Evaluation of Optimal Vibrotactile Feedback for Force-Controlled Upper Limb Myoelectric Prostheses.

The main goal of this study is to evaluate how to optimally select the best vibrotactile pattern to be used in a closed loop control of upper limb myoelectric prostheses as a feedback of the exerted force. To that end, we assessed both the selection of actuation patterns and the effects of the selection of frequency and amplitude parameters to discriminate between different feedback levels. A single vibrotactile actuator has been used to deliver the vibrations to subjects participating in the experiments. The results show no difference between pattern shapes in terms of feedback perception. Similarly, changes in amplitude level do not reflect significant improvement compared to changes in frequency. However, decreasing the number of feedback levels increases the accuracy of feedback perception and subject-specific variations are high for particular participants, showing that a fine-tuning of the parameters is necessary in a real-time application to upper limb prosthetics. In future works, the effects of training, location, and number of actuators will be assessed. This optimized selection will be tested in a real-time proportional myocontrol of a prosthetic hand.

A survey on FPGA-based sensor systems: towards intelligent and reconfigurable low-power sensors for computer vision, control and signal processing.

The current trend in the evolution of sensor systems seeks ways to provide more accuracy and resolution, while at the same time decreasing the size and power consumption. The use of Field Programmable Gate Arrays (FPGAs) provides specific reprogrammable hardware technology that can be properly exploited to obtain a reconfigurable sensor system. This adaptation capability enables the implementation of complex applications using the partial reconfigurability at a very low-power consumption. For highly demanding tasks FPGAs have been favored due to the high efficiency provided by their architectural flexibility (parallelism, on-chip memory, etc.), reconfigurability and superb performance in the development of algorithms. FPGAs have improved the performance of sensor systems and have triggered a clear increase in their use in new fields of application. A new generation of smarter, reconfigurable and lower power consumption sensors is being developed in Spain based on FPGAs. In this paper, a review of these developments is presented, describing as well the FPGA technologies employed by the different research groups and providing an overview of future research within this field.

A Comparison of Myoelectric Control Modes for an Assistive Robotic Virtual Platform.

In this paper, we propose a daily living situation where objects in a kitchen can be grasped and stored in specific containers using a virtual robot arm operated by different myoelectric control modes. The main goal of this study is to prove the feasibility of providing virtual environments controlled through surface electromyography that can be used for the future training of people using prosthetics or with upper limb motor impairments. We propose that simple control algorithms can be a more natural and robust way to interact with prostheses and assistive robotics in general than complex multipurpose machine learning approaches. Additionally, we discuss the advantages and disadvantages of adding intelligence to the setup to automatically assist grasping activities. The results show very good performance across all participants who share similar opinions regarding the execution of each of the proposed control modes.

Cancer Cell Small Molecule Secretome Induces the Immune Checkpoint NKG2A and Dysfunction of Human CD8+ T Cells.

PD-1 blockade has been approved for head and neck squamous cell carcinoma (HNSCC) patients. However, many HNSCC patients do not respond to this treatment, and other tumor microenvironmental factors may promote resistance to PD-1 blockade. We previously identified increased expression of the inhibitory receptor NKG2A on CD8+ T cells in HNSCC tumors compared with T cells in matching PBMC samples. Mechanisms that promote NKG2A expression and the role of NKG2A on human T cells in the tumor microenvironment, however, are uncertain. In this study, we show that tumor-conditioned media (TCM) of HNSCC cancer cell lines or ascites fluid from colorectal carcinoma patients is sufficient to induce the expression of NKG2A and other inhibitory receptors on activated CD8+ T cells isolated from PBMCs of healthy donors. Boiling or small molecular mass cutoff filtering did not eliminate the effect of TCM, suggesting that a small molecule promotes NKG2A. T cell activation in TCM decreased the basal and maximal mitochondrial respiration to metabolically restrain CD8+ T cells. Functionally, T cell activation in TCM reduced CD8+ T cell cytotoxicity as shown by lower production of cytokines, granzyme B, and perforin. Furthermore, TCM prevented CD8+ T cells from killing cancer cells in response to an anti-CD19/anti-CD3 bispecific T cell engager. Thus, a small secreted molecule from HNSCC cells can induce NKG2A expression and promote T cell dysfunction. Our findings may lead to targets for novel cancer therapies or biomarkers for NKG2A blockade response and provide a model to study T cell dysfunction and impaired metabolism.

Multisensory Evaluation of Muscle Activity and Human Manipulability during Upper Limb Motor Tasks.

In this work, we evaluate the relationship between human manipulability indices obtained from motion sensing cameras and a variety of muscular factors extracted from surface electromyography (sEMG) signals from the upper limb during specific movements that include the shoulder, elbow and wrist joints. The results show specific links between upper limb movements and manipulability, revealing that extreme poses show less manipulability, i.e., when the arms are fully extended or fully flexed. However, there is not a clear correlation between the sEMG signals' average activity and manipulability factors, which suggests that muscular activity is, at least, only indirectly related to human pose singularities. A possible means to infer these correlations, if any, would be the use of advanced deep learning techniques. We also analyze a set of EMG metrics that give insights into how muscular effort is distributed during the exercises. This set of metrics could be used to obtain good indicators for the quantitative evaluation of sequences of movements according to the milestones of a rehabilitation therapy or to plan more ergonomic and bearable movement phases in a working task.

A kinematic, imaging and electromyography dataset for human muscular manipulability index prediction.

Human Muscular Manipulability is a metric that measures the comfort of an specific pose and it can be used for a variety of applications related to healthcare. For this reason, we introduce KIMHu: a Kinematic, Imaging and electroMyography dataset for Human muscular manipulability index prediction. The dataset is comprised of images, depth maps, skeleton tracking data, electromyography recordings and 3 different Human Muscular Manipulability indexes of 20 participants performing different physical exercises with their arm. The methodology followed to acquire and process the data is also presented for future replication. A specific analysis framework for Human Muscular Manipulability is proposed in order to provide benchmarking tools based on this dataset.

Biosensors in Rehabilitation and Assistance Robotics.

Robotic developments in the field of rehabilitation and assistance have seen a significant increase in the last few years [...].

ARMIA: A Sensorized Arm Wearable for Motor Rehabilitation.

In this paper, we present ARMIA: a sensorized arm wearable that includes a combination of inertial and sEMG sensors to interact with serious games in telerehabilitation setups. This device reduces the cost of robotic assistance technologies to be affordable for end-users at home and at rehabilitation centers. Hardware and acquisition software specifications are described together with potential applications of ARMIA in real-life rehabilitation scenarios. A detailed comparison with similar medical technologies is provided, with a specific focus on wearable devices and virtual and augmented reality approaches. The potential advantages of the proposed device are also described showing that ARMIA could provide similar, if not better, the effectivity of physical therapy as well as giving the possibility of home-based rehabilitation.

A multi-sensorial hybrid control for robotic manipulation in human-robot workspaces.

Autonomous manipulation in semi-structured environments where human operators can interact is an increasingly common task in robotic applications. This paper describes an intelligent multi-sensorial approach that solves this issue by providing a multi-robotic platform with a high degree of autonomy and the capability to perform complex tasks. The proposed sensorial system is composed of a hybrid visual servo control to efficiently guide the robot towards the object to be manipulated, an inertial motion capture system and an indoor localization system to avoid possible collisions between human operators and robots working in the same workspace, and a tactile sensor algorithm to correctly manipulate the object. The proposed controller employs the whole multi-sensorial system and combines the measurements of each one of the used sensors during two different phases considered in the robot task: a first phase where the robot approaches the object to be grasped, and a second phase of manipulation of the object. In both phases, the unexpected presence of humans is taken into account. This paper also presents the successful results obtained in several experimental setups which verify the validity of the proposed approach.

Survey of visual and force/tactile control of robots for physical interaction in Spain.

Sensors provide robotic systems with the information required to perceive the changes that happen in unstructured environments and modify their actions accordingly. The robotic controllers which process and analyze this sensory information are usually based on three types of sensors (visual, force/torque and tactile) which identify the most widespread robotic control strategies: visual servoing control, force control and tactile control. This paper presents a detailed review on the sensor architectures, algorithmic techniques and applications which have been developed by Spanish researchers in order to implement these mono-sensor and multi-sensor controllers which combine several sensors.

Tethered dimers as NAD synthetase inhibitors with antibacterial activity.

The solution-phase parallel synthesis of tethered dimers was employed to identify lead inhibitors of bacterial NAD synthetase. Active dimers contained two aromatic end groups joined by a polymethylene linker, with one end group containing a permanent positive charge. Effective inhibitors of NAD synthetase also inhibited the growth of Gram-positive (but not Gram-negative) bacteria, including antibiotic-resistant strains. The desmethyl precursors of active inhibitors lacked a permanent positive charge and were inactive as either enzyme inhibitors or antibacterial agents. Similarly, a close structural analogue of the most active inhibitors contained two additional ether oxygens in the tether and was inactive in both assays. These results are consistent with the premise that NAD synthetase inhibition is responsible for the antibacterial actions and support further studies on NAD synthetase as a new target for antibacterial agents.