Action selection is extremely important, particularly when the accomplishment of competitive tasks may require access to limited motor resources. The spontaneous exploration of the world plays a fundamental role in the development of this capacity, providing subjects with an increasingly diverse set of opportunities to acquire, practice and refine the understanding of action-outcome connection. The computational modeling literature proposed a number of specific mechanisms for autonomous agents to discover and target interesting outcomes: intrinsic motivations hold a central importance among those mechanisms. Unfortunately, the study of the acquisition of action-outcome relation was mostly carried out with experiments involving extrinsic tasks, either based on rewards or on predefined task goals. This work presents a new experimental paradigm to study the effect of intrinsic motivation on action-outcome relation learning and action selection during free exploration of the world. Three- and four-year-old children were observed during the free exploration of a new toy: half of them were allowed to develop the knowledge concerning its functioning; the other half were not allowed to learn anything. The knowledge acquired during the free exploration of the toy was subsequently assessed and compared.

Recent advances in wearable sensor technologies for motion capture have produced devices, mainly based on magneto and inertial measurement units (M-IMU), that are now suitable for out-of-the-lab use with children. In fact, the reduced size, weight and the wireless connectivity meet the requirement of minimum obtrusivity and give scientists the possibility to analyze children's motion in daily life contexts. Typical use of magneto and inertial measurement units (M-IMU) motion capture systems is based on attaching a sensing unit to each body segment of interest. The correct use of this setup requires a specific calibration methodology that allows mapping measurements from the sensors' frames of reference into useful kinematic information in the human limbs' frames of reference. The present work addresses this specific issue, presenting a calibration protocol to capture the kinematics of the upper limbs and thorax in typically developing (TD) children. The proposed method allows the construction, on each body segment, of a meaningful system of coordinates that are representative of real physiological motions and that are referred to as functional frames (FFs). We will also present a novel cost function for the Levenberg-Marquardt algorithm, to retrieve the rotation matrices between each sensor frame (SF) and the corresponding FF. Reported results on a group of 40 children suggest that the method is repeatable and reliable, opening the way to the extensive use of this technology for out-of-the-lab motion capture in children.

Nutritive Sucking (NS) is a highly organized process that is essential for infants' feeding during the first six months of their life. It requires the complex coordination of sucking, swallowing and breathing. The infant's inability to perform a safe and successful oral feeding can be an early detector of immaturity of the Central Nervous System (CNS). Even though the importance of early sucking measures has been confirmed over the years, the need for standardized instrumental assessment tools still exists. Clinicians would benefit from specifically designed devices to assess oral feeding ability in their routine clinical monitoring and decision-making process. This work is a review of the main instrumental solutions developed to assess an infant's NS behavior, with a detailed survey of the main quantities and indices measured and/or estimated to characterize sucking behavior skills and their development. The adopted sensing measuring systems will be described, and their main advantages and weaknesses will be discussed, taking into account their application to clinical practice, or to at-home monitoring as post-discharge assessment tools. Finally, the study will highlight the most suitable sensing solutions and give some prompts for further research.

A bidirectional, low cost flowmeter for neonatal artificial ventilation, suitable for application in mono-patient breathing circuits, is described here. The sensing element consists of two nominally identical bipolar junction transistors employed as hot bodies. The sensor working principle is based on the convective heat transfer between the transistors, heated by Joule phenomenon, and the colder hitting fluid which represents the measurand. The proposed design allows the sensor to discriminate flow direction. Static calibration has been carried out in a range of flowrate values (from -8 L·min(-1) up to +8 L L·min(-1)) covering the ones employed in neonatal ventilation, at different pipe diameters (ie., 10 mm and 30 mm) and collector currents (i.e., 500 mA, 300 mA, and 100 mA) in order to assess the influence of these two parameters on sensor's response. Results show that the configuration with a pipe diameter of 10 mm at the highest collector current guarantees the highest sensitivity (i.e., 763 mV/Lmin1 at low flowrate ± 1 L-min(-1)) and ensures the minimum dead space (2 mL vs 18 mL for 30 mm of diameter). On the other hand, the 30 mm pipe diameter allows extending the range of measurement (up to ±6 L-min 1 vs ±3.5 L· min(-1) at 10 mm), and improving both the discrimination threshold (<;0.1 L·min-(1)) and the symmetry of response. These characteristics together with the low dead space and low cost foster its application to neonatal ventilation.

Motion capture based on magneto-inertial sensors is a technology enabling data collection in unstructured environments, allowing "out of the lab" motion analysis. This technology is a good candidate for motion analysis of children thanks to the reduced weight and size as well as the use of wireless communication that has improved its wearability and reduced its obtrusivity. A key issue in the application of such technology for motion analysis is its calibration, i.e. a process that allows mapping orientation information from each sensor to a physiological reference frame. To date, even if there are several calibration procedures available for adults, no specific calibration procedures have been developed for children. This work addresses this specific issue presenting a calibration procedure for motion capture of thorax and upper limbs on healthy children. Reported results suggest comparable performance with similar studies on adults and emphasize some critical issues, opening the way to further improvements.

The Sucking Efficiency (SEF) is one of the main parameters used to monitor and assess the sucking pattern development in infants. Since Nutritive Sucking (NS) is one of the earliest motor activity performed by infants, its objective monitoring may allow to assess neurological and motor development of newborns. This work proposes a new ecological and low-cost method for SEF monitoring, specifically designed for feeding bottles. The methodology, based on the measure of the hydrostatic pressure exerted by the liquid at the teat base, is presented and experimentally validated at different operative conditions. Results show how the proposed method allows to estimate the minimum volume an infant ingests during a burst of sucks with a relative error within the range of [3-7]% depending on the inclination of the liquid reservoir