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13:00   Neuromechanics III Chair: Dick Plettenburg 13:00 15 mins MUSCLE SYNERGIES IN PEOPLE WITH FACIOSCAPULOHUMERAL DYSTROPHY DURING SHOULDER ABDUCTION Hans Essers, Koen Peters, Anneliek Peters, Kenneth Meijer, Alessio Murgia Abstract: Facioscapulohumeral Dystrophy (FSHD) is a progressive disease characterized by muscle wasting, primarily affecting muscles in the facial and shoulder area. A weakened shoulder girdle is associated with instability of the shoulder joint, often visible as winging of the scapula [1], and a decrease in range of motion [2]. However, it is not yet clear if FSHD also affects the upper limb motor coordination or muscle synergies. Muscle synergies have been proposed as a simplifying principle of generation of movements based on a low-dimensional control by the central nervous system [3] which describes groups of muscles that are working together for a given timing and amplitude of muscle activity. Hypothesis is that compensatory muscle synergies are formed for people with FSHD to energy-efficiently cope with varied decreases in muscle strength involving the shoulder muscles, a changed anatomical position of the scapula, and an increased instability in the shoulder joint. This study focussed on shoulder abduction as effects will be most evident due to the requirement of scapula movement for full upper limb elevation. Muscle activity from one male participant with FSHD (P1) and one age-matched healthy male participant (C1) were recorded via electromyography (EMG) at 2000Hz while participants performed shoulder abduction. The EMG data was cut to contain the same degree of shoulder abduction, then filtered with a 4th order Butterworth 20-450Hz bandpass filter, rectified, smoothened with a 100ms moving window, and normalized to amplitudes derived from a maximum voluntary contraction. The processed EMG data was used as input for the Non-negative Matrix Factorization which decomposed the data into muscle synergies and activation commands [4]. The muscle synergy that is involved in mobilization of the shoulder complex accounted for the highest amount of variance. For C01, this muscle synergy consisted of Trapezius Descendens (TD) and Ascendens (TA), and medial Deltoid (MD) with a smaller contribution from Pectoralis Major (PM), Serratus Anterior (SA) and Latissimus Dorsi (LD). For P11, when compared with C01, an earlier onset of the activation commands was found for all muscles, but with a decrease in activity of TA and SA, and an increase of TD and PM. The decreased activity of TA and SA is in agreement with the characteristics of scapular winging. The increased activity of TD is a likely compensation for the lack of scapular movement due to decreased TA and SA activity. The increased PM activity is presumably used to limit the movements of the humerus. This pilot study showed compensatory alterations in the muscle synergy that mobilizes the shoulder complex for a person with FSHD compared with a healthy participant. 13:15 15 mins ESTIMATING THE COMPLETE GROUND REACTION FORCES AND MOMENTS DURING WALKING USING INERTIAL MOTION CAPTURE Angelos Karatsidis, Giovanni Bellusci, Martin Schepers, Mark de Zee, Michael Skipper Andersen, Peter Veltink Abstract: Whole-body inverse dynamics techniques have been recently proposed to assess the ground reaction forces and moments (GRF&M) only from motion data. Even though such techniques remove the dependency on force plate measurements, they are still bounded by the restrictions imposed by optical motion capture, i.e. the limited marker tracking volume, increased complexity, and requirement of a laboratory space. As a result, GRF&M prediction techniques cannot be applied in ambulatory environments, outside the lab. To tackle this limitation, we propose a method to estimate the GRF&M using only Xsens MVN, a robust ambulatory motion capture system consisted of 17 inertial measurement units. A custom-made program was developed, in which the Newton-Euler equations of motion were used to predict the total external forces and moments, which, during single stance, balances the GRF&M applied on the foot in contact with the ground. However, during double stance the equations of motion result in the sum of left & right GRF&M, and we therefore use a smooth transition assumption to distribute this sum between both feet. To evaluate our method, we measured 11 healthy subjects, recording simultaneously using the Xsens MVN system and AMTI force plates. The accuracy of our GRF&M estimates versus the force plate measurements was assessed using Pearson correlation coefficient (ρ) and relative root mean square error (rRMSE). The results showed excellent correlation coefficients and low to moderate rRMSE for the vertical (ρ=0.99, rRMSE=5.9±3.1%), anterior: (ρ=0.95, rRMSE=8.0±2.0%), and sagittal: (ρ=0.90, rRMSE=14.9±3.84%) GRF&M. Strong correlations and moderate to high rRMSE were observed in the other three components (lateral: ρ=0.85, rRMSE=15.2±4.7%, frontal: ρ=0.73, rRMSE=40.2±18.6%, transverse: ρ=0.85, rRMSE =21.0±6.4 %). To our knowledge, this study was the first to estimate GRF&M using a technique based on inertial measurement units. Since force measurements are usually impractical outside the lab, the use of inertial motion capture increases the value of motion-based GRF&M estimation. Moreover, the performance was comparable to optical motion capture-based estimates, reported in previous studies. Future work should investigate the suitability of this method in assessing GRF&M and joint loading in daily life, clinical and sport applications. 13:30 15 mins INFLUENCE OF HORIZONTAL FORCES WHEN MEASURING BALANCE CONTROL ON A TREADMILL Ingrid Schut, Jolanda Roelofs, Jantsje Pasma, Herman van der Kooij, Vivian Weerdesteyn, Alfred Schouten Abstract: ABSTRACT People who sustained a stroke often undergo impaired balance involving complex contributions of neural, muscular and sensory systems. To give insight into the neurophysiological mechanisms underlying impaired balance, system identification techniques in combination with perturbations can be used in which the body is perturbed using dedicated and large devices such as motion platforms, which are unavailable in most labs and clinics. Treadmills are becoming more popular and affordable for gait training in neurological patients. This study investigates the possibilities of measuring standing balance control using a treadmill by focusing on which ground reaction forces are necessary to identify the neurophysiological mechanisms. In this study, 2 healthy women were asked to maintain their balance while standing on a dual force plate treadmill equipped with a motion capture device, while the belt speed was perturbed in both directions around an equilibrium position. A multisine perturbation containing frequencies in the range of 0.05-5 Hz was applied on the belt with a peak-to-peak translation of 23 cm. Each subject performed three trials of 100 seconds. Horizontal and vertical ground reaction forces were measured to calculate the corrective ankle torque consisting of a horizontal torque component and a vertical torque component respectively. The corrective ankle torque was calculated both with and without incorporating the horizontal forces. Body kinematics were measured using a motion capture system to calculate the body sway. Both the corrective ankle torque with and without incorporating the horizontal forces and body sway were used for system identification techniques to calculate the frequency response function (FRF) of the neuromuscular controller, which describes the amount and timing of the response of the ankle torque to the body sway by a magnitude and phase respectively, resulting in two FRFs for both subjects. Preliminary results show that the averaged root mean square of the horizontal torque component is 0.17 Nm whereas the vertical torque component has an averaged root mean square of 27 Nm. All subjects show that the mean of the FRFs calculated without horizontal torque component does not exceed the standard deviation boundaries of the FRFs calculated with horizontal torque component. This study shows that the horizontal torque component seems negligible to the ankle torque and FRF of the neuromuscular controller and therefore could be ignored when measuring standing balance control, which simplifies the setup of the instrumented treadmill. 13:45 15 mins THE RELATION BETWEEN VESTIBULAR FUNCTION AND SENSORY REWEIGHTING DURING STANCE IN PATIENTS WITH VESTIBULAR DISORDERS Joost van Kordelaar, Jantsje Pasma, Massimo Cenciarini, Alfred Schouten, Herman van der Kooij, Christoph Maurer Abstract: Joost van Kordelaar*, Jantsje H. Pasma†, Massimo Cenciarini‡, Alfred C. Schouten*†, Herman van der Kooij*† and Christoph Maurer‡ *Department of Biomechanical Engineering, Inst. for Biomedical Technology and Technical Medicine (MIRA), University of Twente, P.O. Box 217, 7500 AE Enschede, The Netherlands † Department of Biomechanical Engineering, Delft University of Technology, Mekelweg 2, 2628 CD Delft, The Netherlands ‡ Department of Neurology, University Clinics Freiburg, Breisacher Straβe 86, 79110 Freiburg im Breisgau, Germany ABSTRACT Vestibular deficits affect the ability to use and reweight vestibular information during stance. However, vestibular-ocular reflex (VOR) tests designed to detect vestibular deficits mainly test semi-circular canal function in horizontal direction, whereas for balance control otolith function in vertical direction is also important [1]. In this study we investigated how common VOR tests are related to the ability to reweight vestibular information under different sensory disturbance conditions in patients with vestibular disorders. 12 Patients (5 female) with vestibular disorders (60.5 ± 9.4 years) were included. Patients underwent videonystagmography during spontaneous nystagmus, bilateral cold caloric test, the rotational chair test at horizontal harmonic chair oscillations at 0.2 Hz and the head impulse test. Balance control experiments were conducted using continuous support surface rotations (SS) which followed a pseudo-random ternary sequence (PRTS). Four conditions were used, combining 0.5 and 1.0 degrees peak-to-peak SS rotations with eyes open and eyes closed. System identification and parameter estimation were used to estimate balance control model parameters, including the proprioceptive weight (Wp) which allows to determine how much patients relied on proprioceptive information [2]. The correlation between VOR tests and between VOR tests and the difference in Wp between the two SS amplitudes during eyes open (ΔWp_eo) and eyes closed (ΔWp_ec) conditions was determined. Significant correlations were found between spontaneous nystagmus eye velocity and the eye velocity offset during the rotational chair test (ρ = 0.92, p < 0.001) and between the eye velocity gain and offset during the rotational chair test (ρ = 0.68, p = 0.04). Trends were found between ΔWp_eo and spontaneous nystagmus eye velocity (ρ = -0.54, p = 0.09), the eye velocity gain during the rotational chair test (ρ = -0.55, p = 0.08) and eye velocity offset during the rotational chair test (ρ = -0.55, p = 0.09) and between and ΔWp_ec and eye velocity offset during the rotational chair test (ρ = -0.55, p = 0.09). Our results suggest that different VOR tests assess different dynamics of the vestibular system and provide only partially overlapping information. Furthermore, only moderate insignificant relations between VOR tests and sensory reweighting were found, suggesting that there is not a direct linear relationship between vestibular deficits and sensory reweighting disorders. FUNDING This study was part of the European Union FP7-ICT project 610454 ‘EMBalance REFERENCES [1] J. Allum, “An overview of the clinical use of dynamic posturography in the differential diagnosis of balance disorders”, J Vestib Res, Vol. 9, pp. 223-252, (1999). [2] R.J. Peterka, “Sensorimotor integration in human postural control”, J Neurophysiol, Vol. 88, pp 1097-1118, (2002). 14:00 15 mins ESTIMATION OF FULL-BODY POSES USING ONLY FIVE INERTIAL SENSORS: AN EAGER OR LAZY LEARNING APPROACH? Frank Wouda, Matteo Giuberti, Giovanni Bellusci, Peter Veltink Abstract: Human motion capture systems can be simplified by using the large amount of available high quality motion capture data, to decrease the number of body-worn sensors. One of the first data-driven approaches used six reflective markers placed on the body [1], recorded with two video cameras, to estimate full-body movements. Tautges et. al [2] used few accelerometers instead, but with the addition of scaling in the temporal domain. Both examples used Nearest Neighbor Search (NNS), a lazy learning algorithm, to estimate full-body poses. An eager learning algorithm does not require the training database to be available at runtime, but has not yet been applied for this problem. To that end we evaluated the performance of both NNS and Artificial Neural Networks (ANNs) for the estimation of full-body poses using orientations obtained from only five Inertial Measurement Units (IMUs) with magnetometers. 25 minutes of movements of different activities, such as gait, Activities of Daily Living (ADLs) and sports for 6 subjects were recorded using Xsens MVN. Full-body poses were used as the output and orientations of individual sensors were mapped to body segments to provide the input for training and testing of both algorithms. Six sensor configurations were tested, where the smallest joint position error was obtained (7 cm using ANN and 8 cm using NNS) for sensors placed at both upper arms/legs and the pelvis. On the other hand the smallest joint angle error (7 degrees for ANN, 8 degrees for NNS) was obtained with an asymmetric configuration. Gait poses were estimated with smaller average errors (6-7 cm, 7 degrees), compared to movements involving more poses, such as ADL (9-11 cm, 7-10 degrees). Similar error profiles for different subjects showed that both ANN and NNS can generalize over subjects. Magnetic disturbances could result in heading errors of approximately 4 degrees. Such magnetic noise was applied to input orientations, which resulted in an increased average joint position error of 1 cm, which shows possibilities for applying such a reduced sensor system. Our results show that differences between both algorithms were small. Choosing either a lazy or eager learning approach would therefore depend on specific requirements for a certain application, such as real-time estimation, memory requirements, noise sensitivity. This solution enables full-body pose estimation using five individual IMUs. 14:15 15 mins MECHANICAL INTERACTIONS BETWEEN EXTRINSIC MUSCLES DURING SINGLE FINGER FLEXION Mojtaba Mirakhorlo, Huub Maas, Dirkjan Veeger Abstract: Fingers of the human hand cannot exert force fully independently [1]. Such finger enslaving has been investigated predominantly for isometric finger tasks [1, 2] or during finger movements [3, 4]. Investigating finger interaction during dynamic tasks, which involves both force exertion and movement, can provide more insight into the relative contribution of neuromuscular control and muscle-tendon mechanics. The aim of this study was to assess if the extent of force enslaving is dependent on relative finger movements. Eleven right-handed subjects (22-30 years) flexed the index finger while overcoming constant resistance forces orthogonal to the fingertip. The non-instructed fingers were held at a constant extended position. EMG activity of flexor digitorum profundus (FDS) and extensor digitorum (ED) in the regions corresponding to the index, middle and ring fingers were measured. During flexion of the index finger, forces applied by the non-instructed fingers increased substantially (by 0.4 to 0.7 N) leading to enhanced enslaving effects. This increase was found 300-350 ms after the initiation of index flexion. In contrast to the finger forces, no significant changes in EMG activity of the non-instructed fingers FDS regions upon flexion of the index finger were found. Thus, the response to index finger flexion of fingertip forces in the non-instructed fingers was different to that of their corresponding EMG activities. The mismatch between force and EMG responses in the non-instructed fingers, together with the delay in force development suggests that mechanical connections between muscle-tendon structures were (at least partly) responsible for the observed increase in finger force enslaving during movement. REFERENCES 1. Zatsiorsky VM, L.Z., Latash ML Coordinated force production in multi-nger tasks: nger interaction and neural network modeling. Biol Cybern, 1998. 79: p. 139150. 2. Kapur, S., et al., Finger interaction in a three-dimensional pressing task. Experimental brain research, 2010. 203(1): p. 101-118. 3. Lang, C.E. and M.H. Schieber, Human finger independence: limitations due to passive mechanical coupling versus active neuromuscular control. Journal of neurophysiology, 2004. 92(5): p. 2802-2810. 4. Häger-Ross, C. and M.H. Schieber, Quantifying the independence of human finger movements: comparisons of digits, hands, and movement frequencies. The Journal of neuroscience, 2000. 20(22): p. 8542-8550.