Emerging Therapies in Neurorehabilitation II

Great progress has been achieved in the last few years in Neurorehabilitation and Neural Engineering. Thanks to the parallel development of medical research, the chances to survive a neural injury are growing, so it is necessary to develop technologies that can be used both for rehabilitation and to improve daily activities and social life. New robotic and prosthetic devices and technologies such as Functional Electrical Stimulation, Brain-Computer Interfaces and Virtual Reality are slowly becoming part of clinical rehabilitation setting, but they are far from being part of everyday life for the patients. As technology improves, expectations keep rising and new problems emerge: from cost reduction to the diffusion in the medical environment, from the enlargement of the number of patients who may benefit from these technologies to transferring rehabilitation to the patient’s home. All these requests lead to great challenges that researchers have to face to enhance their contribution towards the improvement of rehabilitation and life conditions of patients with neural impairment.

Neurorehabilitation plays a crucial role in the multidisciplinary management of brain injury patients. Emergent therapies based on rehabilitation technologies such as robots, bci, FES, and virtual reality could facilitate cognitive and sensorimotor recovery by supporting and motivating patients to practice-specific tasks on high repetitive levels during different stages of rehabilitation. Robots have become a promising task-oriented tool intended to restore upper limb function and a more normal gait pattern. Virtual reality environments by providing powerful sensorimotor feedback and increasing user interaction with a virtual scenario could improve gait, balance, and upper limb motor function. This chapter will provide an overview on the rationale of introducing rehabilitation technologies-based therapies into clinical settings and discuss their evidence for effectiveness, safety, and value for stroke and traumatic brain injury patients. In addition, recommendations for goal setting and practice of training based on disease-related symptoms and functional impairment are summarized together with reliable functional assessments.

Spinal cord injury (SCI) results in a temporary or permanent impairment in the spinal cord’s normal motor, sensory, or autonomic function below the level of the lesion causing significant functional impairments in individuals. Restoration of gait is one of the major rehabilitation goals for SCI patients, along with recovery of upper limb control and other functions. When treating an individual with SCI, the ultimate objective is complete reparation of the functional damage, which is presently not yet possible. However, both human and animal studies in neuroplasticity have shown that the spinal cord has some potential to reorganize despite the loss of supraspinal input and utilize the remaining peripheral input to control stepping and standing. Therefore, optimally leveraging the interaction of neuroplasticity with technological devices to restore functionality in these individuals is the main focus of current research efforts in neurorehabilitation. In this chapter, we briefly review the clinical aspects of SCI and present a summary of the present and future approaches for rehabilitation of SCI patients and discuss how these techniques may restore function and potentially promote recovery in these patients.

Cerebral palsy (CP) is the most common motor disorder of childhood. It is characterized by abnormal muscle tone and is caused by a nonprogressive injury to the developing brain. The hallmark of abnormal posture and movement occurs as the child develops fundamental motor skills. Thus, it is critical to make opportunities for infants and young children to interact with the environment. It is recognized that assistive technology can improve the functional capabilities limited by CP. In this chapter we will explore four distinct current innovative strategies that promote rehabilitation functional outcomes. The first two will focus on the output side of treatment that of robotic control systems with virtual reality to increased practice performance in locomotion and activity of daily living. The second contribution describes the state of the art of wearable sensors providing feedback for improving motor performance including communication. The third will focus on noninvasive brain stimulation for CP rehabilitation. The next contribution provides analogues strategies used with stroke research that may be translated to children. Finally, we summarize the assistive devices for rehabilitation of people with CP from a parents perspective describing the challenges achieved and the future work required.

Human NeuroMusculoSkeletal systems (NMS SYs) 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 behaviors 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.

Over the past several decades, it has been shown that the spinal cord exhibits significant adaptive plasticity during development and throughout life. This is normally a positive phenomenon, allowing the spinal cord to develop fundamental functions and learn novel behaviours. However, after a spinal cord injury, the pathways controlling the behaviours mediated by the spinal cord are interrupted and maladaptive plasticity can take place. The traditional approach to rehabilitation after spinal cord injury is to apply physical training exercises improving the overall condition and functioning of the patient, and thus to indirectly promote neural recovery. Emerging neuromodulation therapies that complement physical therapy have been proposed to directly stimulate and modify specific impaired neural pathways and thereby produce a more satisfactory functional state. This chapter presents an overview of these new treatment approaches.

Brain-computer interface (BCI) systems are novel and emerging technologies that allow a person to interact with the environment without any muscular activity using only his or her brain. Currently, there are various applications of neurorehabilitation, which have emerged from this technology. These are based mainly on the performance of motor imagery tasks and visualization of movement, which encourage a process of neuroplasticity. Virtual reality (VR) is an innovative approach that is used in numerous neurorehabilitation applications. Several studies have combined BCIs and VR to develop applications, which allow a person to navigate in virtual environments or to play video games, among others. Some studies have been focused on neurorehabilitation applications, such as applications that allow a person to control virtual limbs. However, nowadays neurorehabilitation has become essential to our society, and this resulted in a substantial increase in BCI research directed toward this field. This chapter will introduce the current state of the art in BCI systems developed for neurorehabiliation applications, among which are innovative studies that make use of VR.

Robot-assisted rehabilitation therapy interventions are emerging as a new technique to help individuals with motor impairment recover lost motor control. While initial clinical studies indicate the devices can reduce impairment, the mechanisms of recovery behind their effectiveness are not well understood. Thus, there is still uncertainty on how best to design robotic therapy devices. Ideally at the onset of designing a robotic therapy device, the designer would fully understand the physiological mechanisms of recovery, then shape the machine design to target those mechanisms. This chapter reviews key potential mechanisms by which robotic therapy devices may promote motor recovery. We discuss the evidence for each mechanism, how initial devices have targeted these mechanisms, and the implications of this evidence for optimal design of robotic therapy machines.

Patients who have suffered impairment of their neuromotor abilities due to a disease or accident have to relearn to control their bodies. For example, after stroke the ability to coordinate the movements of the upper limb in order to reach and grasp an object could be severely damaged. Or in the case of amputees, the functional ability is completely lost.

Understanding how the CNS copes with the redundancy of the musculoskeletal system is a central aim in motor neuroscience and has important implications in the clinical scenario. A long-standing idea hypothesis is that motor control may be simplified by a modular organization, in which several a few muscle synergies are used to organize muscles in functional groups. In this chapter, we present the theory hypothesis of muscle synergies under from a simplified point of view and we describe its practical implications in the context of neurological pathologies. This chapter wants to be an intuitive and practical guide to those practitioners, new to the concept of muscle synergies, willing to understand how to perform such an analysis in typical clinical settings.

This chapter aims to give a general description of basic concepts related to transcutaneous FES. It offers examples of simple exercises to introduce the reader into the practical aspects of the application of transcutaneous FES. Different influencing aspects such as stimulation waveform, stimulation parameters, electrode type, placement, and size are analyzed. Available models related to FES that represent the electrical properties of the skin, current distribution on the skin, or either nerve excitability are presented as well, highlighting those factors that affect most transcutaneous FES applications. A practical guide on upper and lower limb is also presented, where different exercises are proposed to experience previously described theoretical aspects in practical application of FES. Finally, conclusions of the chapter and challenges observed during the exercises are described and novel techniques and technology used to overcome some of these challenges are mentioned.

This chapter addresses the current state of the art of virtual rehabilitation by summarizing recent research results that focus on the assessment and remediation of motor impairments using virtual rehabilitation technology. Moreover, strengths and weaknesses of the virtual rehabilitation approach and its technical and clinical implications will be discussed. This overview is an update and extension of a previous virtual rehabilitation chapter with a similar focus. Despite tremendous advancements in virtual reality hardware in the past few years, clinical evidence for the efficacy of virtual rehabilitation methods is still sparse. All recent meta-analyses agree that the potential of virtual reality systems for motor rehabilitation in stroke and traumatic brain injury populations is evident, but that larger clinical trials are needed that address the contribution of individual aspects of virtual rehabilitation systems on different patient populations in acute and chronic stages of neurorehabilitation.