Multi-dimensional task recognition for human-robot teaming: literature review.

Human-robot teams collaborating to achieve tasks under various conditions, especially in unstructured, dynamic environments will require robots to adapt autonomously to a human teammate's state. An important element of such adaptation is the robot's ability to infer the human teammate's tasks. Environmentally embedded sensors (e.g., motion capture and cameras) are infeasible in such environments for task recognition, but wearable sensors are a viable task recognition alternative. Human-robot teams will perform a wide variety of composite and atomic tasks, involving multiple activity components (i.e., gross motor, fine-grained motor, tactile, visual, cognitive, speech and auditory) that may occur concurrently. A robot's ability to recognize the human's composite, concurrent tasks is a key requirement for realizing successful teaming. Over a hundred task recognition algorithms across multiple activity components are evaluated based on six criteria: sensitivity, suitability, generalizability, composite factor, concurrency and anomaly awareness. The majority of the reviewed task recognition algorithms are not viable for human-robot teams in unstructured, dynamic environments, as they only detect tasks from a subset of activity components, incorporate non-wearable sensors, and rarely detect composite, concurrent tasks across multiple activity components.

Predicting task performance for intelligent human-machine interactions.

Human-machine teams are deployed in a diverse range of task environments and paradigms that may have high failure costs (e.g., nuclear power plants). It is critical that the machine team member can interact with the human effectively without reducing task performance. These interactions may be used to manage the human's workload state intelligently, as the overall workload is related to task performance. Intelligent human-machine teaming systems rely on a facet of the human's state to determine how interaction occurs, but typically only consider the human's state at the current time step. Future task performance predictions may be leveraged to determine if adaptations need to occur in order to prevent future performance degradation. An individualized task performance prediction algorithm that relies on a multi-faceted human workload estimate is shown to predict a supervisor's task performance accurately. The analysis varies the prediction time frame (from 0 to 300 s) and compares results to a generalized algorithm.

Redundancy and overactuation in cephalopod-inspired soft robot arms.

Current soft robotic arms commonly follow traditional-i.e. hard-robot design conventions. Omnidirectional soft arms most commonly consist of segments that contain three parallel longitudinal actuators, or actuator groups, of which one or two are activated to induce bending. This design uses the minimum number of actuators required for omnidirectional bending, which is consistent with traditional robot design but unnecessarily constrains the soft arm design space. The cephalopods that frequently inspire soft robot arms have tens of bundles of longitudinal muscle fibers, and these bundles are distributed around the limb circumference rather than grouped. This article analyzes fluid-driven soft arm architectures with up to 12 actuators, which mimics the redundant and distributed nature of cephalopod arms and tentacles, in order to investigate the performance implications of an arm morphology closer to nature. Overactuation (i.e. activating more than two actuators) was considered, which is possible because soft robots-unlike traditional robots-can tolerate misaligned or partially opposed actuation without jamming. A previously-developed generalizable model was used to simulate design performance, and a subset of the examined architectures were constructed and tested. Many-actuator soft arms achieve high strokes under equivalent load and equivalent actuation pressures, without sacrificing no-load reach. These arms are also able to achieve quasi-omnidirectionality, as well as to execute near constant-curvature turns using a simple actuation pattern and a single pressure signal. The introduced framework also enables non-circular cross sections that are not possible with minimalist arm designs, allowing the load capacity and reach to be tuned in multiple directions. Several elliptical cross section arms were analyzed to explore the potential of non-circular cross sections. Overactuated, many-actuator arms significantly expand the design space of soft arms, improving performance in some cases and introducing options to tailor behavior that are infeasible in structurally minimal arms.

Redundancy and overactuation in cephalopod-inspired soft robot arms.

Current soft robotic arms commonly follow traditional - i.e., hard - robot design conventions. Omnidirectional soft arms most commonly consist of segments that contain three parallel longitudinal actuators, or actuator groups, of which one or two are activated to induce bending. This design uses the minimum number of actuators required for omnidirectional bending, which is consistent with traditional robot design but unnecessarily constrains the soft arm design space. The cephalopods that frequently inspire soft robot arms have tens of bundles of longitudinal muscle fibers, and these bundles are distributed around the limb circumference rather than grouped. This article analyzes fluid-driven soft arm architectures with up to 12 actuators, which mimic the redundant and distributed nature of cephalopod arms and tentacles. Over-constraints (activating more than two actuators) were considered, which are possible because soft robots - unlike traditional robots - can tolerate conflicting constraints without jamming. A previously-developed generalizable model was used to simulate design performance, and a subset of the examined architectures were constructed and tested. Many-actuator soft arms achieved high strokes under equivalent load without sacrificing no-load reach and were able to execute near constant-curvature turns with a simple actuation pattern. The framework introduced here also enables cross section variations that are not possible with minimalist designs.

Emergency Clinical Procedure Detection With Deep Learning.

Information about a patient's state is critical for hospitals to provide timely care and treatment. Prior work on improving the information flow from emergency medical services (EMS) to hospitals demonstrated the potential of using automated algorithms to detect clinical procedures. However, prior work has not made effective use of video sources that might be available during patient care. In this paper we explore the use convolutional neural networks (CNNs) on raw video data to determine how well video data alone can automatically identify clinical procedures. We apply multiple deep learning models to this problem, with significant variation in results. Our findings indicate performance improvements compared to prior work, but also indicate a need for more training data to reach clinically deployable levels of success.

Automatic Clinical Procedure Detection for Emergency Services.

Understanding a patient's state is critical to providing optimal care. However, information loss occurs during patient hand-offs (e.g., emergency services (EMS) transferring patient care to a receiving hospital), which hinders care quality. Augmenting the information flow from an EMS vehicle to a receiving hospital may reduce information loss and improve patient outcomes. Such augmentation requires a noninvasive system that can automatically recognize clinical procedures being performed and send near real-time information to a receiving hospital. An automatic clinical procedure detection system that uses wearable sensors, video, and machine-learning to recognize clinical procedures within a controlled environment is presented. The system demonstrated how contextual information and a majority vote method can substantially improve procedure recognition accuracy. Future work concerning computer vision techniques and deep learning are discussed.

Feasibility Assessment of a Pre-Hospital Automated Sensing Clinical Documentation System.

Clinical documentation in the pre-hospital setting is challenged by limited resources and fast-paced, high-acuity. Military and civilian medics are responsible for performing procedures and treatments to stabilize the patient, while transporting the injured to a trauma facility. Upon arrival, medics typically give a verbal report from memory or informal source of documentation such as a glove or piece of tape. The development of an automated documentation system would increase the accuracy and amount of information that is relayed to the receiving physicians. This paper discusses the 12-week deployment of an Automated Sensing Clinical Documentation (ASCD) system among the Nashville Fire Department EMS paramedics. The paper examines the data collection methods, operational challenges, and perceptions surrounding real-life deployment of the system. Our preliminary results suggest that the ASCD system is feasible for use in the pre-hospital setting, and it revealed several barriers and their solutions.

Human performance measures for the evaluation of process control human-system interfaces in high-fidelity simulations.

We reviewed the available literature on measuring human performance to evaluate human-system interfaces (HSIs), focused on high-fidelity simulations of industrial process control systems, to identify best practices and future directions for research and operations. We searched the available literature and then conducted in-depth review, structured coding, and analysis of 49 articles, which described 42 studies. Human performance measures were classified across six dimensions: task performance, workload, situation awareness, teamwork/collaboration, plant performance, and other cognitive performance indicators. Many studies measured performance in more than one dimension, but few studies addressed more than three dimensions. Only a few measures demonstrated acceptable levels of reliability, validity, and sensitivity in the reviewed studies in this research domain. More research is required to assess the measurement qualities of the commonly used measures. The results can provide guidance to direct future research and practice for human performance measurement in process control HSI design and deployment.

Synthesis and biological activity of a CXCR4-targeting bis(cyclam) lipid.

A bis(cyclam)-capped cholesterol lipid designed to bind C-X-C chemokine receptor type 4 (CXCR4) was synthesised in good overall yield from 4-methoxyphenol through a seven step synthetic route, which also provided a bis(cyclam) intermediate bearing an octaethyleneglycol-primary amine that can be easily derivatised. This bis(cyclam)-capped cholesterol lipid was water soluble and self-assembled into micellar and non-micellar aggregates in water at concentrations above 8 µM. The bioactivity of the bis(cyclam)-capped cholesterol lipid was assessed using primary chronic lymphocytic leukaemia (CLL) cells, first with a competition binding assay then with a chemotaxis assay along a C-X-C motif chemokine ligand 12 (CXCL12) concentration gradient. At 20 µM, the bis(cyclam)-capped cholesterol lipid was as effective as the commercial drug AMD3100 for preventing the migration of CLL cells, despite a lower affinity for CXCR4 than AMD3100.

Lymphocytes from chronic lymphocytic leukaemia undergo ABL1-linked amoeboid motility and homotypic interaction as an early adaptive change to ex vivo culture.

BACKGROUND: Those stimuli that together promote the survival, differentiation and proliferation of the abnormal B-lymphocytes of chronic lymphocytic leukaemia (CLL) are encountered within tissues, where together they form the growth-supporting microenvironment. Different tissue-culture systems promote the survival of the neoplastic lymphocytes from CLL, partly replicating the in vivo tissue environment of the disorder. In the present study, we focussed on the initial adaptive changes to the tissue culture environment focussing particularly on migratory behaviour and cellular interactions. METHODS: A high-density CLL culture system was employed to test CLL cell-responses using a range of microscopic techniques and flow cytometric analyses, supported by mathematical measures of cell shape-change and by biochemical techniques. The study focussed on the evaluation of changes to the F-actin cytoskeleton and cell behaviour and on ABL1 signalling processes. RESULTS: We showed that the earliest functional response by the neoplastic lymphocytes was a rapid shape-change caused through rearrangement of the F-actin cytoskeleton that resulted in amoeboid motility and promoted frequent homotypic interaction between cells. This initial response was functionally distinct from the elongated motility that was induced by chemokine stimulation, and which also characterised heterotypic interactions between CLL lymphocytes and accessory cells at later culture periods. ABL1 is highly expressed in CLL lymphocytes and supports their survival, it is also recognised however to have a major role in the control of the F-actin cytoskeleton. We found that the cytoplasmic fraction of ABL1 became co-localised with F-actin structures of the CLL lymphocytes and that the ABL1 substrate CRKL became phosphorylated during initial shape-change. The ABL-inhibitor imatinib mesylate prevented amoeboid movement and markedly reduced homotypic interactions, causing cells to acquire a globular shape to rearrange F-actin to a microvillus form that closely resembled that of CLL cells isolated directly from circulation. CONCLUSION: We suggest that ABL1-induced amoeboid motility and homotypic interaction represent a distinctive early response to the tissue environment by CLL lymphocytes. This response is separate from that induced by chemokine or during heterotypic cell-contact, and may play a role in the initial entry and interactions of CLL lymphocytes in tissues.

Effect of cloretazine (VNP40101M) on acute myeloid leukaemia blast cells in vitro as a single agent and combined with cytarabine and daunorubicin.

We have investigated the effect of cloretazine (VNP40101M or Laromustine), a novel sulfonylhydrazine alkylating agent with significant antileukaemic activity, alone, or combined with cytarabine or daunorubicin, on the proliferation, viability and apoptosis of cell lines and acute myeloid leukaemia blast cells in vitro. Cloretazine alone induced a concentration-dependent inhibition of proliferation, reduction in cell viability and an increase in apoptosis in all samples tested. Combinations of cloretazine with varying concentrations of cytarabine or daunorubicin further enhanced these inhibitory effects, suggesting VNP40101M may have a role in combined low dose chemotherapy regimes especially in the elderly.

Qualitative analysis of sketched route maps: translating a sketch into linguistic descriptions.

In this correspondence, we introduce our work on sketch understanding, focusing here on the analysis of a sketched route map. A route map is drawn to help someone navigate along a path for the purpose of reaching a goal. A hand-sketched route map does not generally contain complete map information and is not necessarily drawn to scale, but yet it contains the correct qualitative information for route navigation. Here we propose a methodology for extracting a qualitative model of a sketched route map, based on human navigation strategies, using spatial relationships. Linguistic descriptions are generated from the sketch, both in the form of detailed descriptions at discrete path steps and also as a high-level route description. To describe the path linguistically, one must first be able to understand the path in a qualitative sense. We assert that the translation of a sketch into linguistic descriptions illustrates that the essential qualitative path knowledge has been extracted. The methodology is demonstrated using example sketches drawn on a handheld PDA.