Pensions reforms, workforce ageing and firm-provided welfare

This paper investigates the impact of an exogenous increase in the legal retirement age on the firms’ propensity to provide welfare services voluntarily to their employees. To this purpose we exploit a unique dataset derived from the Employers and Employees Survey, conducted by the National Institute for Public Policies Analysis (Inapp) in 2015 on a large and representative sample of Italian firms. By referring to the existing sociological and economic literature we make the hypothesis that a sudden increase in the share of older workers may motivate the employers to establish welfare schemes as a way to cope with an ageing workforce. The results obtained from different regression models show that firms which, as a consequence of the Law 214/2011 (the so-called “Fornero pension reform”), were forced to give up previously planned hirings increased the probability of providing welfare services at the workplace. This result also holds if propensity score matching methods are used in order to control for sample selection issues

Development of a novel wearable system for real-time measurement of the inter-foot distance during gait

The combination of magneto-inertial measurement unit (MIMU) and distance sensor (DS) represents smart solution for evaluating the distance between feet during various daily-life activities. In particular, when analyzing gait, the latter technology can be used for estimating the instantaneous or average distance between selected points of the feet (IFD) during mid-swing and mid-stance phases. The aim of this preliminary work is twofold: a) to develop and validate a novel wearable system for the measurement of the IFD during gait; b) to investigate the optimal positioning of the DS on the foot. Preliminary results showed that the innovative wearable system can be effectively used for accurately measuring the IFD during gait. Interestingly, the accuracy of the IFD estimation is highly affected by the position of the DS on the foot

A wearable solution for accurate step detection based on the direct measurement of the inter-foot distance

Accurate step detection is crucial for the estimation of gait spatio-temporal parameters. Although several step detection methods based on the use of inertial measurement units (IMUs) have been successfully proposed, they may not perform adequately when the foot is dragged while walking, when walking aids are used, or when walking at low speed. The aim of this study was to test an original step-detection method, the inter-foot distance step counter (IFOD), based on the direct measurement of the distance between feet. Gait data were recorded using a wearable prototype system (SWING2DS), which integrates an IMU and two time-of-flight distance sensors (DSs). The system was attached to the medial side of the right foot with one DS positioned close to the forefoot (FOREDS) and the other close to the rearfoot (REARDS). Sixteen healthy adults were asked to walk over ground for two minutes along a loop, including both rectilinear and curvilinear portions, during two experimental sessions. The accuracy of the IFOD step counter was assessed using a stereo-photogrammetric system as gold standard. The best performance was obtained for REARDS with an accuracy higher than 99.8% for the instrumented foot step and 88.8% for the non-instrumented foot step during both rectilinear and curvilinear walks. Key features of the IFOD step counter are that it is possible to detect both right and left steps by instrumenting one foot only and that it does not rely on foot impact dynamics. The IFOD step counter can be combined with existing IMU-based methods for increasing step-detection accuracy

A context based model for sentiment analysis in twitter for the italian language

Studi recenti per la Sentiment Analysis in Twitter hanno tentato di creare modelli per caratterizzare la polarit´a di un tweet osservando ciascun messaggio in isolamento. In realt`a, i tweet fanno parte di conversazioni, la cui natura pu`o essere sfruttata per migliorare la qualit`a dell’analisi da parte di sistemi automatici. In (Vanzo et al., 2014) `e stato proposto un modello basato sulla classificazione di sequenze per la caratterizzazione della polarit` a dei tweet, che sfrutta il contesto in cui il messaggio `e immerso. In questo lavoro, si vuole verificare l’applicabilit`a di tale metodologia anche per la lingua Italiana.Recent works on Sentiment Analysis over Twitter leverage the idea that the sentiment depends on a single incoming tweet. However, tweets are plunged into streams of posts, thus making available a wider context. The contribution of this information has been recently investigated for the English language by modeling the polarity detection as a sequential classification task over streams of tweets (Vanzo et al., 2014). Here, we want to verify the applicability of this method even for a morphological richer language, i.e. Italian

An objective assessment to investigate the impact of turning angle on freezing of gait in Parkinson's disease

Freezing of gait (FoG) is often described in subjects with Parkinson's disease (PD) as a sudden inability to continue the forward walking progression. FoG occurs most often during turning, especially at sharp angles. Here, we investigated 180 and 360 degrees turns in two groups: PD subjects reporting FoG (FoG+), and PD subjects without FoG (FoG-). Forty-three subjects (25 FoG+, 18 FoG-) wore an inertial sensor on their back while walking back and forth continuously for 2 min (reversing direction with a 180° turn), and while turning in place for 1 min (alternating 360° turning in opposite directions). Objective measures (turn duration, peak velocity, jerkiness and range of acceleration) were computed during the turns and compared across FoG+ and FoG-groups. Results showed that FoG+ compared to FoG-took significantly a longer time to complete 360° turns than 180° turns. A significant lower turn peak velocity, higher jerkiness and an increased range of medio-lateral acceleration was also found in FoG+. Significant differences between the two groups across the two turning tasks validated the hypothesis that sharper turns might cause higher instability in FoG+ compared to FoG-

A proximity sensor for the measurement of the inter-foot distance in static and dynamic tasks

Measuring the base of support is of paramount importance in determining human stability during gait or balance tests. While wearable inertial sensors have been successfully employed to quantify numerous gait parameters (velocity, stride length, etc), they could not be used to estimate quantities related to the feet relative position. Thus, alternative technological solutions need to be investigated. Some attempts have been made by combining light intensity infrared or ultrasounds sensors with inertial measurement units. Lately, the Infrared Time-of-Flight technology (IR-ToF) has become popular for measuring distances. IR-ToF sensor measures the time an electromagnetic wave needs to travel a distance. The aim of this work was to investigate the feasibility of the use of an IR-ToF sensor for estimating the inter-foot distance (IFD) in both static and dynamic tasks. Very accurate IFD estimates were obtained during Static (MAE%=3.3%) and Oscillation (MAE%=4.1%) conditions, while larger errors during Gait trials (MAE%=19.8%)

Robust Spoken Language Understanding for House Service Robots

Service robotics has been growing significantly in thelast years, leading to several research results and to a numberof consumer products. One of the essential features of theserobotic platforms is represented by the ability of interactingwith users through natural language. Spoken commands canbe processed by a Spoken Language Understanding chain, inorder to obtain the desired behavior of the robot. The entrypoint of such a process is represented by an Automatic SpeechRecognition (ASR) module, that provides a list of transcriptionsfor a given spoken utterance. Although several well-performingASR engines are available off-the-shelf, they operate in a generalpurpose setting. Hence, they may be not well suited in therecognition of utterances given to robots in specific domains. Inthis work, we propose a practical yet robust strategy to re-ranklists of transcriptions. This approach improves the quality of ASRsystems in situated scenarios, i.e., the transcription of roboticcommands. The proposed method relies upon evidences derivedby a semantic grammar with semantic actions, designed tomodel typical commands expressed in scenarios that are specificto human service robotics. The outcomes obtained throughan experimental evaluation show that the approach is able toeffectively outperform the ASR baseline, obtained by selectingthe first transcription suggested by the AS

A discriminative approach to grounded spoken language understanding in interactive robotics

Spoken Language Understanding in Interactive Robotics provides computational models of human-machine communication based on the vocal input. However, robots operate in specific environments and the correct interpretation of the spoken sentences depends on the physical, cognitive and linguistic aspects triggered by the operational environment. Grounded language processing should exploit both the physical constraints of the context as well as knowledge assumptions of the robot. These include the subjective perception of the environment that explicitly affects linguistic reasoning. In this work, a standard linguistic pipeline for semantic parsing is extended toward a form of perceptually informed natural language processing that combines discriminative learning and distributional semantics. Empirical results achieve up to a 40% of relative error reduction

Static and dynamic accuracy of an innovative miniaturized wearable platform for short range distance measurements for human movement applications

Magneto-inertial measurement units (MIMU) are a suitable solution to assess human motor performance both indoors and outdoors. However, relevant quantities such as step width and base of support, which play an important role in gait stability, cannot be directly measured using MIMU alone. To overcome this limitation, we developed a wearable platform specifically designed for human movement analysis applications, which integrates a MIMU and an Infrared Time-of-Flight proximity sensor (IR-ToF), allowing for the estimate of inter-object distance. We proposed a thorough testing protocol for evaluating the IR-ToF sensor performances under experimental conditions resembling those encountered during gait. In particular, we tested the sensor performance for different (i) target colors; (ii) sensor-target distances (up to 200 mm) and (iii) sensor-target angles of incidence (AoI) (up to 60°). Both static and dynamic conditions were analyzed. A pendulum, simulating the oscillation of a human leg, was used to generate highly repeatable oscillations with a maximum angular velocity of 6 rad/s. Results showed that the IR-ToF proximity sensor was not sensitive to variations of both distance and target color (except for black). Conversely, a relationship between error magnitude and AoI values was found. For AoI equal to 0°, the IR-ToF sensor performed equally well both in static and dynamic acquisitions with a distance mean absolute error <1.5 mm. Errors increased up to 3.6 mm (static) and 11.9 mm (dynamic) for AoI equal to ±30°, and up to 7.8 mm (static) and 25.6 mm (dynamic) for AoI equal to ±60°. In addition, the wearable platform was used during a preliminary experiment for the estimation of the inter-foot distance on a single healthy subject while walking. In conclusion, the combination of magneto-inertial unit and IR-ToF technology represents a valuable alternative solution in terms of accuracy, sampling frequency, dimension and power consumption, compared to existing technologies

A 2D Markerless Gait Analysis Methodology: Validation on Healthy Subjects

A 2D markerless technique is proposed to perform lower limb sagittal plane kinematic analysis using a single video camera. A subject-specific, multisegmental model of the lower limb was calibrated with the subject in an upright standing position. Ankle socks and underwear garments were used to track the feet and pelvis segments, whereas shank and thigh segments were tracked by means of reference points identified on the model. The method was validated against a marker based clinical gait model. The accuracy of the spatiotemporal parameters estimation was found suitable for clinical use (errors between 1% and 3% of the corresponding true values). Comparison analysis of the kinematics patterns obtained with the two systems revealed high correlation for all the joints (0.82<R2<0.99). Differences between the joint kinematics estimates ranged from 3.9 deg to 6.1 deg for the hip, from 2.7 deg to 4.4 deg for the knee, and from 3.0 deg to 4.7 deg for the ankle. The proposed technique allows a quantitative assessment of the lower limb motion in the sagittal plane, simplifying the experimental setup and reducing the cost with respect to traditional marker based gait analysis protocols