## 1 Introduction  
Approximately 0.5% of children face chronic medical complexities affecting multiple bodily systems, leading to frequent hospitalizations and significant healthcare costs [1, 2, 3]. These children and their caregivers exhibit remarkable resilience, yet their emotional well-being is often undermined by factors such as stress and disrupted social interactions [4]. Children with severe motor and communication impairments (SMCI) are particularly affected, as their limited ability to communicate can lead to social isolation and challenges in expressing their needs [5]. Children with SMCIs use gestures and vocalizations to express themselves to their familiar communication partners. Children with SMCIs often require a familiar interpreter in their daily lives who can translate. However, solely relying on a familiar interpreter to identify the emotional well-being of children with SMCIs can cause bias. Even persons familiar with a child may not be able to interpret their emotions from facial expressions [6]. Technology communication methods can be categorized based on the complexity of the systems used to support communication or emotion assessment. No-tech methods rely on unaided natural communication, such as gestures, facial expressions, and body language, requiring no external devices or tools [5]. In contrast, low-tech methods employ simple, non-electronic aids, such as communication boards, which are cost-effective and easy to use but still provide structured support for communication [5]. High-tech methods use advanced electronic systems, including speech-generating devices (SGDs) accessed through eye-gaze technology or brain signals [5]. These distinctions identify the spectrum of technologies available, from basic to sophisticated, to address the diverse needs of individuals with communication and emotional assessment challenges. The United Nations Convention on the Rights of the Child emphasized the importance of respecting every child's preferences [7]. In this context, accurately identifying and understanding the emotions of children who have communication difficulties is crucial for ensuring that their preferences are respected and effectively met, especially in healthcare settings. Emotional responses can be difficult to assess due to their complexity and humans' natural ability to hide emotion. The current research using psychophysiological signals focuses on the emotional assessment of typically developed adult participants [8; 9; 10; 11; 12]. Psychologists often classify emotions into six discrete categories: happiness, sadness, fear, anger, surprise, and disgust [13]. Psychologists also use the theory of emotion to describe emotions with three dimensions that include pleasure, arousal, and dominance (PAD) [13]. Each dimension is scored on a continuous scale used to describe the emotion: pleasure, sometimes referred to as valence, describes how a feeling is positive or happy; arousal describes how actively one engages with an emotion; and dominance describes whether the environment influences an individual or vice versa (i.e., is the individual controlling the situation or is it controlling the individual). Once a stimulus is presented to an individual in a research setting, the participants respond to the stimulus with their pleasure, arousal, and dominance scores. Each value of the PAD can then be plotted on a set of axes that represent pleasure, arousal, and dominance. The responses to a specific stimulus from a number of participants allows for the creation of a three-dimensional graph with the mean at the center of the sphere, and the standard deviation defining the radius [14]. Based on the three-dimensional location of these spheres, an emotion can theoretically be identified [15]. The current standard for self-reporting emotions is the Self-Assessment Manikin (SAM) method [12; 13].