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.
1.2 An Overview of Robotics for Medical Applications
1.2.1 Neurological and Cognitive
Behavioral approaches have been proved effective in many cases for the treatment of patients with different injuries. A multidisciplinary behavioral approach was made for patients who had movement issues [31]. Neurological disorders have been faced by many patients due to some or other reasons. In [32], a pneumatic muscle actuated orthosis system was developed, and in [33], VR technologies were used with rehabilitation robotics for curing of neurologically disordered patients. The overview of the tools used for the rehabilitation of patients with weak limbs due to neurological disorders was presented [34].
1.2.2 Stroke Patients
Stroke is a medical emergency that needs immediate treatment. A large number of cases around the world are witnessed every year. For disabled stroke patients, the key approaches used for treatment using MANUS robotic system were presented in [35]. A novel algorithm was developed based on performance-based-progressive theory for rehabilitation, and an algorithm was developed for triggering the recovery of stroke patients [36]. The approaches made in human-centered robotic systems were presented and consisted of patient-cooperative abilities that did not impose any predefined movement on stroke patients [37]. ARKOD device for knee rehabilitation was presented, which had damping closed-loop control and an electro-rheological fluid for effective flexion of knee movement [38]. Virtual Gait Rehabilitation Robot (ViGRR) for providing gait motion, training, and motivation to the stroke patients was designed and prototyped [39]. The wearable inflatable robot was designed for stroke patients and showed less cardiac activity for the therapist [40]. Table 1.1 enlists some of the published work with the proposed solution(s) for the stroke patients employing rehabilitation robotics.
Table 1.1 Summary of certain articles related to the use of robotics for stroke patients.
| Ref. number | Area of rehabilitation robotics explored | Remarks |
| [35] | MANUS robotic systems | Different approaches used for treating disabled people and the main areas where MANUS system had significant effects were presented. |
| [36] | Assistance using a performance-based-progressive theory | A novel method for assistance was developed for stroke patients, and the assistance was based on speed, time, or EMG limits. |
| [37] | Human-centered robotic systems | The system was applied for the rehabilitation of the impaired stroke patients, and patient-cooperative system, which produced actions based on the actions of the patient, was presented. |
| [38] | Knee rehabilitation device AKROD | A device was designed particularly for stroke patients and consisted of damped closed-loop control and electro-rheological fluid. |
| [39] | Haptic-based rehabilitation robot | Virtual Gait Rehabilitation Robot (ViGRR) was designed for stroke patients, and its prototype was also presented. It provided gait motion, training, and motivation. |
| [40] | Inflatable wearable robot | The device was tested on stroke patients and showed less cardiac and muscular activity by the therapist. |
1.2.3 Biomechanical or Mechatronic Robotic Systems
A systems approach, mechatronics, mobility sensors, cost/benefit ratio, and softness were discussed for rehabilitation robotics [41]. An exoskeleton robot WOTAS was introduced and was loaded with control strategies that were based on biomechanical loading [42]. The analysis and applications of MEMS technology were tested by applying it to exoskeleton-based bio-mechatronic robotic systems [43]. Based on EMG signals, the torque produced by the muscles was determined using a biomechanical model, and it was predicted whether the proposed model was feasible or not [44]. An ankle rehabilitation robotic device was built, and its mechanical performance was tested [45].
1.2.4 Human–Machine Interfacing
Human–machine integration includes the tactics incorporated for better communication between machines and humans. The structure and implementation of CURL language, MUSIIC, RoboGlyph, and multitasking operator robotic system were presented [46]. The architecture of ARCHIN was produced whose task was to integrate machines with humans, and its performance was evaluated
