Since all muscles move the same body, and there are multiple muscles moving the same joint, most muscles work in groups. From these data, we can estimate what signals the CNS must have sent. However, we can measure the outcome which is the muscle activation. We cannot measure the relevant synergy recruitment signals directly at source, that is, in the brain or other parts of the CNS. Dealing with low-dimensional data is very time-efficient and allows for processing multiple tasks at the same time. The bow-tie structure represents a model of reducing degrees of freedom, since it processes high-dimensional input and produces high-dimensional output by a rather low-dimensional processing unit. The CNS processes this relatively small amount of information and sends signals to the muscles that, in turn, move the highly redundant musculo-skeletal structure. An even smaller portion of this information is relevant to a particular task, such as balance maintenance. Only a portion of the information about the environment outside the human body enters the sensory system. We regard this hypothesis as an assumption for the existence of synergies. Our hypothesis about the control architecture of the CNS is based on the bow-tie structure proposed in. The mechanism of balance maintenance must be clarified in order to find a solution to this growing problem. In a society where humans are living longer than ever before, deterioration of ability to maintain balance poses a serious problem for elderly persons. We based our study on our previous work on human balance. We chose balance maintenance for our task to observe reflex and automatic responses of the central nervous system (CNS). In this study, we calculated synergies from EMG data and used an NMF method based on the Lee–Seung algorithm, which is a basic and fast NMF algorithm with multiplicative updating rules. Muscle synergies can be identified by factor analyses such as non-negative matrix factorization (NMF) and principal component analysis (PCA). Others have investigated reflexes in frogs by cutaneous mechanical stimulation and in cats through displacement of a supporting surface, as well as automatic postural responses in humans, where upright stance synergies were identified for different directions. Studies have focused on voluntary movements such as walking, cycling, and upper-limb reaching. Muscle synergies are calculated from electromyography (EMG) data, and have been described in frogs, cats, and humans. However, the existence of synergies is controversial, with studies providing evidence for and against the existence of muscle synergies. Some researchers define synergies as muscle activation of a set of muscles contributing to a particular movement where each muscle contributes to only one synergy. Different ways of grouping muscles into synergies can be found in the literature. A single muscle can be part of multiple muscle synergies, and a single synergy can activate various muscles. A muscle synergy is the activation of a group of muscles to contribute to a particular movement, thus reducing the dimensionality of muscle control. The term muscle synergy, also called motor synergy, neuromuscular synergy, or muscle mode, has been used in the literature extensively over the last decade. These results suggest that SSI can be used to quantitatively evaluate balance maintenance ability. Participants who were adept at maintaining balance were found to have invariant muscle synergies, and non-adept participants showed variable muscle synergies. We observed a positive proportional relation between balance performance and SSI.

Finally, from the calculated muscle synergies, we obtained SSI.

We then calculated muscle synergies attributed to postural reflex and automatic response by using non-negative matrix factorization (NMF). We measured the activity of muscles responsible for maintaining lateral balance in humans standing on a platform that was subjected to lateral disturbance from the platform. Here, we investigated the variability of muscle synergy and defined a synergy stability index (SSI) to quantify it. Though these synergies are rather stable over time, some variability is present. Muscle synergy theory suggests that the central nervous system produces a small number of signals that pass through a network that distributes combinations of these signals to the muscles. The signals that the central nervous system (CNS) produces and sends to the muscles to effect movement are not entirely understood.

Define synergy pattern