Detection of upper limb abrupt gestures for human–machine interaction using deep learning techniques

In the manufacturing industry the productivity is contingent on the workers' well-being, with operators at the center of the production process. Moreover, when human-machine interaction occurs, operators' safety is a key requirement. Generally, typical human gestures in manipulation tasks have repetitive kinetics, however external disturbances or environmental factors might provoke abrupt gestures, leading to improper interaction with the machine. The identification and characterization of these abrupt events has not yet been thoroughly studied. Accordingly, the aim of the current research was to define a methodology to ready identify human abrupt movements in a workplace, where manipulation activities are carried out. Five subjects performed three times a set of 30 standard pick-and-place tasks paced at 20 bpm, wearing magneto-inertial measurement units (MIMUs) on their wrists. Random visual and acoustic alarms triggered abrupt movements during standard gestures. The recorded signals were processed by segmenting each pick-and-place cycle. The distinction between standard and abrupt gestures was performed through a recurrent neural network applied to acceleration signals. Four different pre-classification methodologies were implemented to train the neural network and the resulting confusion matrices were compared. The outcomes showed that appropriate preprocessing of the data allows more effective training of the network and shorter classification time, enabling to achieve accuracy greater than 99% and F1-score better than 90%

Position-sensorless control of permanent-magnet-assisted synchronous reluctance motor

The sensorless control of permanent-magnet-assisted synchronous reluctance (PMASR) motors is investigated, in order to conjugate the advantages of the sensorless control with full exploitation of the allowed operating area, for a given inverter. An additional pulsating flux is injected in the d-axis direction at low and zero speed, while it is dropped out, at large speed, to save voltage and additional loss. A flux-observer-based control scheme is used, which includes an accurate knowledge of the motor magnetic behavior. This leads, in general, to good robustness against load variations, by counteracting the magnetic cross saturation effect. Moreover, it allows an easy and effective correspondence between the wanted torque and flux and the set values of the chosen control variables, that is d-axis flux and q-axis current. Experimental verification of the proposed method is given, both steady-state and dynamic performance are outlined. A prototype PMASR motor will be used to this aim, as part of a purposely assembled prototype drive, for light traction application (electric scooter

Kinematic and dynamic assessment of trunk exoskeleton

In Industry 4.0, wearable exoskeletons have been proposed as collaborative robotic devices to partially assist workers in heavy and dangerous tasks. Despite the recent researches, proposed prototypes and commercial products, some open issues concerning development, improvements and testing still exist. The current pilot study proposed the assessment of a proper biomechanical investigation of passive trunk exoskeleton effects on the human body. One healthy subject performed walking, stoop and semisquat tasks without, with exoskeleton no support and with exoskeleton with support. 3D Kinematic (angles, translations) and dynamic (interface forces) parameters of both human and exoskeleton were estimated. Some differences were pointed out comparing task motions and exoskeleton conditions. The presented preliminary test revealed interesting results in terms of different human joints coordination, interface forces exchanged at contact points and possible misalignment between human and device. The present study could be considered as a starting point for the investigation of exoskeleton effectiveness and interaction with the user

Proteomic insights on the metabolism in inflammatory bowel disease

Inflammatory bowel diseases (IBD) are chronic and relapsing inflammatory conditions of the gut that include Crohn's disease and ulcerative colitis. The pathogenesis of IBD is not completely unraveled, IBD are multi-factorial diseases with reported alterations in the gut microbiota, activation of different immune cell types, changes in the vascular endothelium, and alterations in the tight junctions\u2019 structure of the colonic epithelial cells. Proteomics represents a useful tool to enhance our biological understanding and to discover biomarkers in blood and intestinal specimens. It is expected to provide reproducible and quantitative data that can support clinical assessments and help clinicians in the diagnosis and treatment of IBD. Sometimes a differential diagnosis of Crohn's disease and ulcerative colitis and the prediction of treatment response can be deducted by finding meaningful biomarkers. Although some non-invasive biomarkers have been described, none can be considered as the \u201cgold standard\u201d for IBD diagnosis, disease activity and therapy outcome. For these reason new studies have proposed an \u201cIBD signature\u201d, which consists in a panel of biomarkers used to assess IBD. The above described approach characterizes \u201comics\u201d and in this review we will focus on proteomics

Influence of dietary conjugated linoleic acid (CLA) and L-Lysine on heavy pigs performances and meat quality

Conjugated linoleic acid (CLA) refers to a group of positional and geometric fatty acid isomers derived from linoleic acid. Dietary CLA supplementation has been shown to increase feed efficiency and may reduce body fat content in swine as recently reviewed by Corino et al., (2005). There was only one research conducted in heavy pig in which the authors did not observed any significant effect of dietary CLA on growth performances and lean tissue (Corino et al., 2003)

Wearable MIMUs for the identification of upper limbs motion in an industrial context of human-robot interaction

The automation of human gestures is gaining increasing importance in manufacturing. Indeed, robots support operators by simplifying their tasks in a shared workspace. However, human-robot collaboration can be improved by identifying human actions and then developing adaptive control algorithms for the robot. Accordingly, the aim of this study was to classify industrial tasks based on accelerations signals of human upper limbs. Two magnetic inertial measurement units (MIMUs) on the upper limb of ten healthy young subjects acquired pick and place gestures at three different heights. Peaks were detected from MIMUs accelerations and were adopted to classify gestures through a Linear Discriminant Analysis. The method was applied firstly including two MIMUs and then one at a time. Results demonstrated that the placement of at least one MIMU on the upper arm or forearm is suitable to achieve good recognition performances. Overall, features extracted from MIMUs signals can be used to define and train a prediction algorithm reliable for the context of collaborative robotics

Ecodesign of Low-Voltage Systems and Exposure to ELF Magnetic Fields

The Ecodesign of modern residential and commercial low-voltage systems implements energy and equipment cost savings, optimizing the size of the distribution system without compromising their functionality or causing environmental contamination, including electromagnetic pollution. Protection of persons against shock hazards should result increased, and the electrical interferences among power systems reduced. To achieve the aforementioned improvements, a possible Ecodesign calls for an earthing system utilizing single-phase separation transformers installed in the unit, grounded at the mid-point of their secondary side. The introduction of a source of magnetic fields into the premises at the power frequency of 60/50 Hz (i.e. extremely low frequency, ELF) might expose persons to their potential adverse health effects, as well as, sensitive electronic equipment to disturbances. This paper seeks to clarify this matter by evaluating the ELF magnetic fields as produced by the user's own transformer and by other units eventually present in the vicinity

Collection and analysis of human upper limbs motion features for collaborative robotic applications

Background: The technologies of Industry 4.0 are increasingly promoting an operation of human motion prediction for improvement of the collaboration between workers and robots. The purposes of this study were to fuse the spatial and inertial data of human upper limbs for typical industrial pick and place movements and to analyze the collected features from the future perspective of collaborative robotic applications and human motion prediction algorithms. (2) Methods: Inertial Measurement Units and a stereophotogrammetric system were adopted to track the upper body motion of 10 healthy young subjects performing pick and place operations at three different heights. From the obtained database, 10 features were selected and used to distinguish among pick and place gestures at different heights. Classification performances were evaluated by estimating confusion matrices and F1-scores. (3) Results: Values on matrices diagonals were definitely greater than those in other positions. Furthermore, F1-scores were very high in most cases. (4) Conclusions: Upper arm longitudinal acceleration and markers coordinates of wrists and elbows could be considered representative features of pick and place gestures at different heights, and they are consequently suitable for the definition of a human motion prediction algorithm to be adopted in effective collaborative robotics industrial applications

Growth performance and oxidative status in piglets supplemented with verbascoside and teupolioside

Two hundred forty piglets, half female and half barrows, 8.1 ± 1.40 kg LW, were divided into 6 experimental groups and fed ad libitum with a diet supplemented with the following levels of antioxidants: 0 (CON + = positive control added with 100 mg lincomicine/kg), 5 (LT = low teupolioside or LV = low verbascoside), 10 (HT = high teupolioside; HV = high verbascoside; LT+LV) mg/kg of diet for 56 days. Body weight and feed intake were recorded on d0, 14 and 56 of the trial. Ten piglets from each group were selected and blood collected by anterior vena cava puncture at 0, 14 and 56 d for reactive oxygen metabolite (ROMs) determination. HV showed final weight higher than the other groups (P<0.05), and oxidative stability was improved by both integrations of verbascoside. These results support the view that Verbascoside influences the growth performances and oxidative status of piglets