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The purpose of this study was to evaluate the differences in the circadian variations of blood pressure (BP) and heart rate (HR) among three subject groups (hypertensive, normal/high normal and optimal blood pressure). The ambulatory BP and HR of 385 subjects, without clinical evidence of hypertension-related complications, were acquired using a Holter Blood Pressure Monitor and their circadian patterns were analyzed. Systolic, Diastolic and Mean BP showed four different well-defined trends in specific time intervals of the day, similar for the three BP measures and among the three subject groups. Both BP and HR signals presented a decrease between 10:00 and 14:30 and from 19:00 to 2:00 and an increase from 5:00 to 10:00. Between 14:30 and 19:00, BP and HR presented an opposite relationship with decreasing HR and increasing BP, not yet reported in the literature. The behaviors of BP and HR were well approximated in each of the four periods by linear trends in all the three subject groups. On the contrary, in the period between 2:00 and 5:00 both BP and HR showed a quite constant trend. Results support the hypothesis of an independent vagal control during 24-h in respect of HR and BP mean levels, the latter depending on the specific subject group. Moreover, linear approximation in the identified four intervals could be used to quantify the circadian changes for all kind of subjects.

Owing to the large inter-subject variability, early post-stroke prognosis is challenging, and objective biomarkers that can provide further prognostic information are still needed. The relation between quantitative EEG parameters in pre-thrombolysis hyper-acute phase and outcomes has still to be investigated. Hence, possible correlations between early EEG biomarkers, measured on bedside wireless EEG, and short-term/long-term functional and morphological outcomes were investigated in thrombolysis-treated strokes. EEG with a wireless device was performed in 20 patients with hyper-acute (

Motor-Imagery based BCI (MI-BCI) neurorehabilitation can improve locomotor ability and reduce the deficit symptoms in Parkinson's Disease patients. Advanced Motor-Imagery BCI methods are needed to overcome the accuracy and time-related MI BCI calibration challenges in such patients. In this study, we proposed a Multi-session FBCSP (msFBCSP) based on inter-session transfer learning and we investigated its performance compared to the single-session based FBSCP. The main result of this study is the significantly improved accuracy obtained by proposed msFBCSP compared to single-session FBCSP in PD patients (median 81.3%, range 41.2-100.0% vs median 61.1%, range 25.0-100.0%, respectively; p

Background Sublingual varices (SV) are dilatations of tortuous veins that increased with age. Previous studies showed that this pathology could be correlated to some risk factors such as hypertension, age, gender and diabetes mellitus. In this study we evaluated, on a large number of subjects, the relationship between SV and different grades of hypertension as well as some risk factors extending the analysis to new risk factors such as dyslipidemia, obesity and antihypertensive therapy, modelling a possible dependence of SV on all these factors. Methods In the study 1008 subjects, 284 with and 724 without SV, were examined. The blood pressure was measured in office condition and, to exclude subjects with white coat syndrome or masked hypertension, also using a 24 h Holter pressure monitor. Hypertensive subjects were divided in resistant, drugs controlled (compensated) and patients with prior unknown hypertension (new diagnosed) groups. The presence or absence of SV as well as of the risk factors was assessed clinically. We tested the influence of age on the presence of SV by using the chi-square test and the relation between each risk factor and SV by the Cochran–Mantel–Haenszel test. Finally, we carried out a multivariate regression tree analysis in order to predict the presence of SV. Results We confirmed the influence of age on SV and found a significant relationship between SV and both the compensated and resistant hypertension grades. We highlighted a relationship between SV and dyslipidemia in subjects with new diagnosed hypertension, and between SV and smoking in subjects with compensated hypertension grade. The regression tree showed a classification accuracy of about 75% using as variables hypertension grades, age and antihypertensive treatment. Conclusions We confirmed the SV dependence on age, resistant hypertension and smoking, highlighting a new association with dyslipidemia in new diagnosed hypertensive subjects and new relations depending on the hypertension grades. Thus, the SV inspection could be used to suggest a lipidologist as well as a hypertension specialist visit for a pharmacological and pressure check particularly in subjects presenting SV and dyslipidemia. However, further parameters are to be considered to improve the sensitivity of the prognostic tree model.

Ischemic heart disease (IHD), particularly in its chronic stable form, is a subtle pathology due to its silent behavior before developing in unstable angina, myocardial infarction or sudden cardiac death. Machine learning techniques applied to parameters extracted form heart rate variability (HRV) signal seem to be a valuable support in the early diagnosis of some cardiac diseases. However, so far, IHD patients were identified using Artificial Neural Networks (ANNs) applied to a limited number of HRV parameters and only to very few subjects. In this study, we used several linear and non-linear HRV parameters applied to ANNs, in order to confirm these results on a large cohort of 965 sample of subjects and to identify which features could discriminate IHD patients with high accuracy. By using principal component analysis and stepwise regression, we reduced the original 17 parameters to five, used as inputs, for a series of ANNs. The highest accuracy of 82% was achieved using meanRR, LFn, SD1, gender and age parameters and two hidden neurons.

The diagnosis of heart diseases is a difficult task generally addressed by an appropriate examination of patients’ clinical data. Recently, the use of heart rate variability (HRV) analysis as well as of some machine learning algorithms, has proved to be a valuable support in the diagnosis process. However, till now, ischemic heart disease (IHD) has been diagnosed on the basis of Artificial Neural Networks (ANN) applied only to signs, symptoms and sequential ECG and coronary angiography, an invasive tool, while could be probably identified in a non-invasive way by using parameters extracted from HRV, a signal easily obtained from the ECG. In this study, 18 non-invasive features (age, gender, left ventricular ejection fraction and 15 obtained from HRV) of 243 subjects (156 normal subjects and 87 IHD patients) were used to train and validate a series of several ANN, different for number of input and hidden nodes. The best result was obtained using 7 input parameters and 7 hidden nodes with an accuracy of 98.9% and 82% for the training and validation dataset, respectively.

Background The analysis of the circadian rhythm of heart rate variability (HRV) represents a relevant physiological tool to assess the vagal system. However, the influence of age (mostly >75 years) on HRV is not widely known. Aims The aim of this study was to evaluate the influence of age on HRV, particularly in the elderly and to identify a model of this relationship. The study was carried out by examining linear and nonlinear parameters extracted from HRV, including individuals over 75 years for which there is no research available. Methods Data from 140 healthy subjects were sex matched and divided into young (young group: 15-39 years old), adult (adult group: 40-64 years old) and senior (senior group: 65-90 years old) groups. 24-h Holter monitoring was used and several HRV parameters were extracted from time, and spectral and nonlinear analyses were examined. Results Time-domain parameters, mainly standard deviation of the NN interval (SDNN) and number of successive differences of intervals which differ by more than 50 ms, presented significant differences between the young group and the other two groups during the 24-h period, while normalized spectral parameters (LFn, HFn and low frequency/high frequency), as well as nonlinear parameters, mainly β exponent and fractal dimension, showed significant difference between the senior group and the other two groups. All these parameters showed a similar circadian rhythm with significant differences between the mean day and night values, especially in young and adult group cohorts. Moreover, a parabolic relationship between these parameters and age was highlighted with an opposite trend over about 60 years compared with younger people. Conclusion A progressive physiological autonomic imbalance is present in ageing. The inverse trend in the relation between HRV parameters and age found in the senior group could be mainly due to a faster fluctuation of RR. This should be considered when studying changes in the cardiac autonomic nervous control.

EEG has a central role in the diagnosis of epileptiform abnormalities helpful in diagnosing epilepsy. Since irregularities are random and sporadic events, easily activated in the initial phase of sleep but difficult to observe in a standard EEG examination, sleep deprivation is a frequent condition to be used. Thus, in this study the EEG monitoring of 44 subjects, 14 without epilepsy and 30 with epilepsy, afferent to the IRCCS Centro Neurolesi “Bonino Pulejo” of Messina were examined after sleep deprivation the day before performing the registration. EEGs were recorded according to the international setting system using nineteen channels. The normalized power spectral densities in delta (2–4 Hz), theta (4–8 Hz), alpha (8–13 Hz) and beta (13–30 Hz) band were computed and the non-linear parameters such as beta exponent, fractal dimension and zero crossing were considered. The differences between the sleep and awake were significant in almost all the channels in the beta band and in posterior areas for beta exponent, fractal dimension and zero crossing in normal subjects. In epileptic patients they were significant in all the channels in the delta band and for the non-linear parameters, and in several ones in theta and beta bands. Even if in posterior areas all the spectral and the non-linear parameters showed different values between epileptic and healthy subjects, no significant differences were found. The results suggest that analysis of spectral power as well as of complexity, obtained by non-linear parameters, could be used to identify differences between healthy and epileptic patients.

Management of Type 1 Diabetes (T1D) in the context of exercise or sports competition still represents a great challenge for athletes living with this disease, due to the wide excursions in blood glucose level with increased risk of life threatening hypoglycemia. Recently, an algorithm called ECRES has been developed to estimate patient-exercise tailored carbohydrates (CHO) supplement required to maintain safe blood glucose levels during physical activity. This method estimates a CHO supplement based on the patient’s habitual therapy, the specific patient’s insulin sensitivity and the overall amount of CHO oxidized during the specific exercise. The last is based on the glucose pulse relation, i.e. the relation between heart rate (HR) and CHO oxidation rate, already studied in sedentary and moderately-trained subjects, but not in well-trained athletes. This study aimed to model the glucose pulse relation during exercise in type 1 highly trained diabetic patients and in healthy subjects. HR, oxygen consumption and carbon dioxide production were acquired breath-by-breath in seven T1D and seven well-matched healthy highly-trained subjects at four different exercise intensity levels, as well as at rest. Results showed a linear CHOox-HR relation (CHOox = 0.76 · %HRmax - 19.6; n = 70, R2 = 0.78) with no significant difference between the T1D and healthy athletes (p-value = 0.11). In conclusion, results of this study can be implemented in an updated version of the ECRES algorithm allowing an easy estimate of CHO supplement also in highly trained subjects. This useful support system can enhance the self-management of glycaemia during the training sessions of athletic patients throughout mHealth technologies.

In the present study, 30 right-handed participants randomly performed one of three motor neurorehabilitation paradigms: action observation (AO), motor imagery (MI) and combined action observation and motor imagery (AO+MI) of the right arm and hand movement. Resting state electroencephalography (EEG) was acquired for 5 min before and immediately after the motor paradigms session. EEG was recorded from 10 sites over sensorimotor areas, and the average power was calculated for left (FC3, C3, C1, C5, CP3) and right (FC4, C4, C2, C6, CP4) regions in the spectral bands: delta, theta, alpha, mu, low and high beta. Our main finding demonstrates that delta, theta and mu activity decreased significantly on the contralateral regions during MI, while low beta increased significantly. Except for the mu band, the same changes were observed on the ipsilateral side, where delta and theta decreased significantly, while low beta became significantly higher. No relevant effects were observed for AO or combined AO and MI. These findings demonstrate a rapid effect of MI on cortical modulation in sensorimotor areas which is revealed by changes in resting state oscillatory activity and suggest an interesting interplay between MI and AO. The presented findings may be relevant for choosing a proper protocol for clinical motor neurorehabilitation approaches.

Objective: Ischemic heart disease (IHD), in its chronic stable form, is a subtle pathology due to its silent behavior before developing in unstable angina, myocardial infarction or sudden cardiac death. The clinical assessment is based on typical symptoms and finally confirmed, invasively, by coronary angiography. Recently, heart rate variability (HRV) analysis as well as some machine learning algorithms like artificial neural networks (ANNs) were used to identify cardiovascular arrhythmias and, only in few cases, to classify IHD segments in a limited number of subjects. The goal of this study was the identification of the ANN structure and the HRV parameters producing the best performance to identify IHD patients in a non-invasive way, validating the results on a large sample of subjects. Moreover, we examined the influence of a clinical non-invasive parameter, the left ventricular ejection fraction (LVEF), on the classification performance. Approach: To this aim, we extracted several linear and non-linear parameters from 24 h RR signal, considering both normal and ectopic beats (heart rate total variability), of 251 normal and 245 IHD subjects, matched by age and gender. ANNs using several different combinations of these parameters together with age and gender were tested. For each ANN, we varied the number of hidden neurons from 2 to 7 and simulated 100 times, changing randomly the training and test dataset. Main results: The HRTV parameters showed significant greater variability in IHD than in normal subjects. The ANN applied to mean RR, LF, LF/HF, beta exponent, SD2 together with age and gender reached a maximum accuracy of 71.8% and, by adding as input LVEF, an accuracy of 79.8%. Significance: The study provides a deep insight into how a combination of some HRTV parameters and LVEF could be exploited to reliably detect the presence of subjects affected by IHD.

Blood Pressure (BP) and Heart Rate (HR) provide information on clin-ical condition along 24h. Both signals present circadian changes due to sympa-thetic/parasympathetic control system that influence the relationship between them. Moreover, also the gender could modify this relation, acting on both con-trol systems. Some studies, using office measurements examined the BP/HR re-lation, highlighting a direct association between the two variables, linked to sus-pected coronary heart disease. Nevertheless, till now such relation has not been studied yet using ambulatory technique that is known to lead to additional prog-nostic information about cardiovascular risks. In order to examine in a more ac-curate way this relation, in this work we evaluate the influence of gender on the BP/HR relationship by using hour-to-hour 24h ambulatory measurements. Data coming from 122 female and 50 male normotensive subjects were recorded using a Holter Blood Pressure Monitor and the parameters of the linear regression fit-ting BP/HR were calculated. Results confirmed those obtained in previous stud-ies using punctual office measures in males and underlined a significant relation between Diastolic BP and HR during each hour of the day in females; a different trend in the BP/HR relation between genders was found only during night-time. Moreover, the circadian rhythm of BP/HR is similar in both genders but with different values of HR and BP at different times of the day.

The accurate identification and prediction of cerebral infarct evolution and clinical outcome are of paramount importance in acute ischemic stroke management. Neuroimaging in acute stroke is mandatory to establish the feasibility of reperfusion therapy, but it is not practical to assess the continuous evolution of brain ischemia. EEG could be an applicable instrument to perform functional monitoring in the hyper-acute phase. EEG activity during ischemic stroke has been widely studied in sub-acute and post-acute phase of ischemic stroke. However, only few studies have focused on the early phase of brain ischemia. The aim of this study conducted at the stroke unit was to investigate stroke-related EEG changes during the earliest phase of ischemic stroke within 4.5 h from symptom onset and to correlate these data with neurological deficit in terms of NIHSS score. We studied 12 patients with ischemic stroke, who underwent EEG recordings within 4.5 h from symptom onset. The EEG signals acquisition was performed bedside without delaying reperfusion treatment, using @64 channels Wi-Fi Be Plus LTM amplifier and 19 channel 10–20 Ag/AgCl electrodes wireless prewired headset. The main finding of this study is a significant positive correlation between stroke-related EEG changes measured by DAR and DTABR parameters and the neurological deficit measured by NIHSS score, during the earliest phase of ischemic stroke. The results of this study highlight the importance of EEG as complementary tool in the assessment of stroke severity and its potential role in acute decision-making and monitoring.

In-line free propagation phase-contrast synchrotron tomography of the lungs has been shown to provide superior image quality compared with attenuation-based computed tomography (CT) in small-animal studies. The present study was performed to prove the applicability on a human-patient scale using a chest phantom with ventilated fresh porcine lungs. Local areas of interest were imaged with a pixel size of 100 µm, yielding a high-resolution depiction of anatomical hallmarks of healthy lungs and artificial lung nodules. Details like fine spiculations into surrounding alveolar spaces were shown on a micrometre scale. Minor differences in artificial lung nodule density were detected by phase retrieval. Since we only applied a fraction of the X-ray dose used for clinical high-resolution CT scans, it is believed that this approach may become applicable to the detailed assessment of focal lung lesions in patients in the future.

Electrophysiological examinations constitute objective and accurate measures of cerebral function. They can be recorded at bedside, which is of major value in intensive care units. The objective of the present study considers the linear and non-linear analysis of resting electroencephalography (EEG) signals as predictors for poor outcome and differences between brain regions. We studied 24 brain injured patients (trauma, cerebral anoxia, intracranial haemorrhage, cerebral infections) and 12 healthy controls and compared their EEG power spectra, the zero crossing and fractal dimension splitting the brain in four regions: left hemisphere, right hemisphere, anterior cortex, posterior cortex. In this study early linear and non-linear parameters showed the ability to predict recovery of communicative skills in brain injured patients at 6 months.

Physical activity is a keystone of a healthy lifestyle as well as of management of patients with type 1 diabetes. The risk of exercise-induced hypoglycemia, however, is a great challenge for these patients. The glycemic response to exercise depends upon several factors concerning the patient him/herself (eg, therapy, glycemic control, training level) and the characteristics of the exercise performed. Only in-depth knowledge of these factors will allow to develop individualized strategies minimizing the risk of hypoglycemia. The main factors affecting the exercise-induced hypoglycemia in patients with T1D have been analyzed, including the effects of insulin concentration. A model is discussed, which has the potential to become the basis for providing patients with individualized suggestions to keep constant glucose levels on each exercise occasion.

Nutrition and physical activity are important parts of a healthy lifestyle and management of diabetes. Regular moderate-intensity physical activity in type 1 diabetes patients can enhance insulin sensitivity, reduce the risk of cardiovascular disease and improve psychological well-being. Nevertheless, the risk of exercise-induced hypoglycemia is a great challenge for patients with type 1 diabetes and represents an important barrier to physical activity in these patients. Recently, an algorithm called ECRES has been developed with the aim of estimating, depending on patient’s own therapy and specific physical activity, the glucose supplement required by the patient to maintain safe blood glucose levels. The aim of this study is to compare the ECRES algorithm to classical quantitative approach. Therefore, we measured and compared glycaemia in 23 patients (mean age: 43 ± 12 years) during 1-h treadmill walk/run maintaining heart rate at 65% of his/her theoretical maximum value for age. For each subject two separate tests were performed: with carbohydrates supplement estimated by ECRES algorithm and by classical approach, respectively. The average heart rate observed during exercise (average progression speed: 5.8 ± 0.8 km/h at 4.2 ± 2.3% inclination) was 111.5 ± 9.4 bpm. Glycaemia measured by portable glucometer showed no significant differences between tests managed with ECRES algorithm and with classical approach, both before (149 ± 47 vs. 128 ± 41 mg/dL) and at the end of the performed exercise (134 ± 66 vs. 138 ± 54 mg/dL). The ECRES algorithm, however, estimated a significantly lower amount of carbohydrate needed for physical activity as compared to that suggested by the classical approach (14.8 ± 12.0 g vs. 23.4 ± 4.7 g; p < 0.05), while maintaining patients’ blood glucose within optimal clinical limits. The study results confirmed the validity of the estimates made by the ECRES algorithm.

mHealth is a growing field of research, concerning the great potentialities of mobile technology as a tool for self-management of chronic conditions. Physical activity greatly influences blood glucose levels, therefore for type 1 diabetes patients is important to adapt their diet and therapy in order to avoid exercise-induced hyperglycemia and hypoglycemia. The later represents one of the major barriers to physical activity and it limits volitional exercise in type 1 diabetes patients. However, there is lack of stand-alone mobile tool that provides the support to the patient in order to perform physical activity and exercise under safe glycaemia levels. Recently, Exercise Carbohydrate Requirement Estimating Software (ECRES) algorithm was proposed to calculate patient-exercise tailored glucose supplement required to maintain safe blood glucose levels during physical activity. The objective of this study was to develop a mobile App which implements an individualized predictive system for blood glucose in type 1 diabetes, depending on exercise strength. Its usability and accuracy were compared to original ECRES estimating software in 15 volunteer subjects. The developed application provides relevant feedback to patients on carbohydrate intake needed to carry out a planned physical activity, in a safe manner. Furthermore, application provides other important features, for self-management of this chronicity, reported in recent literature: entry of blood glucose values, display of diabetes-related data, such as blood glucose readings and their analysis, carbohydrate intake, insulin doses, and easy data export. The application also incorporates food atlas in order to facilitate carbohydrates calculation. The results of the test showed that developed application accurately implements ECRES algorithm and the self-management features. In conclusion, proposed App could be a useful support tool to diabetes type 1 patents. The results should be confirmed in larger clinical study.

Background: Mild (MCI) and Subjective Cognitive Impairment (SCI) are conditions at risk of developing Alzheimer’s disease (AD). Differential between normal aging at early stages can be really challenging; available biomarkers need to be combined and can be quite invasive and expensive. Objective: The aim of this pilot study is to examine possible EEG alterations in MCI and SCI compared to controls, analyzing if a cognitive task could highlight early AD hallmarks. Method: We recruited 11 MCI, 8 SCI and 7 healthy subjects as controls (CS), all matched for age and education. Neuropsychological assessment and EEG recording, at resting state and during a mental memory task, were performed. Classical spectral measures and nonlinear parameters were used to characterize EEGs. Results: During cognitive task, α-band power reduction was found predominantly in frontal regions in SCI and CS, diffused to all regions in MCI; moreover, decreased EEG complexity was found in SCI compared to controls. The α -band power attenuation restricted to frontal regions in SCI during a free recall task (involving frontal areas), suggests that MCI patients compensate for encoding deficit by activating different brain networks to perform the same task. Furthermore, EEG complexity reduction - that has been found already in SCI - could be a possible early hallmark of AD. Conclusion: This study draws attention on the importance of nonlinear approach in EEG analysis and the potential role of cognitive task in highlighting EEG alterations at very early stages of cognitive impairment; EEG could therefore have a practical impact on dementia diagnosis.

Purpose: to compare the rebound tonometer ICare® (RT) with the Goldmann applanation tonometer (GAT) in cataract surgery and to assess the influence of central corneal thickness (CCT) on intraocular pressure (IOP) measurements. Design: retrospective, comparative study. Methods: a total of 472 patients underwent IOP measurement using RT (time 0 = RTa). GAT IOP measurement was performed 5 minutes later, followed by a second RT IOP measurement after other 5 minutes (RTa + 10 min = RTb). CCT was obtained by ultrasound pachymetry. In 106 patients IOP was measured by means of RT and GAT before clear corneal cataract surgery (RT1 and GAT1) and at one day postoperatively (RT2 and GAT2). Results: RT IOP values > 5 mmHg were overestimated, while RT IOP values < 15 mmHg were underestimated. Every 100 µm of CCT an increase of 0.97 mmHg and 0.33 mmHg was found for RT and GAT respectively. The difference between RT1 and RT2, GAT1 and GAT2, RT1 and GAT1 was not statistically significant; while the difference between RT2 and GAT2 was statistically significant (p < 0.04). The difference between RTa and RTb was not statistically significant whereas the difference between RTa and GAT and RTb and GAT was statistically significant (p < 0.001). Conclusion: our results showed a good agreement between measurements obtained with RT and GAT in pre and postoperative cataract surgery, although a significant statistically difference was found between RT and GAT measurements performed postoperatively. Moreover, CCT is a parameter to be considered for the IOP measurement, especially for values obtained with RT.

Non-clinical hospital services to support clinical activities, such as the sterilization service and clinical engineering, are an important technology asset in healthcare, and require constant improvement aimed to reduce economic burden and increase quality. The selection of the most effective healthcare service to adopt in a healthcare facility is a multi-criteria decision problem that classical Health Technology Assessment, being mostly focused on medicines, vaccines and medical devices, cannot easily address. Here we present a methodology based on Multi-Criteria Decision Analysis allowing a full assessment of non-clinical hospital services and supporting the selection of the most suitable solution in a certain environment. The methodology involves two different panels of experts: the first one includes international professionals and is aimed at selecting the assessment criteria that are relevant to the target service; the second one is a local panel whose members know the needs and peculiarities of the specific healthcare facility. This approach allows the final decision makers to take into account changes and constraints of their environment, but examining criteria that are internationally recognized as of interest. The proposed methodology, tested in a real context of an Italian Local Health Authority, is versatile and can be applied in any context, even out of the healthcare domain, especially if data in the literature are not sufficient to allow comparisons with similar services in different settings. Abbreviations: HTA, Health Technology Assessment; NCHS, Non-Clinical Hospital Services; CSSD, Central Sterile Services Department; MCDA, Multi-Criteria Decision Analysis; ASM, Local Health

This paper focuses on the relationship between blood pressure (BP) and heart rate (HR) during 24 hours in 423 normotensive (NO) and 205 hypertensive (HE) subjects. Although considerable knowledge has been gained about BP and HR signals, their relationship over 24 hours has never been completely described. By using a Holter Blood Pressure Monitor, it was possible to record BP and HR for 24 hours. Systolic, Diastolic and Mean BP in both NO and HE subjects showed four different time intervals presenting well-defined trends The results demonstrated that changes in HR present closely parallel changes in BP with a marked reduction of both signals during nocturnal rest. On the contrary, in the period between 15:30 and 19:30, HR and BP showed an inverse relationship with decreasing heart rate and increasing blood pressure.

The aim of this study was to highlight the advantages that propagation-based phase-contrast computed tomography (PB-CT) with synchrotron radiation can provide in breast cancer diagnostics. For the first time, a fresh and intact mastectomy sample from a 60 year old patient was scanned on the IMBL beamline at the Australian Synchrotron in PB-CT mode and reconstructed. The clinical picture was described and characterized by an experienced breast radiologist, who underlined the advantages of providing diagnosis on a PB-CT volume rather than conventional two-dimensional modalities. Subsequently, the image quality was assessed by 11 breast radiologists and medical imaging experts using a radiological scoring system. The results indicate that, with the radiation dose delivered to the sample being equal, the accuracy of a diagnosis made on PB-CT images is significantly higher than one using conventional techniques.

Circadian rhythm is a characteristic behavior of human physiology and it is known that, in healthy subjects, blood pressure (BP) increases during the day and decreases during the night, as a result of sleep-wake changes. Some studies highlighted that female had lower office BP values than male and this should be considered for define the threshold of hypertension. With the introduction of the Holter Blood Pressure Measurement, it has been possible to record the blood pressure for 24 hours. This innovation allowed to analyze the circadian Blood pressure pattern (CBPP) and some studies identified the differences between normotensives and hypertensives subjects. In this study, we examined the circadian pattern in positive drug responsive hypertensive patients in respect of negative ones and of normotensive subjects and the differences due to gender. The results demonstrated that positive drug responsive hypertensive patients had the same circadian blood pressure pattern as normotensives. Moreover, the difference in circadian blood pressure values between male and female was about 2-4 mmHg.

Handwriting difficulties represent a common cause of under-achievement in children’s education and low self-esteem in daily life. Since proper handwriting teaching methods can reduce dysgraphia problems, the evaluation of these methods represents an important task. In this paper a methodology to compare visual and spatio-temporal teaching methods is proposed and applied in order to assess the influence of different teaching approaches on handwriting performance, via big data analysis techniques. Data was collected from children in their final years of primary school, when cursive writing skills have typically been mastered. Qualitative and kinematic parameters were considered: the former were calculated by means of quality checklists, whereas the latter were automatically extracted from digitizing tablet acquisitions. Results showed significant differences in pupils’ handwriting depending on the teaching method applied.

Many different treatment approaches have been ap- plied for handwriting remediation in school-aged children. The effects of these treatments are usually evaluated by using ad-hoc checklists as well as some standard test protocols like Movement ABC tests, Visual-Motor Integration (V.M.I.) tests, etc. Recently, digitizing tablets have allowed the study of kinematic character- istics of handwriting and a series of parameters were estimated on cursive writing of Italian children. In this paper, the influence of a new rehabilitation protocol (Terzi’s method) on kinematics of cursive writing was evaluated. The analysis was carried out on 22 nonproficient handwriting children, attending primary or secondary school, which undertook a series of three exercises, with and without linguistic concerns. A set of kinematic parameters was calculated before and after the rehabilitation process. The results showed that Terzi’s rehabilitation program is capable of producing a significant velocity increase in the test without linguistic involve- ment, whereas a significant slowdown in the stroke realization was present in the other tasks. The effectiveness of Terzi’s rehabilitation program was proved by significant improvements in the V.M.I. test, in the Movement ABC test as well as in writing legibility (evaluated by checklist).

Purpose: To analyze the changes in ganglion cell complex and peripapillary retinal nerve fiber layer thickness, in central macular thickness and choroidal thickness on spectral domain optical coherence tomography in patients with neovascular age-related macular degeneration treated with intravitreal ranibizumab injections. Methods: All consecutive patients with untreated neovascular age-related macular degeneration received loading phase of three monthly intravitreal ranibizumab, followed by retreatments on a pro re nata protocol for 12 months. Primary outcome: changes in ganglion cell complex and retinal nerve fiber layer at the end of follow-up. Secondary outcome: changes in best-corrected visual acuity, central macular thickness, and choroidal thickness at the end of follow-up. Choroidal thickness was measured at 500 m, 1000 m, and 1,500 m intervals nasally, temporally, superiorly, and inferiorly to the fovea, respectively, on horizontal and vertical line scans centered on the fovea. Results: Twenty-four eyes were included. Ganglion cell complex and peripapillary retinal nerve fiber layer thickness did not show statistically significant changes through 12 months (55.6 ± 18.5 and 81.9 ± 9.9 m at baseline, 52.7 ± 19.3 and 84.6 ± 15.5 m at month 12, P > 0.05). Central macular thickness showed progressive decrease from baseline to month 12, with maximum reduction at month 3 (P < 0.001). Statistically significant reduction in choroidal thickness was registered in the nasal 500, 1000, and 1,500 m from the fovea, corresponding to the papillomacular region (from 169.6 ± 45.3 to 153.9 ± 46.9, P < 0.001). Conclusion: Intravitreal ranibizumab injections did not affect retinal nerve fiber layer and ganglion cell complex thickness in 1-year follow-up. Choroidal thickness in papillomacular area and central macular thickness was significantly reduced at the end of treatment. Further studies, with larger sample, longer follow-up, and greater number of injections, are warranted.

Handwriting is the result of a process in which linguistic, psychomotor and biomechanical factors interact with physical maturation, cognitive development and learning. Digital tablets, which record the writing in real time, allow a kinematic analysis of written trace: the implemented algorithms analyze parameters as length, duration and speed of the components (trace between two pen-lifts) and strokes (trace between two minima of curvilinear velocity). The purpose of this work is to fill, at least for Italy, the lack of normative data on typical handwriting processes. This cross-sectional study will present data on 218 right-handed and Italian mother-tongue students, attending classes from 2nd to 8th grade. They performed specific tasks (tests of writing speed; transcription of a sentence accurately vs. speedily) by a digital tablet. The analysis showed many changes of the considered parameters across the classes, as in the horizontal, curvilinear mean and peak velocities of components and strokes, with higher values in the last years of schooling and a parallel decrease in the number of strokes/letter (improvement of automation). In conclusion, some of these parameters are useful for studying development and learning of writing and their values can be used as references to evaluate samples with different characteristics.

When considering the acquisition of experimental synchrotron radiation (SR) X-ray CT data, the reconstruction workflow cannot be limited to the essential computational steps of flat fielding and filtered back projection (FBP). More refined image processing is often required, usually to compensate artifacts and enhance the quality of the reconstructed images. In principle, it would be desirable to optimize the reconstruction workflow at the facility during the experiment (beamtime). However, several practical factors affect the image reconstruction part of the experiment and users are likely to conclude the beamtime with sub-optimal reconstructed images. Through an example of application, this article presents SYRMEP Tomo Project (STP), an open-source software tool conceived to let users design custom CT reconstruction workflows. STP has been designed for post-beamtime (off-line use) and for a new reconstruction of past archived data at user’s home institution where simple computing resources are available. Releases of the software can be downloaded at the Elettra Scientific Computing group GitHub repository https://github.com/ElettraSciComp/STP-Gui.

Over the last two decades, the advances in ventilatormodalities and technology have revolutionized the mechanicalventilation process. The new anesthesia ventilatorsconstitute adaptations of machines previously used in intensivecare units. In this line, the FLOW-i anesthesia ventilator hasbeen recently developed based on the SERVO-i intensive careventilator platform. However, the FLOW-i behavior has notbeen so far tested in a leaking circuit.In this study we tested FLOW-i, and compared to SERVO-i,in volume-, pressure-, and pressure-regulated volumecontrolledmodes (VC, PC, and PRVC, respectively) withgas flows of 6, 1, and 0.3 L/min, booth in airtight and leakingcircuit.In the airtight system both ventilators behaved similarly.FLOW-i delivered preset tidal volume and maintained ventilationand circuit pressure at the same levels independently ofventilatory mode or fresh gas flow rate. In the face of a leakingcircuit and in PC mode FLOW-i and SERVO-i delivered to thelung model higher tidal volumes (about 90% and 85% of setvalues, respectively) than in VC and PRVC modes. Additionally,delivered tidal volume did not differ from 6 to 0.3 L/min offresh gas flow.

High frequency percussive ventilation (HFPV) is a non-conventional ventilatory modality which has proven very effective and safe in patients with acute respiratory failure. HFPV ventilator measures airway pressure that represents the sum of the endotracheal tube pressure drop and the tracheal pressure dissipated to inflate a lung. The estimation of the difference between the peak airway and tracheal pressure ∆Pp may be very useful to the clinician to avoid lung injury. The aim of this study is to provide a comprehensive solution for estimation of ∆Pp in adult endotracheal tubes, by developing a flow-independent model, based on endotracheal tube size, ventilator set parameters (i.e. peak pressures, pulsatile frequencies) and patient’s respiratory system resistance and compliance. The model for the estimation of ∆Pp was determined by using the Least Absolute Shrinkage and Selection Operator (LASSO) regularized least-squares regression technique. The identified model was successively assessed on test data set.

SummarySolutions for improving management of chronic conditions are under the attention of healthcare systems, due to the increasing prevalence caused by demographic change and better survival, and the relevant impact on healthcare expenditures. The objective of this study was to propose a comprehensive architecture of a mHealth system aimed at boosting the active and informed participation of patients in their care process, while at the same time overcoming the current technical and psychological/clinical issues highlighted by the existing literature.After having studied the current challenges outlined in the literature, both in terms of technological and human requirements, we focused our attention on some specific psychological aspects with a view to providing patients with a comprehensive and personalized solution. Our approach has been reinforced through the results of a preliminary assessment we conducted on 22 patients with chronic conditions. The main goal of such an assessment was to provide a preliminary understanding of their needs in a real context, both in terms of self-awareness and of their predisposition toward the use of IT solutions.According to the specific needs and features, such as mindfulness and gamification, which were identified through the literature and the preliminary assessment, we designed a comprehensive open architecture able to provide a tailor-made solution linked to specific individuals’ needs.The present study represents the preliminary step towards the development of a solution aimed at enhancing patients’ actual perception and encouraging self-management and selfawareness for a better lifestyle. Future work regards further identification of pathology-related needs and requirements through focus groups including all stakeholders in order to describe the architecture and functionality in greater detail.Citation: Lasorsa I, D’Antrassi P, Ajčević M, Stellato K, Di Lenarda A, Marceglia S, Accardo A. Personalized support for chronic conditions: a novel approach for enhancing self-management and improving lifestyle

Direct and indirect economic costs related to chronic diseases are increasing in Europe due to the aging of population. One of the most challenging goals is to improve the quality of life of patients affected by chronic conditions, and enhance their self-management. In this paper, we propose a novel architecture of a scalable solution, based on mobile tools, aimed to keep patients with chronic diseases away from acute episodes, to improve their quality of life and, consequently, to reduce their economic impact. Our solution aims to provide patients with a personalized tool for improving self-management, and it supports both patients and clinicians in decision-making through the implementation of two different Decision Support Systems. Moreover, the proposed architecture takes into account the interoperability and, particularly, the compliance with data transfer protocols (e.g., BT4/LE, ANT+, ISO/IEEE 11073) to ensure integration with existing devices, and with the semantic web approaches and standards related to the content and structure of the information (e.g., HL7, ICD-10 and openEHR) to ensure correct sharing of information with hospital information systems, and classification of patient behaviors (Coelition). The solution will be implemented and validated in future study.

Today, many hospitals have a running enterprise picture archiving and communication system (PACS) and their administrators should have the tools to measure the system activity and, in particular, how much it is used. The information would be valuable for decision-makers to address asset management and the development of policies for its correct utilization and eventually start training initiatives to get the best in resource utilization and operators’ satisfaction. On the economic side, a quantitative method to measure the usage of the workstations would be desirable to better redistribute existing resources and plan the purchase of new ones. The paper exploits in an unconventional way the potential of the IHE Audit Trail and Node Authentication (ATNA) profile: it uses the data generated in order to safeguard the security of patient data and to retrieve information about the workload of each PACS workstation. The method uses the traces recorded, according to the profile, for each access to image data and to calculate how much each station is used. The results, constituted by measures of the frequency of PACS station usage suitably classified and presented according to a convenient format for decision-makers, are encouraging. In the time of the spending review, the careful management of available resources is the top priority for a healthcare organization. Thanks to our work, a common medium such as the ATNA profile appears a very useful resource for purposes other than those for which it was born. This avoids additional investments in management tools and allows optimization of resources at no cost. © 2016 Society for Imaging Informatics in Medicine.

It is widely demonstrated that phase contrast imaging yields better contrast resolution on soft-tissue with respect to conventional absorption radiography. In this feasibility study an application of synchrotron radiation imaging for arthritic bone erosion is presented. In particular two phase-contrast imaging techniques are investigated and analyzed in order to differentiate different aspects of bone microarchitecture and cartilages, with the ultimate aim to demonstrate the translation of the technique in in-vivo studies.

Along the last years, the number of HRV studies has been widely grown. The computation of HRV linear and non-linear parameters allows the quantification of the cardiac frequency modulation and of the possible link between them and different pathologies. In the literature, significant variations of HRV linear and non-linear parameters are described, with the focus on age related changes in healthy subjects. The aim of this study is to evaluate the possible presence of age related changes in HRV parameters in congestive heart failure (CHF) patients. The RR time series extracted from 80 CHF patients, divided by age into two groups, have been accurately analyzed. The results point out a linear influence of age on characteristic parameters extracted from these patients; the behaviors of these parameters are opposite to the literature results obtained in healthy subjects. We hypothesize that this discrepancy may be due to the RR data selection and to their pre-processing phase as well as to some clinical factors as the neuro hormonal imbalance characteristic of the CHF disease that often produces a sympathetic activation.

We present the outcomes of combined feasibility studies carried out at Elettra and Australian Synchrotron to evaluate novel protocols for threedimensional (3D) mammographic phase contrast imaging. A custom designed plastic phantom and some tissue samples have been studied at diverse resolution scales and experimental conditions. Several computed tomography (CT) reconstruction algorithms with different pre-processing and post-processing steps have been considered. Special attention was paid to the effect of phase retrieval on the diagnostic value of the reconstructed images. The images were quantitatively evaluated using objective quality indices in comparison with subjective assessments performed by three experienced radiologists and one pathologist. We show that the propagation-based phase-contrast imaging (PBI) leads to substantial improvement to the contrast-to-noise and to the intrinsic quality of the reconstructed CT images compared with conventional techniques as well as to an important reduction of the delivered doses, thus opening the way to clinical implementations.

Purpose TO describe Goldmann applanation tonometer (GAT) and rebound tonometer (RT) agreement in measuring intraocular pressure (IOP) in glaucomatous and ocular hypertensive (OH) eyes and to evaluate central corneal thickness (CCT) influence on RT readings. Methods A total of 347 eyes were enrolled and IOP measured between 9 and 11 am. Rebound tonometry was performed first (RT1), followed by 3 consecutive GAT measurements and by a second RT reading (RT2), within a 5-minute span. Mean IOP (±SD) values were compared by means of paired t-test. Agreement between GAT and RT1 (test 1) and RT2 (test 2) was evaluated with Bland-Altman method, whereas a linear function described the relationship between CCT and IOP taken with RT. Results Mean IOP (±SD) taken with RT1, GAT, and RT2 was 18.1±4.3, 15.6±3.3, and 16.3±3.9 mmHg, respectively. Readings were within ±3 mmHg in 63.7% and 86.7% of eyes for test 1 and 2, respectively. A significant (pConclusions When used first, RT significantly overestimated IOP compared with GAT. Differences became clinically negligible when RT was used immediately after GAT. Repeated applanation tonometry may explain this observation. Agreement between instruments was acceptable for low IOP, but worsened with increasing IOP values. RT is significantly influenced by CCT. Goldmann applanation tonometer and RT should not be used interchangeably.

Purpose To demonstrate in a two-compartment heterogeneous mechanical model of the lung how different loads applied to one compartment, while the other is kept constant, would modify gas distribution between the two pathways under high-frequency percussive ventilation (HFPV). Additionally, these results were compared with those generated in the same model by pressure-controlled ventilation (PCV). Methods Analysis was based on a Siemens lung simulator, representing a fixed branch of the system with an elastance equal to 45 cmH2O/L and a resistance of 20 cmH2O/L/s, and a single-compartment lung simulator, representing a variable pathway of the model, presenting three elastic loads varying between 35 and 85 cmH2O/L and three resistive loads varying between 5 and 50 cmH2O/L/s. Each simulator represented one compartment of the model connected to a central airway that was ventilated with either a volumetric diffusive respirator (VDR-4; Percussionaire Corporation, Sandpoint, ID, USA) or a Siemens Servo 900c ventilator. Flow and pressures were measured in each branch of the model under nine conditions representing the combinations of three elastic and three resistive loads (variable branch) while the loads in the other pathway were kept constant. Results HFPV was able to avoid hyperinflation and reduce tidal volume in a bicompartmental heterogeneous lung model. Under HFPV, gas distribution between the two compartments was not constrained by their time constants. PCV yielded gas distribution as determined by the time constant of each compartment. Conclusions HFPV accommodated volume distribution without overinflating compartments with low time constants, thus possibly presenting a potential protective behavior in mechanically heterogeneous lungs.

The approach to evaluate handwriting quality is usually based on the use of check-lists and scales regarding qualitative, postural and pen grasp aspects that are detected during task execution and through a visual analysis of written texts. Nevertheless, this approach lacks of objectivity and all the parameters have the same weight. On the other hand, objective evaluation methods focusing on the qualitative approach are available in the literature. For example, the analytic hierarchy process (AHP) is a technique that allows to organise complex relationships between elements into a system based on subjective judgements. In this paper we present an innovative evaluation scale, based on a new neuromotor model of handwriting production, which associates a specific weight to each parameter during the calculation of a quality score. The scale allows teachers, speech therapists and all those interested in diagnostic and rehabilitative phase to identify subjects who show some handwriting difficulties compared to the average performance of their peers. The new approach was applied to two groups of students, following different teaching methods, in order to evaluate suitably weighted aspects of handwriting quality.

The common practice of Clinical Engineering Services (CESs) is to manage separately Electric Safety Checks (ESCs), Quality Controls (QCs) and Preventive Maintenance (PM). However, protocols related to these activities are partially overlapped. This results in a redundancy of maintenance steps producing a waste of time. Furthermore, outsourced CESs are in charge of managing activities in hospitals located in different areas with the same team. Thus the distance to be covered by technicians from an area to another one in order to reach the equipment represents a waste of time. This problem can be solved by merging ESC, QC and PM into a unique operative protocol we call Single Planned Activity (SPA). This implies the development of new maintenance plans and the human resources redistribution, and clinical engineers are in charge of this task. In order to assess its feasibility, we developed a comprehensive method that consists of the analysis of technician’s workload and of the algorithm able to generate a monthly maintenance plan. The method reprograms the previous planned activities through the available human resources redistribution in a more efficient way, according to their actual workload. The method has been tested in an Italian CES and proved to be useful for clinical engineers.

Heart rate variability (HRV) has been widely investigated in a variety of clinical conditions, but few studies have assessed the changes in the heart rate with regard to different congestive heart failure (CHF) etiologies. The aim of this work was to characterize the heart rate variability of patients affected by CHF caused by dilated cardiomyopathy, ischemic heart disease or other different CHF etiologies, in comparison to that of healthy subjects. The parameters adopted for analysis were the power spectral density in the very low, low and high frequency bands, the power-law β exponent and the SD1 and SD2 index-es of the Poincaré plot. Results showed significant changes related to etiology especially in the very low and high frequency bands and in the β exponent values, thus encouraging the future development of a classifier for the discrimination of the different CHF etiologies.

Heart Rate Variability (HRV) has been studied in a variety of clinical situations in order to quantify the modulations in the heart rate associated to different pathological conditions. Nevertheless, significant changes in spectral and some nonlinear parameters of the HRV were reported also in normal subjects, depending on age and gender. The aim of this work was to quantify the age-related differences in other nonlinear parameters, particularly in the fractal dimension, of the HRV of healthy subjects and to compare the results with the changes showed by spectral measures. The RR time series extracted by the Holter monitoring of 60 healthy subjects, divided into three groups similar for both age and gender, were accurately analyzed. The results only partially revealed age-related changes both in the spectral and fractal HRV measures, underlining the need to carefully examine the RR data selection and the pre-processing phases.

Lean management constitutes an emerging approach in the healthcare context, in order to increase quality of care and reduce costs. Nevertheless, literature shows the lack of a standardized method, especially in healthcare, due to the complexity of the involved processes. This paper proposes an innovative method for standardizing the lean management approach in Healthcare, in order to reduce wastes particularly in Hospitals. The integration of different techniques, such as IDEF0, and GQM, used in the process management is proposed, in order to let the overall method reproducible and repeatable. The application and feasibility of the method has been studied in an Italian Hospital.

High-frequency percussive ventilation (HFPV) is a non-conventional ventilatory modality which has proven effective and safe in patients with acute respiratory failure. HFPV associates the beneficial aspects of conventional mechanical ventilation with those of high-frequency ventilation. At the present time, HFPV ventilator provides only analog airway pressure waveform and digital output of peak and the mean airway pressures. Currently, the latter is the only parameter that allows an indirect comparison between conventional volume controlled ventilation (VCV) and HFPV treatment set up. The aim of this pilot study was to measure in vivo the main respiratory parameters, in order to use them for a new bedside monitoring of HFPV treatment. For such purpose pressure, flow and volume were measured in five patients undergoing HFPV. Lung resistance and compliance were estimated using multiple linear regression method on Dorkin high frequency pulmonary model, while endotracheal tube pressure drop was estimated using Blasius model. The results of this study showed that during the transition from conventional VCV to HFPV the tidal volume delivery can significantly change, although the same mean airway pressure was setup. Thus the volume measurement is clinically important during HFPV treatment. The validity of the Dorkin model during HFPV was confirmed in vivo. Moreover, the estimation of resistance, compliance and endotracheal tube pressure drop through non-invasive method represents an important step towards personalized HFPV treatment.

The aim of this study is to fulfill the need of reengineering the Clinical Engineering Service in an Italian ASL (Local Health Authority) located in Sardinia, in accordance with the Italian regulations for healthcare. Even if methods for processes redesigning in healthcare organizations are available in the literature, there are no recent evidences of their application in Clinical Engineering Services. Among the multi-criteria techniques, in this work PAPRIKA was used, since it is an easy-to-use and intuitive method for multi- criteria decision making, based on decision-makers’ preferences. We identified the decision makers’ criteria to be fulfilled and four different preference levels for each criterion, as inputs of the method. Moreover four different scenarios were identified and, for each scenario and criterion, the decision makers selected the most suitable level. In order to reduce the number of pairwise comparisons among the preference levels associated to the identified criteria, the online software 1000minds, implementing the PAPRIKA method, was used. After 460 steps, the software allowed to rank the four possible scenarios. The application of the method allowed choosing the best solution for the ASL and it represents a good way for decision making, even though the number of questions is still high.

X-ray computed tomography (CT) experiments performed at synchrotron radiation fa- cilities require adequate computing and storage resources due to the large amount of acquired and reconstructed data produced. To satisfy the heterogeneous needs of beamline users, flexible solu- tions are also required. Moreover, the growing demand of quantitative image analysis impose an easy integration between the CT reconstruction process and the subsequent feature extraction step. This paper presents some of the software solutions adopted by the SYRMEP beamline of the Italian synchrotron radiation facility Elettra. By using the enhanced version of the reconstruction software here presented as well as data reduction and data analysis tools, beamline users can easily imple- ment an integrated and comprehensive approach to the digital image processing and image analysis required by a tomography-oriented scientific workflow.

High-frequency percussive ventilation (HFPV) is a non-conventional ventilatory modality which has proven highly effective in patients with severe gas exchange impairment. HFPV delivers a series of high-frequency sub-tidal volumes, by pulsatile flow, in combination with low-frequency breathing cycles. Currently, the mean airway pressure is the only parameter that allows an indirect comparison between conventional volume controlled ventilation and HFPV treatment set up. In the clinical practice, HFPV is not an intuitive ventilatory modality and the absence of valuable information during the treatment as delivered tidal volume, respiratory system resistance and compliance produces disaffection among the physicians. The aim of this study was to tailor HFPV treatment setup, avoiding under and overtreatment, using new bedside measurements of the main respiratory parameters. For this purpose pressure, flow and volume were measured in six patients undergoing HFPV. Respiratory system resistance and compliance were estimated using multiple linear regression method on Dorkin’s high frequency model, while endotracheal tube pressure drop was estimated using Blasius’s model. This study offers a new approach for HFPV treatment tailoring in accordance with protective ventilatory strategy and optimization of the alveolar ecruitment. The possibility to measure respiratory parameters has opened a new horizon in clinical monitoring during this particular ventilator strategy, improving the beneficial effect of HFPV and minimizing iatrogenic lung damage.

Heart rate variability (HRV) decrease has been described in patients with obstructive sleep apnea syndrome (OSAS). Nevertheless, time and frequency domain methods commonly used for HRV analysis are considered not completely reliable in case of respiratory and arrhythmic disorders. On the contrary, the nonlinear approach may supply powerful and promising tools to give a better insight of the autonomic control in OSAS. In this study, power-law β exponent, fractal dimension and approximate entropy parameters are calculated on the whole night recordings of 77 OSAS patients. The relationships between each pair of the parameters are quantified and discussed, also in comparison to the theoretical models.