Telehealth rehabilitation had its roots in the 1960s, when some hospitals and university medical centers started experimenting with telemedicine to reach patients in remote areas. However, it was not until the advent of the internet and advancements in telecommunications technology in the 1990s that telehealth began to take form. Telehealth has been gaining momentum over the past two decades, and its application in rehabilitation is diverse. One notable example is the development of the InMotion ARM, a telehealth robotic system that allows for remote physical therapy for stroke patients [7].

Furthermore, robotic assistance in telerehabilitation has proven to be a groundbreaking advancement; [8] presented an extensive study on how robots have been instrumental in rehabilitating patients with neuromuscular disorders. This work especially delves into upper and lower limb exercises, stressing the role of robots in aiding patients in performing high-intensity repetitive tasks, which is crucial for neuroplasticity. The authors showed how robots can objectively measure patients’ movements and improvements.

Jin et al. [9] have demonstrated the efficacy of deep reinforcement learning (DRL) in improving post-stroke limb function, whereas Majhi and Kashyap [10] have explored adaptive algorithms for patient-specific therapy adjustments. Furthermore, the work by Wang et al. [11] has been instrumental in showcasing how DRL can optimize engagement levels during robotic-assisted therapy. These studies underscore the potential of DRL to enhance the adaptability and personalization of rehabilitation protocols according to motor rehabilitation.

Another instance is Teleswallowing Rehabilitation, which assists in the remote assessment and management of dysphagia in elderly patients [12,13]. These examples scratch the surface of what has been accomplished in telehealth rehabilitation, where systems have been developed for various types of physical impairments, speech therapy, and more. Robotics has been a key component in advancing rehabilitation methods. For example, the Lokomat, developed by Hocoma, is a robotic gait therapy device widely used in rehabilitating individuals with spinal cord injuries and stroke [14]. Another example is the ArmeoPower, a robotic exoskeleton for arm and arm rehabilitation, also for patients with stroke or spinal cord injuries [15,16,17].

Telehealth rehabilitation has also been influential in managing chronic pain, as discussed by [18,19,20]. Their work focuses on internet-delivered treatment for chronic pain management. It also delves into how integrating psychological approaches into telehealth platforms has helped in better pain management. Moreover, telerehabilitation is increasingly seen as a viable method for managing cardiovascular diseases. In a study by [21,22,23,24,25], a home-based telerehabilitation program was studied for patients with heart failure. The study elucidated how telerehabilitation could effectively enhance the exercise capacity and quality of life of patients with chronic heart diseases. An interesting approach is also observed in a research work by [26,27], where the authors developed a tele-treatment program for patients with chronic obstructive pulmonary disease (COPD). They designed a service platform that includes exercise, education, and counselling, supported by a triage function. Godine et al. in [28] addressed the novel approaches in telehealth for behavioral management in individuals with neurological conditions. They discussed various telerehabilitation interventions, such as cognitive behavioral therapy, motivational interviewing, and mindfulness-based stress reduction, that can be leveraged to manage symptoms and enhance the quality of life. Moreover, integration with electronic health records (EHRs) has emerged as an essential feature in telehealth rehabilitation. According to [29], EHR integration enables efficient information sharing, leading to better coordination in care processes.

Interactive online platforms have enabled the remote delivery of physical therapy. Johnson et al. in [30] explored an online platform, PhysiTrack, which allowed physical therapists to design personalized exercise programs. Patients from their homes could access these. The study demonstrated that patients using PhysiTrack showed better exercise adherence and reported higher satisfaction levels than in traditional physical therapy. Robotics is another domain that has greatly advanced telehealth rehabilitation. In a study [31] by Radder et al., telerehabilitation robotics were shown to be effective in providing intensive task-specific training, especially for stroke patients. The study highlighted that robotic devices could deliver repetitive training tasks, which are often required for neuromuscular rehabilitation. A study [32] by Patel et al. showcased the use of kinematic sensors and smart textiles to remotely monitor patients’ movements during physical therapy. These real-time data were critical for providing feedback to both the patient and the therapist, allowing for more targeted and effective therapy. Virtual reality (VR) has been another significant advancement. Laver et al.’s study [33] showed that VR could be effectively employed in telerehabilitation settings, particularly for stroke rehabilitation. Patients using VR systems showed improved physical activity compared to those who underwent conventional therapy.

DRL has been employed in various healthcare applications. For example, Peng et al. [34], utilized DRL for dose optimization in radiation therapy. Another application of DRL is in optimizing treatment plans for patients with chronic conditions such as diabetes, where Prasad et al. [35] used DRL to create personalized insulin plans. One recent development is using artificial intelligence (AI) in telerehabilitation. Wade et al. [36] highlighted AI’s role in enhancing telerehabilitation outcomes. By incorporating AI algorithms, it is possible to analyze patients’ data to create personalized rehabilitation plans that can dynamically change as per their progress. Table 1 describes different published research work with respective technologies and advantages and disadvantages.

Research Paper	Technology Used	Advantages	Disadvantages
[1]	Telehealth robotic system	Allows for remote physical therapy. Enhances motor recovery in stroke patients.	Limited to upper extremities. High cost.
[5]	Telehealth swallowing assessment tool	Facilitates remote assessment. Reduces the need for patient travel.	Requires a reliable internet connection. May not be suitable for severe cases.
[6]	Robotic gait therapy	Provides intensive gait rehabilitation. Adjustable to individual needs.	Expensive. Requires trained personnel for operation.
[7]	Robotic exoskeleton	Facilitates arm rehabilitation. Adaptable to individual progress.	High cost. Limited availability.
[16]	Deep reinforcement learning for dose optimization	Personalized treatment plans. Potential to minimize radiation exposure.	Computationally intensive. Requires extensive data for training.
[17]	Deep reinforcement learning for insulin optimization	Personalized insulin plans. Potential to improve long-term health outcomes.	Reliant on continuous data input. Potential issues with data privacy.
[This Study]	Telepresence robot with mechanical arm	Enables full-body rehabilitation. Cost-effective compared to similar systems.	Requires calibration for individual patient use. Operational training needed for healthcare staff.