## 4 Discussion  
### Principal Findings  
In summary, we observe that the integration of AI and HCI in OT practices has expanded significantly in recent years, addressing the diverse needs of people across multiple domains. The reviewed studies have been categorized into four major areas: upper-limb motor function after stroke, ASD and developmental conditions, elderly support and AL, and emotional expression with virtual companionship. Across these domains, various technologies have been employed, evolving with advancements in AI-driven approaches and interactive systems. Figure 5 illustrates the comparative distribution of studies across four main application domains over the examined years. The main patterns highlighted in Figure 5 refer to both the proportional distribution of research across domains and the temporal evolution of studied areas, emphasizing the dynamic progression of AI and HCI integration within OT. Furthermore, by paying careful attention, the reader can observe that research related to ASD and developmental conditions has maintained a consistent presence between 2015 and 2022, indicating sustained scientific interest in these areas. In contrast, studies focusing on elderly support and AL show a pronounced increase from 2021 onwards, reflecting the growing societal need to address challenges associated with aging populations. In addition, emotional expression and virtual companionship appear to be more recent research focuses, with most studies published between 2024 and 2025 suggesting an emerging recognition of technology's role in supporting emotional well-being. Research on motor function rehabilitation after stroke appears more sporadically distributed, with studies emerging in 2014, 2017, 2023, and 2024 indicating ongoing but less concentrated efforts in this area. In the domain of upper-limb motor function rehabilitation, earlier studies primarily utilized VR and traditional motion-tracking techniques for assessment and training, e.g., Kinect-based sensory data. Yet, more recent works have incorporated DT, serious-game VR, and AI-driven motion analysis, like CNNs, to improve stroke rehabilitation strategies. The trend suggests an increasing reliance on robotics solutions, like exoskeletons  
Figure 5: The distribution of the collected 26 studies across the 4 application domains and the corresponding years. The proportional distribution of both research across domains and the temporal evolution of studied areas are illustrated. and interactive AI models, for real-time patient adaptation and feedback, highlighting a shift towards more adaptive and personalized physical therapy methods [31; 32]. For individuals with ASD and other developmental conditions, socially assistive robotics and serious-game applications have been consistently utilized, with an increasing emphasis on AI-driven engagement detection. Early studies focused on tangible interfaces and game-based interventions, whereas more recent research integrates DL techniques, such as CNNs and RL, to optimize engagement levels [37]. Furthermore, AI-driven emotion recognition and adaptive interaction models have gained prominence, demonstrating a move towards personalized therapy experiences that cater to individual behavioral responses [39]. The domain of elderly support and AL has seen an evolution from rule-based smart home automation towards more sophisticated AI-driven robotic assistance and multimodal activity recognition. Earlier works emphasized decision trees and basic sensor-based automation, while recent studies have also incorporated cutting-edge DL models and real-world participatory design approaches. The trend indicates a growing preference for AI-augmented humanoid robots and assistive robotic arms aiming to enhance ADL recognition, grasping, and manipulation tasks for elderly individuals [51]. Subsequently, in the field of emotional expression and virtual companionship, there is a notable transition from traditional chatbot-based interventions towards more immersive VR and AI-driven emotion recognition systems.