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Epidemiological data on prevalence and incidence of chronic hypoparathyroidism are still scarce. This study aimed to establish prevalence of chronic hypoparathyroidism and incidence of surgical hypoparathyroidism using the analysis of electronic anonymous public health care database. Data referred to a 5-year period (2009–2013, Region of Tuscany, Italy, as a sample representative of the whole Mediterranean/European population, estimated mean population: 3,750,000 inhabitants) were retrieved by the analysis of pharmaceutical distribution dataset, containing data related to drugs reimbursed by public health system, hospital discharge and procedures codes, and ICD9 exemption codes for chronic diseases. The application of a specific algorithm was applied to indirectly identify people with chronic hypoparathyroidism as assuming chronic therapy with active vitamin D metabolites (AVDM). The number of people taking AVDM for a period equal to or longer than 6 months till the end of the study period, with ICD9 exemption code for hypoparathyroidism, and with a disease-related discharge code were identified. Within this restricted group, patients with chronic kidney disease and osteoporosis were excluded. The indirect estimate of chronic hypoparathyroidism in a European Mediterranean subpopulation by means of the analysis of chronic therapy with AVDM was 27/100,000 inhabitants (female:male ratio = 2.2:1), with a mean age of 63.5 ± 16.7 years. The risk of developing hypoparathyroidism after neck surgery was 1.5%. While the epidemiological approaches based on disease code and hospital discharge code greatly underestimates the prevalence of hypoparathyroidism, the indirect estimate of this disease through the analysis of prescriptions of AVDM in a European region is in line with the results of studies performed in other regions of the world.

The vestibular system plays a crucial role in the sense of balance and spatial orientation in mammals. It is a sensory system that detects both rotational and translational motion of the head, via its semicircular canals and otoliths respectively. In this work, we propose a real-time hardware model of an artificial vestibular system, implemented using a custom neuromorphic Very Large Scale Integration (VLSI) multi-neuron chip interfaced to a commercial Inertial Measurement Unit (IMU). The artificial vestibular system is realized with spiking neurons that reproduce the responses of biological hair cells present in the real semicircular canals and otholitic organs. We demonstrate the real-time performance of the hybrid analog-digital system and characterize its response properties, presenting measurements of a successful encoding of angular velocities as well as linear accelerations. As an application, we realized a novel implementation of a recurrent integrator network capable of keeping track of the current angular position. The experimental results provided validate the hardware implementation via comparisons with a detailed computational neuroscience model. In addition to being an ideal tool for developing bio-inspired robotic technologies, this work provides a basis for developing a complete low-power neuromorphic vestibular system which integrates the hardware model of the neural signal processing pathway described with custom bio-mimetic gyroscopic sensors, exploiting neuromorphic principles in both mechanical and electronic aspects.

Psychological research has found that human perception of randomness is biased. In particular, people consistently show the overalternating bias: they rate binary sequences of symbols (such as Heads and Tails in coin flipping) with an excess of alternation as more random than prescribed by the normative criteria of Shannon's entropy. Within data mining for medical applications, Marcellin proposed an asymmetric measure of entropy that can be ideal to account for such bias and to quantify subjective randomness. We fitted Marcellin's entropy and Renyi's entropy (a generalized form of uncertainty measure comprising many different kinds of entropies) to experimental data found in the literature with the Differential Evolution algorithm. We observed a better fit for Marcellin's entropy compared to Renyi's entropy. The fitted asymmetric entropy measure also showed good predictive properties when applied to different datasets of randomness-related tasks. We concluded that Marcellin's entropy can be a parsimonious and effective measure of subjective randomness that can be useful in psychological research about randomness perception.

This work aims at implementing an event driven neuromorphic vestibular sensor using a commercial Inertial Measurement Unit (IMU) and a custom analog VLSI neuromorphic chip. We investigate a model of the vestibular sensor that emulates the spiking responses of hair cells in the semicircular canals. We calibrate the neuromorphic chip to match the parameters of a neuroscientific computational model. Experimental results validating the hardware implementation and the calibration procedure are presented.