Inter-personal motor interaction is facilitated by hand pairing

The extent to which hand dominance may influence how each agent contributes to inter-personal coordination remains unknown. In the present study, right-handed human participants performed object balancing tasks either in dyadic conditions with each agent using one hand (left or right), or in bimanual conditions where each agent performed the task individually with both hands. We found that object load was shared between two hands more asymmetrically in dyadic than single-agent conditions. However, hand dominance did not influence how two hands shared the object load. In contrast, hand dominance was a major factor in modulating hand vertical movement speed. Furthermore, the magnitude of internal force produced by two hands against each other correlated with the synchrony between the two hands’ movement in dyads. This finding supports the important role of internal force in haptic communication. Importantly, both internal force and movement synchrony were affected by hand dominance of the paired participants. Overall, these results demonstrate, for the first time, that pairing of one dominant and one non-dominant hand may promote asymmetrical roles within a dyad during joint physical interactions. This appears to enable the agent using the dominant hand to actively maintain effective haptic communication and task performance.

A Novel Tilt and Acceleration Measurement System Based on Hall-Effect Sensors Using Neural Networks

A tilt sensor is a device used to measure the tilt on many axes of a reference point. Tilt sensors measure the bending position according to gravity and are used in many applications. Slope sensors allow easy detection of direction or slope in the air. These tilt gauges have become increasingly popular and are being adapted for a growing number of high-end applications. As an example of practical application, the tilt sensor provides valuable information about an aircraft’s vertical and horizontal tilt. This information also helps the pilot understand how to deal with obstacles during flight. In this paper, Hall-effect effective inclination and acceleration sensor design, which makes a real-time measurement, have been realized. 6 Hall-effect sensors with analog output (UGN-3503) have been used in the sensor structure. These sensors are placed in a machine, and the hall sensor outputs are continuously read according to the movement speed and direction of the sphere magnet placed in the assembly. Hall sensor outputs produce 0–5 Volt analog voltage according to the position of the magnet sphere to the sensor. It is clear that the sphere magnet moves according to the inclination of the mechanism when the mechanism is moved angularly, and the speed of movement from one point to the other changes according to the movement speed. Here, the sphere magnet moves between the hall sensors in the setup according to the ambient inclination and motion acceleration. Each sensor produces analog output values in the range of 0–5 V instantaneous according to the position of the spheroid. Generally defined, according to the sphere magnet position and movement speed, the data received from the hall sensors by the microcontroller have been sent to the computer or microcomputer unit as UART. In the next stage, the actual sensor has been removed. The angle and acceleration values have been continuously produced according to the mechanism’s movement and output as UART. Thanks to the fact that the magnet is not left idle and is fixed with springs, problems such as vibration noises and wrong movements and the magnet leaning to the very edge and being out of position even at a slight inclination are prevented. In addition, the Hall-effect sensor outputs are given to an artificial neural network (ANN), and the slope and acceleration information is estimated in the ANN by training with the data obtained from the real-time slope and accelerometer sensor.

Optimization of Link Length Fitting between an Operator and a Robot with Digital Annealer for a Leader-Follower Operation

In recent years, the teleoperation of robots has become widespread in practical use. However, in some current modes of robot operation, such as leader-follower control, the operator must use visual information to recognize the physical deviation between him/herself and the robot, and correct the operation instructions sequentially, which limits movement speed and places a heavy burden on the operator. In this study, we propose a leader-follower control parameter optimization method for the feedforward correction necessitated by deviations in the link length between the robot and the operator. To optimize the parameters, we used the Digital Annealer developed by Fujitsu Ltd., which can solve the combinatorial optimization problem at high speed. The main objective was to minimize the difference between the hand coordinates target and the actual hand position of the robot. In simulations, the proposed method decreased the difference between the hand position of the robot and the target. Moreover, this method enables optimum operation, in part by eliminating the need for the operator to maintain an unreasonable posture, as in some robots the operator’s hand position is unsuitable for achieving the objective.

Processing of the Results of Satellite Inland Positioning Transport using Mobile Devices and their Visualization

The issue of spatial data visualization is currently an important element in the positioning and navigation process. The constant trend in increasing the accuracy and availability of position modules affects the widespread use of the mobile devices in transport. The paper presents creation of a three-dimensional visualization model based on ground tracks recorded in NMEA (National Marine Electronics Association) and GPX (GPS Exchange Format) formats. Additionally, the study presents an analysis of the positioning accuracy including the sky obstructions presence and the instantaneous state of the satellite constellation. The significant deterioration in positioning accuracies was noted due to the presence of sky obstructions and low movement speed during data recording. The analysis of these parameters showed the dependence of the positioning accuracy with the number of visible satellites and the HDOP (Horizontal Dilution of Precision) parameter.

DEVELOPMENT AND TESTING OF SOIL IMPURITIES REMOVING APPARATUS FOR POTATO

Aiming at the problem that contain more soil impurities of potato post-harvest, which affects subsequent deep processing, an apparatus for removing soil impurities from potato was developed. The whole structure is mainly composed of frame, feeding port, flexible rubber finger conveying mechanism, slender filament rotary brushing mechanism, discharging port and the like. The research and analysis determined that the main parameters influencing the soil impurities removal performance were the movement speed of conveying mechanism, the movement speed of brushing mechanism and the clearance between conveying mechanism and brushing mechanism (hereinafter referred to as the mechanism clearance). Taking the main influencing parameters as test factors, and the soil impurities removal rate and potato damage rate as indexes, the orthogonal test with three factors and three levels was carried out. The optimal parameter combination was obtained as follows: the movement speed of conveying mechanism was 0.35m/s, the movement speed of brushing mechanism was 0.40m/s, and the mechanism clearance was 55mm. At this time, the average soil impurities removal rate was 87.18%, and the potato average damage rate was 1.95%, which met the requirements of potato cleaning operation.

Study on Influencing Factors of Helicopter Brownout Evolution Based on CFD-DEM

The gas-solid two-phase flow model is constructed based on the Euler-Lagrangian framework. The SST k−ω two-equation turbulence model and the soft ball model are coupled by computational fluid dynamics (CFD) and a discrete element model (DEM). Brownout is then simulated by the above method with sliding mesh. As the calculation examples show, the simulations and experiments of the Lynx rotor and the Caradonna–Tung rotor are compared. The coupling method is verified through calculation of the rotor lift coefficient, blade section pressure coefficient and tip vortex shedding position. The results show that when the helicopter is hovering at a height of 0.52R from the ground, it will cause brownout and the pilot’s vision will be obscured by sand. When the hovering height is 1R, the phenomenon of brownout is not serious. The movement speed of most sand dust is about 12 m/s, and the height of the sand dust from the ground will gradually increase over time. Large particles of sand are more difficult to be entrained into the air than the small particles, and the particles with a radius of 50 um are basically accumulated on the ground. Moreover, the slotted-Tip rotor has an effect on restraining brownout.

Remote Evaluation of Parkinson's Disease Using a Conventional Webcam and Artificial Intelligence

Objective: This study aimed to prove the concept of a new optical video-based system to measure Parkinson's disease (PD) remotely using an accessible standard webcam.Methods: We consecutively enrolled a cohort of 42 patients with PD and healthy subjects (HSs). The participants were recorded performing MDS-UPDRS III bradykinesia upper limb tasks with a computer webcam. The video frames were processed using the artificial intelligence algorithms tracking the movements of the hands. The video extracted features were correlated with clinical rating using the Movement Disorder Society revision of the Unified Parkinson's Disease Rating Scale and inertial measurement units (IMUs). The developed classifiers were validated on an independent dataset.Results: We found significant differences in the motor performance of the patients with PD and HSs in all the bradykinesia upper limb motor tasks. The best performing classifiers were unilateral finger tapping and hand movement speed. The model correlated both with the IMUs for quantitative assessment of motor function and the clinical scales, hence demonstrating concurrent validity with the existing methods.Conclusions: We present here the proof-of-concept of a novel webcam-based technology to remotely detect the parkinsonian features using artificial intelligence. This method has preliminarily achieved a very high diagnostic accuracy and could be easily expanded to other disease manifestations to support PD management.

Agency evaluation in motor cognition: Action’s control-effectiveness feedback and its environmental context enhances motor performance

A perceptual effect that is temporally contiguous on one’s action holds important information about one’s control over the action and its effect (“I did that”). Previous work has demonstrated the impact of such immediate action-effect on perception and motor processes. In the current study, we investigated the promoting impact of control-effectiveness feedback – an effect that is temporally contiguous on one’s action – on motor performance. In two experiments, participants performed a rapid movement towards a target location on a computer monitor and clicked on the target with their mouse key as quickly and accurately as possible. Their click response triggered a perceptual effect (a brief white flash) on the target. We manipulated control-effectiveness feedback by employing varying levels of action-effect delay in two experimental contexts - long versus short lag distributions. Such design enabled us to investigate the impact of both the recent action-effect delay and its experimental context on motor performance. The findings demonstrate that control-effectiveness feedback (e.g., temporally contiguous perceptual effect) enhances motor performance as indicated by both endpoint precision and movement speed. In addition, a substantial effect of the experimental context was observed. Namely, we found enhanced motor performance, especially after an ambiguous (intermediate) action-effect delay when it was sampled from a short compared to long lag distribution; a pattern that supports the contribution of both ‘control’ expectations and control-feedback on motor performance. We discuss findings in the context of previous work on control-effectiveness and movement control and their potential implications for clinicians and digital interface developers.

Detection of Parkinsonian Motor Symptoms Using Non-Invasive Motion Sensing Technology

Parkinson’s Disease (PD) is characterized by impaired movement, resting tremor, and muscle rigidity. The Unified PD Rating Scale (UPDRS) is a standardized protocol used by neurologists to measure progression of disease as well as evaluation of treatments. However, this examination is subjective, time consuming, and results can be affected by stress, diet, or sleep. Our goal is to develop a non-invasive device that can record objective clinically-relevant measurements during subtasks of the UPDRS to allow for remote evaluations, which would be beneficial considering the frequency of clinical visits for medication adjustments. Five healthy individuals (ages 21-59) completed UPDRS tasks 3.6 (pronation/supination of hands) and 3.17 (rest tremor amplitude). Participants performed these tasks twice, first normally and second simulating PD patients (tremor, bradykinesia, reduction of movement amplitude) after viewing example videos. Motion data including linear and angular accelerations in 3 dimensions was acquired using a lightweight wrist-mounted motion sensor. Three features were extracted: (1) Power of higher frequency components of the linear acceleration signal (rest task), as a measure of resting tremor amplitude. (2) Power of higher frequency components of the rotational acceleration signal (pronation/supination task), as a measure of bradykinesia. (3) Standard deviation of the local maxima of the rotational acceleration (pronation/supination task), as a measure of reduction in movement speed and amplitude. These features were used to correctly differentiate trials completed with and without simulated PD symptoms, using an SVM classifier with leave-one-out cross validation accuracy of 95%. These findings suggest it is possible to capture clinical features of PD using motion sensors. Future work in PD patients will examine how these measures correlate with UPDRS evaluations and whether they will be helpful in providing a quick, objective telehealth measure of progression and treatment response that can supplement current tools.

Theoretical and Experimental Research on Multi-Layer Vessel-like Structure Printing Based on 3D Bio-Printing Technology

Cardiovascular disease is the leading cause of death worldwide. Traditional autologous transplantation has become a severe issue due to insufficient donors. Artificial blood vessel is an effective method for the treatment of major vascular diseases, such as heart and peripheral blood vessel diseases. However, the traditional single-material printing technology has been unable to meet the users’ demand for product functional complexity, which is not only reflected in the field of industrial manufacturing, but also in the field of functional vessel-like structure regeneration. In order to achieve the printing and forming of multi-layer vessel-like structures, this paper carries out theoretical and experimental research on the printing and forming of a multi-layer vessel-like structure based on multi-material 3D bioprinting technology. Firstly, theoretical analysis has been explored to research the relationship among the different parameters in the process of vessel forming, and further confirm the synchronous relationship among the extrusion rate of material, the tangential speed of the rotating rod, and the movement speed of the platform. Secondly, sodium alginate and gelatin have been used as the experimental materials to manufacture the vessel-like structure, and the corrected parameter of the theoretical analysis is further verified. Finally, the cell-loaded materials have been printed and analyzed, and cell viability is more than 90%, which provides support for the research of multi-layer vessel-like structure printing.