Geodesic synergy paper abstract

Peter D. Neilson, Megan D. Neilson, and Robin T. Bye. A Riemannian Geometry Model of Human Movement: The Geodesic Synergy Hypothesis. Human Movement Science 44: 42--72, 2015. Download PDF.


Mass-inertia loads on muscles change with posture and with changing mechanical interactions between the body and the environment. The nervous system must anticipate changing mass-inertia loads, especially during fast multi-joint coordinated movements. Riemannian geometry provides a mathematical framework for movement planning that takes these inertial interactions into account. To demonstrate this we introduce the controlled (vs. biomechanical) degrees of freedom of the body as the coordinate system for a configuration space with movements represented as trajectories. This space is not Euclidean. It is endowed at each point with a metric equal to the mass-inertia matrix of the body in that configuration. This warps the space to become Riemannian with curvature at each point determined by the differentials of the mass-inertia at that point. This curvature takes nonlinear mass-inertia interactions into account with lengths, velocities, accelerations and directions of movement trajectories all differing from those in Euclidean space. For newcomers to Riemannian geometry we develop the intuitive groundwork for a Riemannian field theory of human movement encompassing the entire body moving in gravity and in mechanical interaction with the environment. In particular we present a geodesic synergy hypothesis concerning planning of multi-joint coordinated movements to achieve goals with minimal muscular effort.

Decoupling paper abstract

Robin T. Bye, Peter D. Neilson, and Megan D. Neilson. The human operator favours decoupled control in aimed movement. Manuscript under preparation for submission to Human Movement Science during 2013.


Kinematic data from visual tracking and reaching and grasping experiments show that each degree of freedom in a multi-joint response can be independently controlled by corresponding independent components of the visual input. Some researchers have suggested that such independent visuomotor channels reflect separate neuroanatomical pathways, a view that fails to take into account the highly cross-coupled inertial, viscous, centrifugal, coriolis, gravitational, and reflex interactions present between efferent drives to muscles and resulting body movements. An alternative view is provided by AMT, which suggests that the human operator employs an adaptive, nonlinear, highly interactive, inverse neural controller that exactly compensate for the interactions within the neuromusculoskeletal system. The mathematical foundation of this controller has been presented previously and shows that such a controller can be formed in the central nervous system by biologically feasible adaptive filter mechanisms. Assuming that the system to be controlled has a stable inverse (a minimum phase system), the controller is able to render all of the dynamics (linear and nonlinear) apart from time delays unobservable in the visuomotor relationships while simultaneously maintaining independent decoupled control of each degree of freedom of the response. If, on the other hand, the system has an unstable inverse (a non-minimum phase system), there exists a tradeoff between two control strategies favouring either decoupling or cancellation of dynamics. The controller may detune its inverse model to achieve stability, and (1) obtain perfect cancellation of the dynamics of the system at the cost of not achieving decoupled control, or (2) maintain decoupled control of the system at the expense of cancelling only some of the dynamics. In this paper, we present findings from a visual tracking experiment where 24 participants were confronted with at two-input, two-output, dynamic, cross-coupled tracking system with an unstable inverse. The experiment shows that the participants preferred the second strategy, namely decoupling their response at the expense of accurately cancelling the dynamics of the non-minimum tracking system. This result contradicts the hypothesis of separate neuroanatomical pathways being responsible for decoupled control, since the external tracking system was cross-coupled. On the contrary, the neural controller proposed in AMT can explain the experimental result.


ECMS 2016 EEG wheelchair control paper abstract

Rolf-Magnus Hjørungdal, Filippo Sanfilippo, Ottar L. Osen, Adrian Rutle, and Robin T. Bye. A Game-based Learning Framework for Controlling Brain-Actuated Wheelchairs. In Proceedings of the 30th European Conference on Modelling and Simulation (ECMS'16), pp. xx--yy, 2016. Download PDF.


Paraplegia is a disability caused by impairment in motor or sensory functions of the lower limbs. Most paraplegic subjects use mechanical wheelchairs for their movement, however, patients with reduced upper limb functionality may benefit from the use of motorised, electric wheelchairs. Depending on the patient, learning how to control these wheelchairs can be hard (if at all possible), time-consuming, demotivating, and to some extent dangerous. This paper proposes a game-based learning framework for training these patients in a safe, virtual environment. Specifically, the framework utilises the Emotiv EPOC EEG headset to enable brain wave control of a virtual electric wheelchair in a realistic virtual world game environment created with the Unity 3D game engine.

ECMS 2016 EEG stroke rehabilitation paper abstract

Tom Verplaetse, Filippo Sanfilippo, Adrian Rutle, Ottar L. Osen, and Robin T. Bye. On Usage of EEG Brain Control for Rehabilitation of Stroke Patients. In Proceedings of the 30th European Conference on Modelling and Simulation (ECMS'16), pp. xx--yy, 2016. Download PDF.


This paper demonstrates rapid prototyping of a stroke rehabilitation system consisting of an interactive 3D virtual reality computer game environment interfaced with an EEG headset for control and interaction using brain waves. The system is intended for training and rehabilitation of partially monoplegic stroke patients and uses low-cost commercial-off-the-shelf products like the Emotiv EPOC EEG headset and the Unity 3D game engine. A number of rehabilitation methods exist that can improve motor control and function of the paretic upper limb in stroke survivors. Unfortunately, most of these methods are commonly characterised by a number of drawbacks that can limit intensive treatment, including being repetitive, uninspiring, and labour intensive; requiring one-on-one manual interaction and assistance from a therapist, often for several weeks; and involve equipment and systems that are complex and expensive and cannot be used at home but only in hospitals and institutions by trained personnel. Inspired by the principles of mirror therapy and game-stimulated rehabilitation, we have developed a first prototype of a game-like computer application that tries to avoid these drawbacks. For rehabilitation purposes, we deprive the patient of the view of the paretic hand while being challenged with controlling a  virtual hand in a simulated 3D game environment only by means of EEG brain waves interfaced with the computer. Whilst our system is only a first prototype, we hypothesise that by iteratively improving its design through refinements and tuning based on input from domain experts and testing on real patients, the system can be tailored for being used together with a conventional rehabilitation programme to improve patients' ability to move the paretic limb much in the same vain as mirror therapy. Our proposed system has several advantages, including being game-based, customisable, adaptive, and extendable. In addition, when compared with conventional rehabilitation methods, our system is extremely low-cost and flexible, in particular because patients can use it in the comfort of their homes, with little or no need for professional human assistance. Preliminary tests are carried out to highlight the potential of the proposed rehabilitation system, however, in order to measure its efficiency in rehabilitation, the system must first be improved and then run through an extensive field test with a sufficiently large group of patients and compared with a control group.

Tremor paper abstract

Robin T. Bye and Peter D. Neilson. The BUMP model of response planning: Intermittent predictive control accounts for 10 Hz physiological tremor. Human Movement Science, 29(5): 713--736, 2010. Download PDF.


Physiological tremor during movement is characterised by ~10 Hz oscillation observed both in the electromyogram activity and in the velocity profile. We propose that this particular rhythm occurs as the direct consequence of a movement response planning system that acts as an intermittent predictive controller operating at discrete intervals of ~100 ms. The BUMP model of response planning describes such a system. It forms the kernel of Adaptive Model Theory which defines, in computational terms, a basic unit of motor production or BUMP. Each BUMP consists of three processes: (1) analysing sensory information, (2) planning a desired optimal response, and (3) execution of that response. These processes operate in parallel across successive sequential BUMPs. The response planning process requires a discrete time interval in which to generate a minimum acceleration trajectory to connect the actual response with the predicted future state of the target and compensate for executional error. We have shown previously that a response planning time of 100 ms accounts for intermittency observed experimentally in visual tracking studies and for the psychological refractory period observed in double stimulation reaction time studies. We have also shown that simulations of aimed movement, using this same planning interval, reproduce experimentally observed speed-accuracy tradeoffs and movement velocity profiles. Here we show, by means of a simulation study of constant velocity tracking movements, that employing a 100 ms planning interval closely reproduces the measurement discontinuities and power spectra of electromyograms, joint-angles, and angular velocities of physiological tremor reported experimentally. We conclude that intermittent predictive control through sequential operation of BUMPs is a fundamental mechanism of 10 Hz physiological tremor in movement.


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