Ultrasound strain rate imaging of individual muscle motor units

Skeletal muscle is organized in motor units, each comprising a motor neuron and all its connected muscle fibres. The arrival of an action potential (a neural “impulse”) causes the fibers to contract, they exhibit a twitch. This study aimed for the spatiotemporal detection of individual twitches, which may allow for a more detailed real-time study of muscle physiology and higher fidelity in applications such as prosthesis control. We used a commercial ultrasound scanner and a linear probe in a clamped and fixed position over the biceps, with the image plane perpendicular to the muscle fibers. The strain rate scans were made with a frequency of 15MHz and a frame rate of approximately 215 FPS. Recordings of tiny voluntary isometric muscle contractions were made, with ElectroMyoGraphic (EMG) electrodes placed on each side of the probe to detect the Associated Motor Unit Action Potentials (MUAPs). The recordings were analyzed using the scanner’s Quantitative analysis (Q-analysis) tool for measuring strain rates within selected Regions Of Interest (ROIs). The results indicate that it is possible to image the mechanical response of a single motor unit by using ultrasonic strain rate imaging. This technique could thus be a future supplement to EMG in certain applications

System training and assessment in simultaneous proportional myoelectric prosthesis control

Background Pattern recognition control of prosthetic hands take inputs from one or more myoelectric sensors and controls one or more degrees of freedom. However, most systems created allow only sequential control of one motion class at a time. Additionally, only recently have researchers demonstrated proportional myoelectric control in such systems, an option that is believed to make fine control easier for the user. Recent developments suggest improved reliability if the user follows a so-called prosthesis guided training (PGT) scheme. Methods In this study, a system for simultaneous proportional myoelectric control has been developed for a hand prosthesis with two motor functions (hand open/close, and wrist pro-/supination). The prosthesis has been used with a prosthesis socket equivalent designed for normally-limbed subjects. An extended version of PGT was developed for use with proportional control. The control system’s performance was tested for two subjects in the Clothespin Relocation Task and the Southampton Hand Assessment Procedure (SHAP). Simultaneous proportional control was compared with three other control strategies implemented on the same prosthesis: mutex proportional control (the same system but with simultaneous control disabled), mutex on-off control, and a more traditional, sequential proportional control system with co-contractions for state switching. Results The practical tests indicate that the simultaneous proportional control strategy and the two mutex-based pattern recognition strategies performed equally well, and superiorly to the more traditional sequential strategy according to the chosen outcome measures. Conclusions This is the first simultaneous proportional myoelectric control system demonstrated on a prosthesis affixed to the forearm of a subject. The study illustrates that PGT is a promising system training method for proportional control. Due to the limited number of subjects in this study, no definite conclusions can be drawn

Low-Order Nonlinear Animal Model of Glucose Dynamics for a Bihormonal Intraperitoneal Artificial Pancreas

Objective: The design of an Artificial Pancreas to regulate blood glucose levels requires reliable control methods. Model Predictive Control has emerged as a promising approach for glycemia control. However, model-based control methods require computationally simple and identifiable mathematical models that represent glucose dynamics accurately, which is challenging due to the complexity of glucose homeostasis. Methods: In this work, a simple model is deduced to estimate blood glucose concentration in subjects with Type 1 Diabetes Mellitus. Novel features in the model are power-law kinetics for intraperitoneal insulin absorption and a separate glucagon sensitivity state. Profile likelihood and a method based on singular value decomposition of the sensitivity matrix are carried out to assess parameter identifiability and guide a model reduction for improving the identification of parameters. Results: A reduced model with 10 parameters is obtained and calibrated, showing good fit to experimental data from pigs where insulin and glucagon boluses were delivered in the intraperitoneal cavity. Conclusion: A simple model with power-law kinetics can accurately represent glucose dynamics submitted to intraperitoneal insulin and glucagon injections. Importance: The parameters of the reduced model were not found to lack of local practical or structural identifiability

Stability analysis of snake robot locomotion based on Poincaré maps

Abstract — This paper presents an analysis of snake locomotion that explains how non-uniform viscous ground friction conditions enable snake robots to locomote forward on a planar surface. The explanation is based on a simple mapping from link velocities normal to the direction of motion into propulsive forces in the direction of motion. From this analysis, a controller for a snake robot is proposed. A Poincaré map is employed to prove that all state variables of the snake robot, except for the position in the forward direction, trace out an exponentially stable periodic orbit. I

SnakeSIM: a ROS‑based Control and Simulation Framework for Perception‑Driven Obstacle‑Aided Locomotion of Snake Robots

Biological snakes are capable of exploiting roughness in the terrain for locomotion. This feature allows them to adapt to different types of environments. Snake robots that can mimic this behaviour could be fitted with sensors and used for transporting tools to hazardous or confined areas that other robots and humans are unable to access. Snake robot locomotion in a cluttered environment where the snake robot utilises a sensory–perceptual system to perceive the surrounding operational environment for means of propulsion can be defined as perception-driven obstacle-aided locomotion (POAL). The initial testing of new control methods for POAL in a physical environment using a real snake robot imposes challenging requirements on both the robot and the test environment in terms of robustness and predictability. This paper introduces SnakeSIM, a virtual rapid-prototyping framework that allows researchers for the design and simulation of POAL more safely, rapidly and efficiently. SnakeSIM is based on the robot operating system (ROS) and it allows for simulating the snake robot model in a virtual environment cluttered with obstacles. The simulated robot can be equipped with different sensors. Tactile perception can be achieved using contact sensors to retrieve forces, torques, contact positions and contact normals. A depth camera can be attached to the snake robot head for visual perception purposes. Furthermore, SnakeSIM allows for exploiting the large variety of robotics sensors that are supported by ROS. The framework can be transparently integrated with a real robot. To demonstrate the potential of SnakeSIM, a possible control approach for POAL is considered as a case study