48,518 research outputs found
Cycle-to-cycle control of swing phase of paraplegic gait induced by surface electrical stimulation
Parameterised swing phase of gait in paraplegics was obtained using surface electrical stimulation of the hip flexors, hamstrings and quadriceps; the hip flexors were stimulated to obtain a desired hip angle range, the hamstrings to provide foot clearance in the forward swing, and the quadriceps to acquire knee extension at the end of the swing phase. We report on two main aspects; optimisation of the initial stimulation parameters, and parameter adaption (control). The initial stimulation patterns were experimentally optimised in two paraplegic subjects using a controlled stand device, resulting in an initial satisfactory swinging motion in both subjects. Intersubject differences appeared in the mechanical output (torque joint) per muscle group. During a prolonged open-loop controlled trial with the optimised but unregulated stimulation onsets and burst duration for the three muscle groups, the hip angle range per cycle initially increased above the desired value and subsequently decreased below it. The mechanical performance of the hamstrings and quadriceps remained relatively unaffected. A cycle-to-cycle controller was then designed, operating on the basis of the hip angle ranges obtained in previous swings. This controller successfully adapted the burst duration of the hip flexors to maintain the desired hip angle range
4D Continuous Descent Operations Supported by an Electronic Flight Bag
This paper describes a set of flight simulation
experiments carried out with the DLR’s Generic Cockpit
Simulator (GECO). A new concept named time and energy
managed operations (TEMO), which aims to enable advanced
four dimensional (4D) continuous descent operations (CDO), was
evaluated after three full days of experiments with qualified
pilots. The experiment focused to investigate the possibility of
using a 4D-controller on a modern aircraft with unmodified or
only slightly modified avionic systems. This was achieved by
executing the controller in an Electronic Flight Bag (EFB) and
using the pilot to “close the loop” by entering speed and other
advisories into the autopilot Flight Control Unit (FCU). The
outcome of the experiments include subjective (questionnaires
answered by pilots) and objective (trajectory logs) data. Data
analysis showed a very good acceptance (both in terms of safety
and operability of the procedure) from the participating crews,
only with minor suggestions to be improved in future versions of
the controller and the speed advisories update rates. Good time
accuracy all along the descent trajectory was also observed.Peer ReviewedPostprint (published version
A Learning-based Stochastic MPC Design for Cooperative Adaptive Cruise Control to Handle Interfering Vehicles
Vehicle to Vehicle (V2V) communication has a great potential to improve
reaction accuracy of different driver assistance systems in critical driving
situations. Cooperative Adaptive Cruise Control (CACC), which is an automated
application, provides drivers with extra benefits such as traffic throughput
maximization and collision avoidance. CACC systems must be designed in a way
that are sufficiently robust against all special maneuvers such as cutting-into
the CACC platoons by interfering vehicles or hard braking by leading cars. To
address this problem, a Neural- Network (NN)-based cut-in detection and
trajectory prediction scheme is proposed in the first part of this paper. Next,
a probabilistic framework is developed in which the cut-in probability is
calculated based on the output of the mentioned cut-in prediction block.
Finally, a specific Stochastic Model Predictive Controller (SMPC) is designed
which incorporates this cut-in probability to enhance its reaction against the
detected dangerous cut-in maneuver. The overall system is implemented and its
performance is evaluated using realistic driving scenarios from Safety Pilot
Model Deployment (SPMD).Comment: 10 pages, Submitted as a journal paper at T-I
Design and Development of an Affordable Haptic Robot with Force-Feedback and Compliant Actuation to Improve Therapy for Patients with Severe Hemiparesis
The study describes the design and development of a single degree-of-freedom haptic robot, Haptic Theradrive, for post-stroke arm rehabilitation for in-home and clinical use. The robot overcomes many of the weaknesses of its predecessor, the TheraDrive system, that used a Logitech steering wheel as the haptic interface for rehabilitation. Although the original TheraDrive system showed success in a pilot study, its wheel was not able to withstand the rigors of use. A new haptic robot was developed that functions as a drop-in replacement for the Logitech wheel. The new robot can apply larger forces in interacting with the patient, thereby extending the functionality of the system to accommodate low-functioning patients. A new software suite offers appreciably more options for tailored and tuned rehabilitation therapies. In addition to describing the design of the hardware and software, the paper presents the results of simulation and experimental case studies examining the system\u27s performance and usability
Machine learning-guided synthesis of advanced inorganic materials
Synthesis of advanced inorganic materials with minimum number of trials is of
paramount importance towards the acceleration of inorganic materials
development. The enormous complexity involved in existing multi-variable
synthesis methods leads to high uncertainty, numerous trials and exorbitant
cost. Recently, machine learning (ML) has demonstrated tremendous potential for
material research. Here, we report the application of ML to optimize and
accelerate material synthesis process in two representative multi-variable
systems. A classification ML model on chemical vapor deposition-grown MoS2 is
established, capable of optimizing the synthesis conditions to achieve higher
success rate. While a regression model is constructed on the
hydrothermal-synthesized carbon quantum dots, to enhance the process-related
properties such as the photoluminescence quantum yield. Progressive adaptive
model is further developed, aiming to involve ML at the beginning stage of new
material synthesis. Optimization of the experimental outcome with minimized
number of trials can be achieved with the effective feedback loops. This work
serves as proof of concept revealing the feasibility and remarkable capability
of ML to facilitate the synthesis of inorganic materials, and opens up a new
window for accelerating material development
A Hierarchical Emotion Regulated Sensorimotor Model: Case Studies
Inspired by the hierarchical cognitive architecture and the perception-action
model (PAM), we propose that the internal status acts as a kind of
common-coding representation which affects, mediates and even regulates the
sensorimotor behaviours. These regulation can be depicted in the Bayesian
framework, that is why cognitive agents are able to generate behaviours with
subtle differences according to their emotion or recognize the emotion by
perception. A novel recurrent neural network called recurrent neural network
with parametric bias units (RNNPB) runs in three modes, constructing a
two-level emotion regulated learning model, was further applied to testify this
theory in two different cases.Comment: Accepted at The 5th International Conference on Data-Driven Control
and Learning Systems. 201
Signal processing methodologies for an acoustic fetal heart rate monitor
Research and development is presented of real time signal processing methodologies for the detection of fetal heart tones within a noise-contaminated signal from a passive acoustic sensor. A linear predictor algorithm is utilized for detection of the heart tone event and additional processing derives heart rate. The linear predictor is adaptively 'trained' in a least mean square error sense on generic fetal heart tones recorded from patients. A real time monitor system is described which outputs to a strip chart recorder for plotting the time history of the fetal heart rate. The system is validated in the context of the fetal nonstress test. Comparisons are made with ultrasonic nonstress tests on a series of patients. Comparative data provides favorable indications of the feasibility of the acoustic monitor for clinical use
Research on computational and display requirements for human control of space vehicle boosters. Part 1 - Theory and results Final report, 22 Jun. - 22 Oct. 1966
Computational and display requirements for man-computer guidance and control techniques for reusable manned spacecraf
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