Movements by a standing person are commonly associated with adjustments in the activity of postural muscles to cause a desired shift of the center of pressure (COP) and keep balance. We hypothesize that such COP shifts are controlled (stabilized) using a small set of central variables (muscle modes, M-modes), while each M-mode induces changes in the activity of a subgroup of postural muscles. The main purpose of this study has been to explore the possibility of identification of muscle synergies in a postural task using the framework of the uncontrolled manifold (UCM) hypothesis employing the following three steps in data analysis: (i) Identification of M-modes: Subjects were asked to release a load from extended arms through a pulley system, resulting in a COP shift forward prior to load release. Electromyographic (EMG) activity of eleven postural muscles on one side of the body was integrated over a 100 ms interval corresponding to the early stage of the COP shift, and subjected to a principal component (PC) analysis across multiple repetitions of each task. Three PCs were identified and associated with a 'push-back M-mode', a 'push-forward M-mode' and a 'mixed M-mode'. (ii) Calculation of the Jacobian of the system, which relates changes in the magnitude of M-modes to COP shifts using regression techniques: Subjects performed three different tasks (releasing different loads at the back, voluntarily shifting body weight forward and backward, at different speeds) to verify if the relationship between magnitudes of M-modes and COP shifts is task or direction specific. (iii) UCM analysis: Three tasks were chosen (load release in the front, arm movement forward and backward) which were associated with an early shift in COP. A manifold was identified in the M-mode space corresponding to a certain average (across trials) shift of the COP and variance per degree of freedom within the UCM (V(UCM)) and orthogonal (V(ORT)) to the UCM was computed. Across subjects, V(UCM) was significantly higher than V(ORT) when analysis at the third step was performed using a Jacobian computed based on a set of tasks associated with a COP shift in the same direction but not in the opposite direction. This result confirms our hypothesis that the M-modes work together as a synergy to stabilize a desired shift of the COP. Forward and backward COP shifts are associated with different synergies based on the same three M-modes.

When a standing person performs a movement such that the center of gravity shifts, the activity of postural muscles adjusts to keep the balance. We assume that such adjustments are controlled using a small set of central variables, while each variable induces changes in the activity of a subgroup of postural muscles. The purpose of this study has been to identify such muscle groups (muscle modes or M-modes) and compare them across tasks and subjects. Four tasks required the subjects to release a load from extended arms leading to a center of pressure (COP) shift prior to the load release. The fifth task required an explicit COP shift by voluntary sway. Electromyographic activity of 11 postural muscles on one side of the body was integrated over a 100-ms interval corresponding to the early stage of the COP shift, and this integrated EMG activity was subjected to a principal component (PC) analysis across multiple repetitions of each task. Three PCs were identified and associated with a "push-back M-mode," a "push-forward M-mode," and a "mixed M-mode." Cluster analysis of the PC vectors across tasks and across subjects confirmed the existence of distinctive push-forward and push-back muscle groups. PC vectors were also compared across tasks and across subjects using cosines as a measure of colinearity between pairs of vectors. In general, M-modes were similar across both tasks and subjects. We conclude that shifts of the COP, whether implicit or explicit, are controlled using a small set of central variables associated with changes in the activity of robust subsets of postural muscles. These results can be used for future analysis of muscle synergies associated with postural tasks.

Muscle synergies in postural tasks have recently been studied using the framework of the uncontrolled manifold (UCM) hypothesis. A set of three hypothetical control variables, named M-modes, derived from the activity of 11 postural muscles, were identified. It was shown that postural synergies composed of these three M-modes preserve a certain shift of the center of pressure (COP) when subjects perform postural tasks while standing on a stable surface. In the present study we investigated the effects of support surface instability and availability of a light touch or grasp of a stable external support on the M-modes and their co-variation. The study was performed in two sessions. In the first session subjects released a load behind the body under four conditions: standing on a stable surface with no support (ST), standing on an unstable surface with no support (UN), standing on an unstable surface with a light touch (UN,T) and standing on an unstable surface with grasp of a stable object (UN,G). In the second session subjects performed two tasks: an arm movement backward and voluntary sway forward (towards the toes) under three conditions--ST, UN and UN,T. Principal component analysis was used to identify M-modes from data in the first session, and a UCM analysis was performed to study M-mode synergies in postural stabilization from data in the second session. A 'menu' of five M-modes was found, which were named either reciprocal M-modes or co-contraction M-modes based on the agonist-antagonist relationship of muscles comprising each mode. For a given task, subjects chose any three of these five M-modes in a subject- and task-specific manner. The reciprocal and co-contraction M-modes occurred equally frequently whether subjects stood on a stable or unstable support surface or whether a light touch was available or not. However, the co-contraction M-modes predominated when grasp of an object was available. In this condition, when the arm could be used for stabilization, there were M-modes uniting hip and shoulder muscles. However, the identified M-mode synergies were not found to lead to a consistent shift in the COP in any of the stability conditions. Possible reasons for this finding are discussed.

When a standing person applies a light finger touch to an external stable object, postural sway is reduced. We tested a hypothesis that two factors related to touch can induce this effect, the presence of a stable reference point and the modulation of contact forces leading to tissue deformation. Force platform signals were analyzed while subjects stood quietly with or without additional light touch to an external object (contact forces under 1 N). The point of touch on the body was manipulated. We also investigated the effects of active touch vs fixation of a finger at a point in external space. The results show that touch to the head or neck can be more effective in reducing body sway than a finger touch. A larger reduction in sway was observed when the finger was fixed in a clip (the net forces between the clip and the point of its fixation to the stand were under 1 N) as compared to a free light touch to a pad. The subjects showed a reduction in postural sway while holding a load suspended using a pulley system; in this situation, contact with the load via the pulley provided modulation of contact forces but not a fixed reference point. This finding emphasizes the importance of such factors as stability of the contact point and modulation of contact forces, as compared to active touch or to an implicit task of stabilizing the kinematic chain. The system of postural stabilization can reduce postural sway, making use of either of two sources of sensory information associated with touch, one related to providing a fixed reference point in space, and the other related to transient force changes at the point of contact related to the sway.

Stabilization of the center of mass (CM) is an important goal of the postural control system. Coordination of several joints along the human "pendulum" is required to achieve this goal. We studied the coordination among body segments with respect to horizontal CM stabilization during a quiet stance task and the effects of vision on CM stability. Subjects were asked to stand quietly on a narrow wooden block supporting only the mid-foot, with either open (EO) or closed (EC) eyes on separate trials. Instant equilibrium points (IEPs) in the center of pressure (CP) trajectory were determined when the horizontal component of the ground reaction force was zero and the CP data were decomposed into their rambling and trembling components. The joint angle, CM and CP data were divided into short cycles (time-normalized to 100 data points) or longer segments (time-normalized to 1000 data points) of equal length beginning and ending in an IEP. Motor abundance with respect to patterns of joint coordination was evaluated using the uncontrolled manifold (UCM) approach. Here, a UCM is a subspace spanning all joint combinations resulting in a given CM position. All combinations of joint angles that lie within this subspace are equivalent with respect to that CM position while joint angle combinations lying in a subspace orthogonal to the UCM lead to deviation from that CM position. UCM analysis was performed on data organized either across time within longer segments or at each point in time across multiple segments or across multiple cycles. Regardless of method of analysis, most of the variance in joint space was constrained to be within the UCM, preserving the mean CM position in both the EO and EC conditions. Joint configuration variance was significantly higher in the EC than in the EO condition although this increase occurred primarily within the UCM rather than in the orthogonal subspace that would have led to variation of the CM position. These results demonstrate the ability of the control system to selectively "channel" motor variability into directions in joint space that stabilize the CM position. This effect was enhanced when the task was made more challenging in the absence of vision. There was also a significant relationship between joint variance that led to a change in the CM position and, in particular, the rambling component of the CP path, lending some support to the idea that the CNS prescribes a certain stable trajectory of the CP during quiet stance that leads to a small controlled movement of the CM.

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This study investigated whether short-term modifications of gait could be induced in healthy adults and whether a combination of kinetic (a compliant force resisting deviation of the foot from the prescribed footpath) and visual guidance was superior to either kinetic guidance or visual guidance alone in producing this modification. Thirty-nine healthy adults, 20-33 years old, were randomly assigned to the three groups receiving six 10-min blocks of treadmill training requiring them to modify their footpath to match a scaled-down path. Changes of the footpath, specific joint events and joint moments were analyzed. Persons receiving combined kinetic and visual guidance showed larger modifications of their gait patterns that were maintained longer, persisting up to 2 h after intervening over-ground activities, than did persons receiving training with primarily kinetic guidance or with visual guidance alone. The results emphasize the short-term plasticity of locomotor circuits and provide a possible basis for persons learning to achieve more functional gait patterns following a stroke or other neurological disorders.

Healthy individuals modulate muscle activation patterns according to their intended movement and external environment. Persons with neurological disorders (e.g., stroke and spinal cord injury), however, have problems in movement control due primarily to their inability to modulate their muscle activation pattern in an appropriate manner. A functionality test at the level of individual muscles that investigates the activity of a muscle of interest on various motor tasks may enable muscle-level force grading. To date there is no extant work that focuses on the application of exoskeleton robots to induce specific muscle activation in a systematic manner. This paper proposes a new method, named "individual muscle-force control" using a wearable robot (an exoskeleton robot, or a power-assisting device) to obtain a wider variety of muscle activity data than standard motor tasks, e.g., pushing a handle by hand. A computational algorithm systematically computes control commands to a wearable robot so that a desired muscle activation pattern for target muscle forces is induced. It also computes an adequate amount and direction of a force that a subject needs to exert against a handle by his/her hand. This individual muscle control method enables users (e.g., therapists) to efficiently conduct neuromuscular function tests on target muscles by arbitrarily inducing muscle activation patterns. This paper presents a basic concept, mathematical formulation, and solution of the individual muscle-force control and its implementation to a muscle control system with an exoskeleton-type robot for upper extremity. Simulation and experimental results in healthy individuals justify the use of an exoskeleton robot for future muscle function testing in terms of the variety of muscle activity data.