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This study developed a method of discriminating real-time motion from electromyogram (EMG) signals. We previously proposed a real-time motion discrimination method using hyper-sphere models that discriminated five motions (open, grasp, pinching, wrist extension, and wrist flexion) above 90% and quickly learned EMG signals. Our method prevents elbow motions from interfering with hand motion discrimination...
This paper deals with the development of a coordinated control system for a robot and robot-driven shape memory alloy (SMA) actuated needle to follow a curvilinear path for percutaneous intervention. The robot driving the needle is considered as the outer loop and the non-linear SMA actuated flexible needle system forms the inner loop. The two feedback control loops are coordinated in such a way that...
Robotic surgery is being used widely due to its various benefits that includes reduced patient trauma and increased dexterity and ergonomics for the operating surgeon. Making the whole or part of the surgical procedure autonomous increases patient safety and will enable the robotic surgery platform to be used in telesurgery. In this work, an Electrosurgery procedure that involves tissue compression...
Percutaneous intervention is a common Minimally Invasive (MI) surgical procedure for the treatment of various disorders. It generally involves the insertion of slender needles deep within tissue, as lesions can be several centimetres below skin level. Consequently, deviations might occur which need to be accounted for and corrected by steering the needle tip during the insertion process. Needle steering...
This paper presents a monocular camera (MC) and inertial measurement unit (IMU) integrated approach for indoor position estimation. Unlike the traditional estimation methods, we fix the monocular camera downward to the floor and collect successive frames where textures are orderly distributed and feature points robustly detected, rather than using forward oriented camera in sampling unknown and disordered...
In this study, we propose to evaluate a 7 DOF exoskeleton in terms of motion control. Using criteria from the human motor control literature, inverse optimization was performed to assess an industrial screwing movement. The results of our study show that the hybrid composition of the free arm movement was accurately determined. At contrary, when wearing the exoskeleton, which produces an arbitrary...
Electrocorticogram (ECoG) is a promising long-term signal acquisition platform for brain-computer interface (BCI) systems such as upper extremity prostheses. Several studies have demonstrated decoding of arm and finger trajectories from ECoG high-gamma band (80–160 Hz) signals. In this study, we systematically vary the velocity of three elementary movement types (pincer grasp, elbow and shoulder flexion/extension)...
In this paper we present a novel methodology for classifying cells by using a combination of dielectrophoresis, image tracking and classification algorithms. We use dielectrophoresis to induce unique motion patterns in cells of interest. Motion is extracted via multi-target multiple-hypothesis tracking. Trajectories are then used to classify cells based on a generalized likelihood ratio test. We present...
This paper describes a novel method for the identification of time-varying ankle joint dynamic stiffness during large passive movements. The method estimates a linear parameter varying parallel-cascade (LPV-PC) model of joint stiffness consisting of two pathways: (a) an LPV impulse response function (IRF) for intrinsic mechanics and (b) an LPV Hammerstein cascade with time-varying static nonlinearity...
Day to day variability and non-stationarity caused by changes in subject motivation, learning and behavior pose a challenge in using local field potentials (LFP) for practical Brain Computer Interfaces. Pattern recognition algorithms require that the features possess little to no variation from the training to test data. As such models developed on one day fail to represent the characteristics on...
Decoding the user intention from non-invasive EEG signals is a challenging problem. In this paper, we study the feasibility of predicting the goal for controlling the robot arm in self-paced reaching movements, i.e., spontaneous movements that do not require an external cue. Our proposed system continuously estimates the goal throughout a trial starting before the movement onset by online classification...
Hand human gesture recognition has been an important research topic widely studied around the world, as this field offers the ability to identify, recognize, and analyze human gestures in order to control devices or to interact with computer interfaces. In particular, in medical training, this approach is an important tool that can be used to obtain an objective evaluation of a procedure performance...
Haptics combined with functional magnetic resonance imaging (Haptic fMRI) can non-invasively study how the human brain coordinates movement during complex manipulation tasks, yet avoiding associated fMRI artifacts remains a challenge. Here, we demonstrate confound-free neural activation measurements using Haptic fMRI for an unconstrained three degree-of-freedom motor task that involves planning, reaching,...
This paper describes the design of a new knee joint mechanism, called the Adaptive Coupling Joint (ACJ). The new mechanism has an adaptive trajectory of the center of rotations (COR) that automatically matches those of the attached biological joint. The detailed design is presented as well as characterization results of the ACJ. Conventional exoskeleton and assistive devices usually consider limb...
This paper presents a new design of the BirthSIM simulator. Its goal is to help obstetricians and midwives to train and improve their skills during childbirth delivery. The new version of the BirthSIM is more actuated than the previous version in order to be more biofidelic and cover various scenarios. The direct and inverse geometric models of the haptic interface are presented. The working space...
A non-contact vision-based system is presented for continuous respiratory rate monitoring. The system identifies feature points in a video feed and tracks them over time. Two methods are presented for comparison — a method which uses principal component analysis (PCA) and a simple averaging approach. These methods condense the feature point trajectories into a compact set of representative signals...
The non-invasive monitoring of the frequency of intestinal pacemaker activity (slow wave, SW) has an important diagnostic value. However the presence of noise, physiological interferences and spurious peaks of the spectral estimators can yield to misidentification of SW frequency when using conventional dominant frequency detection method. In this paper, two methods of ridge extraction from the time-frequency...
We present a novel swing phase controller for powered transfemoral prostheses based on minimum jerk theory. The proposed controller allows physiologically appropriate swing movement at any walking speed, regardless of the stance controller action. Preliminary validation in a transfemoral amputee subject demonstrates that the proposed controller provides physiological swing timing, without speed-or...
This study investigated nonlinear patterns of coordination, or synergies, underlying whole-hand grasping kinematics. Prior research has shed considerable light on roles played by such coordinated degrees-of-freedom (DOF), illuminating how motor control is facilitated by structural and functional specializations in the brain, peripheral nervous system, and musculoskeletal system. However, existing...
Functional electrical stimulation (FES) could restore motor functions for individuals with spinal cord injury (SCI). By applying electric current pulses, FES system could produce muscle contractions, generate joint torques, and thus, achieve joint movements automatically. Since the muscle system is highly nonlinear and time-varying, feedback control is quite necessary for precision control of the...
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