Myoelectric arm using artificial neural networks to reduce cognitive load of the user

Today’s multiple degree-of-freedom myoelectric prosthesis relies only on direct control by the processed electromyographic signal. However, it is difficult for the wearer to learn unnatural muscle contractions in order to wield more than three DoFs of the arm. This makes it almost impossible to use more complex prostheses with a larger number of actuators. Methods based on sensor–actuator loop and artificial intelligence may reduce cognitive load of the user by removing low level control, and an intelligent control system would make it needless to micromanage every action. For this purpose, sensor system for body segments motion capture was developed, as well as sensor system for prosthetic limb’s environment motion capture. Neural networks were designed to process data from the sensor systems. For the identification of the knee angle, orientation trackers were used. Neural network predictor of arm positions predicts the shoulder angle using the information about movement of the lower limb. In the case of the periodic/cyclic movements of the legs, such as walking, the control unit uses typical movement patterns of the healthy upper limb. Ultrasonic range sensors are used to create 3D map of objects in the environment around the arm. Neural network predictor of object positions predicts collisions. If the potential collisions are identified, the control unit stops arm movement. The new methods were verified by MATLAB and are designed as a part of assistive technology for disabled people and are to be understood as an original contribution to the investigation of new prosthesis control units and international debate on the design of new myoelectric prostheses.

     

Geometric and elastostatic calibration of robotic manipulator using partial pose measurements

The paper deals with the geometric and elastostatic calibration of robotic manipulator using partial pose measurements, which do not provide the end-effector orientation. The main attention is paid to the efficiency improvement of identification procedure. In contrast to previous works, the developed calibration technique is based on the direct measurements only. To improve the identification accuracy, it is proposed to use several reference points for each manipulator configuration. This allows avoiding the problem of non-homogeneity of the least-square objective, which arises in the classical identification technique with the full pose information (position and orientation). Its efficiency is confirmed by the comparison analysis, which deals with the accuracy evaluation of different identification strategies. The obtained theoretical results have been successfully applied to the geometric and elastostatic calibration of a serial industrial robot employed in a machining work cell for aerospace industry.     

Effect of scatter on reconstructed image quality in cone beam computed tomography: evaluation of a scatter-reduction optimisation function

The effect of scatter on reconstructed image quality in cone beam computed tomography was investigated and a function which can be used in scatter-reduction optimisation tasks was tested. Projections were calculated using the Monte Carlo method in an axially symmetric cone beam geometry consisting of a point source, water phantom and a single row of detector elements. Image reconstruction was performed using the filtered backprojection method. Image quality was assessed by the L2-norm-based difference relative to a reference image derived from (1) weighted linear attenuation coefficients and (2) projections by primary photons. It was found that the former function was strongly affected by the beam hardening artefact and did not properly reflect the amount of scatter but the latter function increased with increasing beam width, was higher for the larger phantom and exhibited properties which made it a good candidate for scatter-reduction optimisation tasks using polyenergetic beams.     

Guiding of emulsion droplets in microfluidic chips along shallow tracks defined by laser ablation

We demonstrate controlled guiding of nanoliter emulsion droplets of polar liquids suspended in oil along shallow hydrophilic tracks fabricated at the base of microchannels located within microfluidic chips. The tracks for droplet guiding are generated by exposing the glass surface of polydimethylsiloxane (PDMS)-coated microscope slides via femtosecond laser ablation. The difference in wettability of glass and PDMS surfaces together with the shallow step-like transverse topographical profile of the ablated tracks allows polar droplets wetting preferentially the glass surface to follow the track. In this study, we investigate guiding of droplets of two different polar liquids (water/ethylene glycol) with and without surfactant suspended in an oil medium along surface tracks of different depths of 1, 1.5, and 2 \(\upmu\)m. The results of experiments are also verified with computational fluid dynamics simulations. Guiding of droplets along the tracks as a function of the droplet composition and size and the surface profile depth is evaluated by analyzing the trajectories of moving droplets with respect to the track central axis, and conditions for stable guiding are identified. The experiments and numerical simulations indicate that while the track topography plays a role in droplet guiding using 1.5- and 2-\(\upmu\)m deep tracks, for the case of the smallest track depth of 1 \(\upmu\)m, droplet guiding is mainly caused by surface energy modification along the track rather than the presence of a topographical step on the surface. Our results can be exploited to sort passively different microdroplets mixed in the same microfluidic chip, based on their inherent wetting properties, and they can also pave the way for guiding of droplets along reconfigurable tracks defined by surface energy modifications obtained using other external control mechanisms such as electric field or light.     

Synthesis and properties of prepolymers and their siloxane analogues by thiol‐ene polyaddition of limonene with dithiols

This work presents a synthesis of monomers from a natural compound (limonene) and dimethylsiloxanes with various chain lengths by hydrosilylation. Based on these monomers, prepolymers with various lengths of the siloxane and methylene parts, as well as their analogues without siloxane moieties, were obtained by thiol‐ene polyaddition with ethanedithiol, butanedithiol and hexanedithiol. Their physicochemical characteristics, namely the thermal stability, phase behaviour and intrinsic viscosity of the polymers obtained, were compared as a function of the length of the methylene spacer and the siloxane part in the polymer chain. © 2019 Society of Chemical Industry     

Liquefied Sunshine: Transforming Renewables into Fertilizers and Energy Carriers with Electromaterials

It has become apparent that renewable energy sources are plentiful in many, often remote, parts of the world, such that storing and transporting that energy has become the key challenge. For long-distance transportation by pipeline and bulk tanker, a liquid form of energy carrier is ideal, focusing attention on liquid hydrogen and ammonia. Development of high-activity and selectivity electrocatalyst materials to produce these energy carriers by reductive electrochemistry has therefore become an important area of research. Here, recent developments and challenges in the field of electrocatalytic materials for these processes are discussed, including the hydrogen evolution reaction (HER), the oxygen evolution reaction (OER), and the nitrogen reduction reaction (NRR). Some of the mis-steps currently plaguing the nitrogen reduction to ammonia field are highlighted. The rapidly growing roles that in situ/operando and quantum chemical studies can play in new electromaterials discovery are also surveyed.