## 1 Introduction  
According to estimates, 2.4 billion people worldwide are in need of rehabilitation, but in some low- and middle-income countries, more than 50% of them lack access to necessary services. This gap is particularly exacerbated by emergencies such as wars and natural disasters [1]. Currently, over 800 million people suffer from chronic diseases, and a significant portion do not have ready access to medical centers, which complicates their recovery [2]. There is a clear need to build effective medical rehabilitation systems. An integrated framework is highly pertinent, especially for post-hospital discharge care when patients often feel uncertain about their home rehabilitation regimen. Conventional approaches to rehabilitation are typically resource-intensive, making them difficult to implement on a large scale [3]. Digital technologies, in this regard, offer solutions that can make treatments more flexible and accessible. Medical rehabilitation systems that allow remote interactions between doctors, devices, and patients are paramount for post-hospital discharge care, especially when physical contact is restricted. The challenges facing medical rehabilitation organizations today highlight the need for further the optimization and enhancement of current approaches. A recent systematic review [4] emphasizes the growing interest in combining robot-assisted technologies with electrical stimulation for lower extremity rehabilitation in stroke patients, highlighting not only the potential functional improvements but also the current limitations in comparability due to heterogeneous outcome measures and intervention protocols. Furthermore, a study in the East Kazakhstan region revealed that both caregivers and patients face significant challenges in home care, including insufficient training in rehabilitation procedures and limited resources [5]. Digital technologies can help therapists remotely monitor patient performance, provide advice, and adjust treatment plans [3]. Patient engagement is crucial, as low motivation, fatigue, and a lack of clear instructions can reduce the adherence to rehabilitation programs [4]. The nuanced nature of the recovery process, especially during self-rehabilitation at home, often presents difficulties. Implementing medical rehabilitation systems that integrate wearable sensors and AI can overcome these gaps by personalizing care, improving monitoring, increasing patient participation, and reducing the burden on healthcare facilities [3]. The use of AI and machine learning to analyze patient movements, assess exercise accuracy, and detect problems makes rehabilitation more precise and effective, which is particularly important during post-surgical rehabilitation [6]. In this regard, telerehabilitation allows healthcare professionals to actively monitor the recovery process, while patients can observe their own progress, thereby increasing motivation and awareness [2]. A crucial aspect is continuous monitoring through wearable sensors, such as IMUs, which track patient movements and physiological parameters at home and transmit this data for analysis. This process enables healthcare providers to promptly adjust rehabilitation plans based on the patient's real-time condition. Such adaptability significantly increases the efficiency of the recovery process by personalizing treatment based on data from wearable devices [2; 7]. In the field of assistive devices, for example, the development and testing of a personalized ankle exoskeleton demonstrated the effectiveness of individualized rehabilitation technologies [8]. Currently, gamified rehabilitation is gaining popularity, as it allows patients to perform exercises in a serious game format using webcams and deep learning algorithms to track movements, eliminating the need for specialized equipment [3]. The studies show that wearable devices, mobile applications, telerehabilitation platforms, virtual reality, and exergaming contribute to maintaining physical activity and improving the quality of life [9].