A mathematical model of solute kinetics oriented to the simulation of hemodialysis is presented. It includes a three-compartment model of body fluids (plasma, interstitial and intracellular), a two-compartment description of the main solutes (K+, Na+, Cl-, urea, HCO3-, H+), and acid-base equilibrium through two buffer systems (bicarbonate and noncarbonic buffers). Tentative values for the main model parameters can be given a priori, on the basis of body weight and plasma concentration values measured before beginning the session. The model allows computation of the amount of sodium removed during hemodialysis, and may enable the prediction of plasma volume and osmolarity changes induced by a given sodium concentration profile in the dialysate and by a given ultrafiltration profile. Model predictions are compared with clinical data obtained during 11 different profiled hemodialysis sessions, both with all parameters assigned a priori, and after individual estimation of dialysances and mass-transfer coefficients. In most cases, the agreement between the time pattern of model solute concentrations in plasma and clinical data was satisfactory. In two sessions, blood volume changes were directly measured in the patient, and in both cases the agreement with model predictions was acceptable. The present model can be used to improve the dialysis session taking some characteristics of individual patients into account, in order to minimize intradialytic unbalances (such as hypotension or disequilibrium syndrome).

A nonlinear dynamic morphometric model of breathing mechanics during artificial ventilation is described. On the basis of the Weibel symmetrical representation of the tracheo-bronchial tree, the model accurately accounts for the geometrical and mechanical characteristics of the conductive zone and packs the respiratory zone into a viscoelastic Voigt body. The model also accounts for the main mechanisms limiting expiratory flow (wave speed limitation and viscous flow limitation), in order to reproduce satisfactorily, under dynamic conditions, the expiratory flow limitation phenomenon occurring in normal subjects when the difference between alveolar pressure and tracheal pressure (driving pressure) is high. Several expirations characterized by different levels of driving pressure are simulated and expiratory flow limitation is detected by plotting the isovolume pressure-flow curves. The model is used to study the time course of resistance and total cross-sectional area as well as the ratio of fluid velocity to wave speed (speed index), in conductive airway generations. The results highlight that the coupling between dissipative pressure losses and airway compliance leads to onset of expiratory flow limitation in normal lungs when driving pressure is increased significantly by applying a subatmospheric pressure to the outlet of the ventilator expiratory channel; wave speed limitation becomes predominant at still higher driving pressures.

A mathematical model of solute kinetics for the improvement of hemodialysis treatment is presented. It includes a two-compartment description of the main solutes and a three-compartment model of body fluids (plasma, interstitial and intracellular). The main model parameters can be individually assigned a priori, on the basis of body weight and plasma concentration values measured before beginning the session. Model predictions are compared with clinical data obtained in vivo during 11 different hemodialysis sessions performed on 6 patients with a profiled sodium concentration in the dialysate and a profiled ultrafiltration rate. In all cases, the agreement between the time pattern of model solute concentrations in plasma and the in vivo data proves fairly good as to urea, sodium, chloride, potassium and bicarbonate kinetics. Only in two sessions was blood volume directly measured in the patient, and in both cases the agreement with model predictions was good. In conclusion, the model allows a priori computation of the amount of sodium removed during hemodialysis, and makes it possible to predict the plasma volume changes and plasma osmolarity changes induced by a given sodium concentration profile in the dialysate and by a given ultrafiltration profile. Hence, it can be used to improve clinical tolerance to the dialysis session taking the characteristics of individual patients into account, in order to minimize intradialytic hypotension.

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This paper reviews the works found in the literature in the field of Transportation Mode Detection (TMD) which is a subfield of Activity Recognition aiming at indentifying (i.e. classifying) the mean of transportation a person is using. The solutions found in literature have different characteristics according to the device for which the solution was tailored (smartphones or other systems such as, e.g., GPS loggers) and to the algorithm used for the classification task. This may vary a lot according to the number and type of input used (e.g. accelerations, GPS, maps information or GIS-Geographical Information System information) and to the identified classes of transportation mode. These two aspects are the most relevant to consider when evaluating and comparing the accuracies claimed by each work. A comparison of the works is proposed taking into account the characteristics discussed above. In general the accelerometer is the most widely used sensor for TMD applications, as it limits battery consumption and captures relevant features for detecting motion. Indeed a key challenge in TMD is to detect different motorized classes such as bus, car, train and metro because they share common characteristics (such as e.g. the average speed and accelerations) which make hard identifying suitable features for the classification algorithm. Identifying the "walk" and "stationary" transportation modes is a simpler task because they are characterized by distinct features.