustaloup filter. Additionally, a power law model is fitted on the impulse response data, emphasizing the intrinsic fractal dynamics of the respiratory system.

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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.