Читать книгу Intelligent Systems for Rehabilitation Engineering - Группа авторов - Страница 13

Several researchers have contributed [1] to robotics applications in surgery, rehabilitation [2, 3], neurological disorders [4], prosthetics/exoskeleton [5, 6], assistance [7], etc. The usefulness and development of rehabilitation robotics have been sufficiently emphasized in literature [8, 9]. The guidelines issued by the European Commission for robotics in healthcare were examined, and areas in rehabilitation robotics where the development is required are highlighted in [10]. The optimal approach for the iterative learning control for the robotic systems was described with its application in [11]. The research done in the field of exoskeleton robotic system was overviewed, and its applications were provided [12]. A novel method was presented for the development of a device for patients who suffered from sprained ankles and was able to track the activity of ankle [13]. The design, control, and application of Gentle/G system were presented for the patients who were recovering from brain injury [14]. The control algorithms and use of AI were overviewed, and ongoing trends, issues, and future trends were discussed in [15]. The overview of the therapeutic robotic systems and its applications areas have been explored earlier [16]. A robotic workstation was constructed using a manipulator and was tested on spinal cord injury patients [17]. For the neuroprosthetics of spinal cord injury patients, an effective FES system was developed [18].

A robotic ontology, called RehabRobo-Onto, was developed that displayed the information of rehabilitation. A software RehabRobo-Query for facilitating the ontology was presented [19]. fMRI compatible rehabilitation robotic glove was introduced for hand therapy and was equipped with a pneumatic actuator that generated motion [20]. RehabRobo-Onto, which was robotic ontology, was equipped with a method that answered natural language queries [21]. The estimation of force between joint position and joint actuation was done using an extended state observer (ESO) [22]. The process of recovery of upper limbs stroke patients was reviewed [23]. With the help of Virtual Gait Rehabilitation Robotics (ViGRR), a new concept of rehabilitation was introduced that did not require any therapist [24]. The properties of the exoskeleton robotic system were studied, and predictions regarding their benefit in coordination movements were done [25]. A design of the exoskeleton robotic system was proposed for the knee orthosis of poliomyelitis patients [26]. The previous reviews of such works can be found in [27, 28]. Work has also been conducted on the development of FCE using machine learning for rehabilitation robotics [29]. The applications of disturbance observer for rehabilitation and the challenges faced by them are presented in [30].

In this chapter, a thorough review of the various applications of robotics in rehabilitation has been conducted. The applications of robotics in neurology, cognitive science, stroke, biomechanical, machine interface, assistive, motion detection, limb injury, etc. are considered in this chapter. The chapter is organized as follows. Section 1.2 gives an overview of robotics for medical applications. Section 1.3 presents the relevant discussion and future scope in this direction. Finally, the chapter is concluded in Section 1.4.