A minimal control schema for goal-directed arm movements based on physiological inter-joint coupling

Bockemühl T, Dürr V. A minimal control schema for goal-directed arm movements based on physiological inter-joint coupling. In: Proceedings of the International Conference on Neural Computation (ICNC 2010, Valencia, Spain). 2010.Substantial evidence suggests that nervous systems simplify motor control of complex body geometries by use of higher level functional units, so called motor primitives or synergies. Although simpler, such high level functional units still require an adequate controller. In a previous study, we found that kinematic inter-joint couplings allow the extraction of simple movement synergies during unconstrained 3D catching movements of the human arm and shoulder girdle. Here, we show that there is a bijective mapping between movement synergy space and 3D Cartesian hand coordinates within the arm's physiological working range. Based on this mapping, we propose a minimal control schema for a 10-DoF arm and shoulder girdle. All key elements of this schema are implemented as artificial neural networks (ANNs). For the central controller, we evaluate two different ANN architectures: a feed-forward network and a recurrent Elman network. We show that this control schema is capable of controlling goal-directed movements of a 10-DoF arm with as few as five hidden units. Both controller variants are sufficient for the task. However, end-point stability is better in the feed-forward controller

Ultra high-resolution biomechanics suggest that substructures within insect mechanosensors decisively affect their sensitivity

Insect load sensors, called campaniform sensilla (CS), measure strain changes within the cuticle of appendages. This mechanotransduction provides the neuromuscular system with feedback for posture and locomotion. Owing to their diverse morphology and arrangement, CS can encode different strain directions. We used nano-computed tomography and finite-element analysis to investigate how different CS morphologies within one location-the femoral CS field of the leg in the fruit fly Drosophila-interact under load. By investigating the influence of CS substructures' material properties during simulated limb displacement with naturalistic forces, we could show that CS substructures (i.e. socket and collar) influence strain distribution throughout the whole CS field. Altered socket and collar elastic moduli resulted in 5% relative differences in displacement, and the artificial removal of all sockets caused differences greater than 20% in cap displacement. Apparently, CS sockets support the distribution of distal strain to more proximal CS, while collars alter CS displacement more locally. Harder sockets can increase or decrease CS displacement depending on sensor location. Furthermore, high-resolution imaging revealed that sockets are interconnected in subcuticular rows. In summary, the sensitivity of individual CS is dependent on the configuration of other CS and their substructures

Location and arrangement of campaniform sensilla in Drosophila melanogaster

Sensory systems provide input to motor networks on the state of the body and environment. One such sensory system in insects is the campaniform sensilla (CS), which detect deformations of the exoskeleton arising from resisted movements or external perturbations. When physical strain is applied to the cuticle, CS external structures are compressed, leading to transduction in an internal sensory neuron. In Drosophila melanogaster, the distribution of CS on the exoskeleton has not been comprehensively described. To investigate CS number, location, spatial arrangement, and potential differences between individuals, we compared the front, middle, and hind legs of multiple flies using scanning electron microscopy. Additionally, we imaged the entire body surface to confirm known CS locations. On the legs, the number and relative arrangement of CS varied between individuals, and single CS of corresponding segments showed characteristic differences between legs. This knowledge is fundamental for studying the relevance of cuticular strain information within the complex neuromuscular networks controlling posture and movement. This comprehensive account of all D. melanogaster CS helps set the stage for experimental investigations into their responsivity, sensitivity, and roles in sensory acquisition and motor control in a light-weight model organism

Characterization and generation of targeted reaching movements in a redundant motor system using kinematic synergies

Bockemühl T. Characterization and generation of targeted reaching movements in a redundant motor system using kinematic synergies. Bielefeld: Universität Bielefeld; 2011

A small set of principal components can efficiently describe human arm movement

Bockemühl T, Dürr V. A small set of principal components can efficiently describe human arm movement. In: Proc.7th Congr.Int.Soc.Neuroethol. 2004: po 228-po 228

Hand trajectory data

Bockemühl T, Cruse H. Hand trajectory data. Bielefeld University; 2014.This archive contains the hand trajectory data of 25 participants. During the experiments, each participant completed several of the obstacle point configurations. These point configurations are detailed in the figure which can be found in the README contained in the zip file and can also be found in the MAT file 'pointConfigurations.mat'. The folder 'Participants' contains 25 sub-folders (e.g. participant 'AE'). Each of these sub-folder in turn contains several folders associated with a certain obstacle point configuration (e.g. 'A1'). In these folders you will find several MAT-Files, each of which contains the x- and y-coordinates of a trajectory of a single trial. In addition, you will find an overview figure depicting all trials of the participant associated with a particular obstacle configuration (gray lines), as well as the mean trajectory based on these trials (red line). This project was in the main carried out by Dr. Till Bockemühl and was supervised by Prof. Holk Cruse. More info: http://toolkit.cit-ec.uni-bielefeld.de/datasets/hand-trajectory-dat

Inter-joint coupling and joint angle synergies of human catching movements

Bockemühl T, Troje NF, Dürr V. Inter-joint coupling and joint angle synergies of human catching movements. Hum.Movement Sci. 2010;29(1):73-93.A central question in motor control is how the central nervous system (CNS) deals with redundant degrees of freedom (DoFs) inherent in the musculoskeletal system. One way to simplify control of a redundant system is to combine several DoFs into synergies. In reaching movements of the human arm, redundancy occurs at the kinematic level because there is an unlimited number of arm postures for each position of the hand. Redundancy also occurs at the level of muscle forces because each arm posture can be maintained by a set of muscle activation patterns. Both postural and force-related motor synergies may contribute to simplify the control problem. The present study analyzes the kinematic complexity of natural, unrestrained human arm movements, and detects the amount of kinematic synergy in a vast variety of arm postures. We have measured inter-joint coupling of the human arm and shoulder girdle during fast, unrestrained, and untrained catching movements. Participants were asked to catch a ball launched towards them on 16 different trajectories. These had to be reached from two different initial positions. Movement of the right arm was recorded using optical motion capture and was transformed into 10 joint angle time courses, corresponding to 3 DoFs of the shoulder girdle and 7 of the arm. The resulting time series of the arm postures were analyzed by principal components analysis (PCA). We found that the first three principal components (PCs) always captured more than 97% of the variance. Furthermore, subspaces spanned by PC sets associated with different catching positions varied smoothly across the arm's workspace. When we pooled complete sets of movements, three PCs, the theoretical minimum for reaching in 3D space, were sufficient to explain 80% of the data's variance. We assumed that the linearly correlated DoFs of each significant PC represent cardinal joint angle synergies, and showed that catching movements towards a multitude of targets in the arm's workspace can be generated efficiently by linear combinations of three of such synergies. The contribution of each synergy changed during a single catching movement and often varied systematically with target location. We conclude that unrestrained, one-handed catching movements are dominated by strong kinematic couplings between the joints that reduce the kinematic complexity of the human arm and shoulder girdle to three non-redundant DoFs

Principal components as motor synergies of human catching movements

Bockemühl T, Dürr V, Troje NF. Principal components as motor synergies of human catching movements. COMPARATIVE BIOCHEMISTRY AND PHYSIOLOGY A-MOLECULAR & INTEGRATIVE PHYSIOLOGY. 2006;143(4 (S):S110-S111

Motor synergies and object representations in virtual and real grasping

Maycock J, Bläsing B, Bockemühl T, Ritter H, Schack T. Motor synergies and object representations in virtual and real grasping. In: 1st International Conference on Applied Bionics and Biomechanics (ICABB). Venice, Italy: IEEE; 2010

Motorische Synergien und mentale Repräsentation von Handbewegungen beim Greifen virtueller Objekte

Bläsing B, Bockemühl T, Schack T. Motorische Synergien und mentale Repräsentation von Handbewegungen beim Greifen virtueller Objekte. In: Pfeffer I, Alfermann D, eds. Menschen in Bewegung - Sportpsychologie zwischen Tradition und Zukunft. Vol 188. Hamburg: Czwalina Verlag; 2009: 36