Calibration of Respiratory Inductance Plethysmograph in Preterm Infants With Different Respiratory Conditions

Summary. Respiratory inductance plethysmography (RIP) is a method for respiratory measurements particularly attractive in infants because it is noninvasive and it does not interfere with the airway. RIP calibration remains controversial in neonates, and is particularly difficult in infants with thoraco-abdominal asynchrony or with ventilatory assist. The objective of this study was to evaluate a new RIP calibration method in preterm infants either without respiratory disease, with thoraco-abdominal asynchrony, or with ventilatory support. This method is based on (i) a specifically adapted RIP jacket, (ii) the least squares method to estimate the volume/motion ribcage and abdominal coefficients, and (iii) an individualized filtering method that takes into account individual breathing pattern. The reference flow was recorded with a pneumotachograph. The accuracy of flow reconstruction using the new method was compared to the accuracy of three other calibration methods, with arbitrary fixed RIP coefficients or with coefficients determined according to qualitative diagnostic calibration method principle. Fifteen preterm neonates have been studied; gestational age was (mean AE SD) 31.7 AE 0.8 weeks; birth weight was 1,470 AE 250 g. The respiratory flow determined with the new method had a goodness of fit at least equivalent to the other three methods in the entire group. Moreover, in unfavorable conditions-breathing asynchrony or ventilatory assist-the quality of fit was significantly higher than with the three other methods (P < 0.05, repeated measures ANOVA). Accuracy of tidal volume measurements was at least equivalent to the other methods, and the breath-by-breath differences with reference volumes were lower, although not significantly, than with the other methods. The goodness of fit of the reconstructed RIP flow with this new method-even in unfavorable respiratory conditionsprovides a prerequisite for the study of flow pattern during the neonatal period

Mise au point d'une nouvelle technique d'imagerie fonctionnelle pulmonaire en tomographie quantitative par rayonnement synchroton

GRENOBLE1-BU Médecine pharm. (385162101) / SudocPARIS-BIUP (751062107) / SudocSudocFranceF

La pléthysmographie respiratoire par inductance sans étalonnage (développements en exploration, surveillance et assistance respiratoires)

Les signaux des variations de sections thoracique (Tho) et abdominale (Abd) obtenus par pléthysmographie respiratoire par inductance ont été analysés pour 1) détecter des limitations inspiratoires de débit chez le sujet sain induites à l'aide d'un dispositif mis au point au laboratoire; cette méthode de détection est basée sur l'analyse de la forme du signal Abd, 2) évaluer les variations de volume pulmonaire afin d'en déduire l'évolution des fuites au cours de la nuit, chez des patients ayant des maladies neuromusculaire sous ventilation assistée ; pour faire cette évaluation, les variations d'amplitudes des signaux Tho et Abd ont été utilisées et 3) détecter les déglutitions provoquées par ingestion d'eau chez des personnes âgées ; cette détection utilise le signal débit, obtenu par dérivation du signal volume calculé à partir des signaux Abd et Tho. Aucune de ces trois analyses n'a nécessité l'étalonnage du système de pléthysmographie respiratoire par inductance.GRENOBLE1-BU Sciences (384212103) / SudocSudocFranceF

Variability of end-expiratory lung volume in premature infants.

International audienceBACKGROUND: Analysis of breath-to-breath variability of respiratory characteristics provides information on the respiratory control. In infants, the control of end-expiratory lung volume (EELV) is active and complex, and it can be altered by respiratory disease. The pattern of EELV variability may reflect the behavior of this regulatory system. OBJECTIVES: We aimed to characterize EELV variability in premature infants, and to evaluate variability pattern changes associated with respiratory distress and ventilatory support. METHODS: EELV variations were recorded using inductance plethysmography in 18 infants (gestational age 30-33 weeks) during the first 10 days of life. An autocorrelation analysis was conducted to evaluate the 'EELV memory', i.e. the impact of the characteristics of one breath on the following breaths. RESULTS: In infants without respiratory symptoms, EELV variability was high, with large standard deviations of EELV. Autocorrelation was found to be significant until a median lag of 7 (interquartiles: 4-8) breaths. Autocorrelation was markedly prolonged in patients with respiratory distress or ventilatory support, with a higher number of breath lags with significant autocorrelation (p < 0.01) and higher autocorrelation coefficients (p < 0.05). Conventional assisted ventilation does not re-establish a healthy EELV profile and is associated with lower respiratory variability. CONCLUSIONS: In premature infants, EELV variability pattern is modified by respiratory distress with a prolonged 'EELV memory', which suggests a greater instability of the control of EELV

Multi-sensors acquisition, data fusion, knowledge mining and alarm triggering in health smart homes for elderly people.

International audienceWe deal in this paper with the concept of health smart home (HSH) designed to follow dependent people at home in order to avoid the hospitalisation, limiting hospital sojourns to short acute care or fast specific diagnostic investigations. For elderly people the project of such a HSH has been called AISLE (Apartment with Intelligent Sensors for Longevity Effectiveness). For this purpose, system having three levels of automatic measuring (1) the circadian activity, (2) the vegetative state, and (3) some state variables specific of certain organs involved in precise diseases, has been developed within the framework of a 'Health Integrated Smart Home Information System' (HIS2). HIS2 is an experimental platform for technologic development and clinical evaluation, in order to ensure the medical security and quality of life for patients who need home based medical monitoring. Location sensors are placed in each room of the HIS2, allowing the monitoring of patient's successive daily activity phases within the patient's home environment. We proceed with a sampling in an hourly schedule to detect weak variations of the nycthemeral rhythms. Based on numerous measurements, we establish a mean value with confidence limits of activity variables in normal behaviour permitting to detect for example a sudden abnormal event (like a fall) as well as a chronic pathologic activity (like a pollakiuria), allowing us to define a canonical domain within which the patient's activity is qualified to be 'predictable'. Alerts are set off if the patient's activity deviates from a predictable canonical domain. Moreover, we can follow the cardio-respiratory state by measuring the intensity of the respiratory sinusal arrhythmia in order to quantify the integrity of the bulbar vegetative system, and we finally propose to carefully watch abnormal symptoms like arterial pressure or presence of plasma proteins in the expired air flow for early detecting respectively hypertension or pulmonary oedema

Multi-sensors acquisition, data fusion, knowledge mining and alarm triggering in health smart homes for elderly people.

International audienceWe deal in this paper with the concept of health smart home (HSH) designed to follow dependent people at home in order to avoid the hospitalisation, limiting hospital sojourns to short acute care or fast specific diagnostic investigations. For elderly people the project of such a HSH has been called AISLE (Apartment with Intelligent Sensors for Longevity Effectiveness). For this purpose, system having three levels of automatic measuring (1) the circadian activity, (2) the vegetative state, and (3) some state variables specific of certain organs involved in precise diseases, has been developed within the framework of a 'Health Integrated Smart Home Information System' (HIS2). HIS2 is an experimental platform for technologic development and clinical evaluation, in order to ensure the medical security and quality of life for patients who need home based medical monitoring. Location sensors are placed in each room of the HIS2, allowing the monitoring of patient's successive daily activity phases within the patient's home environment. We proceed with a sampling in an hourly schedule to detect weak variations of the nycthemeral rhythms. Based on numerous measurements, we establish a mean value with confidence limits of activity variables in normal behaviour permitting to detect for example a sudden abnormal event (like a fall) as well as a chronic pathologic activity (like a pollakiuria), allowing us to define a canonical domain within which the patient's activity is qualified to be 'predictable'. Alerts are set off if the patient's activity deviates from a predictable canonical domain. Moreover, we can follow the cardio-respiratory state by measuring the intensity of the respiratory sinusal arrhythmia in order to quantify the integrity of the bulbar vegetative system, and we finally propose to carefully watch abnormal symptoms like arterial pressure or presence of plasma proteins in the expired air flow for early detecting respectively hypertension or pulmonary oedema