Neural and musculoskeletal modeling: Its role in neurorehabilitation

Abstract

HumanNeuroMusculoSkeletal systems (NMSSYs) are very complex and have redundant anatomical degrees of freedom (DOFs) at muscles and joints. These features enable them to easily perform dexterous tasks since the childhood. NMS SYs have attracted many researchers from different scientific domains such as neurophysiology, robotics, biomechanics, and neuro-rehabilitation engineering because of its multi-task functionalities. Humans can perform hundreds of tasks and dynamically interact with external environments in a very efficient way without thinking about the complexity of the motor task. Thinking about twirling a coin or writing tasks, the many complex operations needed to perform such actions rise important questions like “do we really perform very complex computations to control our musculoskeletal system?” or “how do we control our musculoskeletal system to perform such actions?” and “what is the main contribution of our biomechanical structure in the motor control task?”. Recently, scientists have paid more attention not only to the neural commands but also to the biomechanical properties of NMS Sys and their role in simplifying the motor control tasks. Muscles are the main building blocks in our biomechanical systems. They can be continuously co-activated to produce and to coordinate movements maintaining the stability.Muscle-tendon actuators have been physically modeled, based on Hill-Type model, to study their non-linear behaviours and characteristics. Those models were then integrated with neuron models to provide a better understanding of the local control mechanism of a motor unit (e.g. spinal cord motor neuron and muscle-tendon actuator). Motor unit behaviors are observed through the muscle activity: the physiological process of converting an electrical stimulus to a mechanical response. This process is fundamental to muscle physiology, whereby the electrical stimulus is usually an action potential and the mechanical response is contraction. The transformation from Electromyographic (EMG) signal to muscle activation is not trivial and can occur through several steps. Muscle activation dynamics is the physiological process described by those steps. In general, the control of NMS models can be achieved also by combining together the EMG signals to retrieve muscle synergies. Apparently, humans use different motor control strategies to command their actions, some already exist in the Central Nervous System (CNS) with their birth and many others are developed and/or adapted during their life and gained experiences. However, both views of control strategies suggest a task dependency of the neural control. More details on description of muscle co-activation patterns based on the two views of the task dependent motor control strategies are provided in this chapter which will give an insight not only on a higher level of neural control but also at a lower level control of muscles in the CNS. Computational musculoskeletal models can provide an accurate knowledge of the physiological loading conditions on the skeletal system during human movements and allow quantifying factors that affect musculoskeletal functions, thus it can significantly improve clinical treatments in several orthopedics and neurological contexts. Every patient is different and possesses unique anatomical, neurological, and functional characteristics that may significantly affect optimal treatment of the patient. Therefore, personalized computational models of NMS systems can facilitate prediction of patient-specific functional outcome for different treatment designs and provide useful information for clinicians. Personalize computational models can be derived by generic models or subject-specific models with different levels of subject-specific details. In this chapter, we describe NMS systems in a bottom-up fashion. First we provide a deep insight on muscle contraction dynamics and musculoskeletal system properties. Then we discuss how a musculoskeletal system is locally driven by neuromuscular controls. Afterwards, we define how central motor commands are mapped through muscle synergies into low level controls.We discuss the two visions on the motor control strategies that CNS might use to perform motor control tasks and some related aspects inspired from neurorehabilitation studies and motor control experiments. Finally, we describe the importance and application of personalized subject-specific musculoskeletal modeling in neurorehabilitation.