## 1 Introduction  
Stroke or other acquired brain injuries often lead to significant physical impairments, including hemiplegia, motor disorders, cognitive decline, and language impairments [1]. Among these, gait impairments caused by spinal or brain injuries particularly impact a patient's independence and quality of life but also predispose the patient to secondary medical complications, such as pressure sores, cardiovascular disorders, and musculoskeletal diseases [2; 3]. These complications are often exacerbated by a decline in the function of various organs due to reduced motor activity. In this context, regular rehabilitation training becomes a critical component of the care plan, aimed at minimizing these risks [3; 4; 5]. Traditional rehabilitation therapies, primarily focused on restoring walking functions, involve manual gait training by physical therapists or the use of exercise equipment to enhance lower limb muscle strength, endurance, and joint range of motion (ROM). However, these methods often heavily rely on the experience of therapists, which can lead to variability in treatment effectiveness [6]. To overcome these limitations, various lower limb robot-assisted gait training systems and exoskeleton robots have been developed over the past several decades, and their effectiveness has been verified in numerous clinical studies [7; 8; 9; 10; 11]. This progress has extended the role of physical therapists beyond providing physical assistance to also performing a supervisory role, thereby contributing to the efficiency of wearable robot-assisted gait training [7; 10]. In the previous study, there was an increasing emphasis on overground gait training in real-world environments. Such training not only facilitates active participation and interaction with the environment but also enhances trunk balance, control, and visuo-spatialawareness. However, it is not advisable to use full lower-limb exoskeletons for overground gait training in patients who retain some functional abilities, such as those with hemiplegia [1]. In line with this, recent research has explored the use of lightweight lower limb exoskeletons, which assist specific joints and reflect the wearer's gait intention [1; 12; 13; 14; 15]. These exoskeletons are not only cost-effective and easy to wear but also enable training in real-world environments without spatial constraints. Hemiplegic gait after stroke is characterized by unilateral muscle weakness, spasticity, and insufficient forward propulsion, resulting in an asymmetric walking pattern. Key issues include limitations in hip, knee, and ankle movements during the swing phase, causing undesirable compensatory movements, like hip hiking and circumduction. In the stance phase, notably, knee hyperextension is observed in about 40-68% of stroke patients, significantly affecting gait speed and symmetry, and increasing the metabolic cost of walking [1; 16; 17]. Addressing these abnormal gaits requires innovative solutions like the knee-actuated exoskeletal gait orthosis (KAEGO), which assists knee joint flexion and extension based on the patient's gait intentions [16; 18; 19; 20; 21]. To develop such control strategies, accurate detection of the user's gait phase and recognition of gait intentions are essential. This has led to the use of various sensors, including electroencephalographic (EEG) [22], electromyographic (EMG), pressure, torque, angle sensors, and inertial measurement units (IMUs) [23]. Among these, ground reaction force (GRF) sensors have been widely used for gait phase detection [24; 25; 26; 19; 27]. In a previous study of this research topic, a GRF sensor using load cells was developed and successfully implemented in the bilateral KAEGO for a patient with an incomplete spinal cord injury (SCI) [24]. However, the placement of the sensors in the foot makes the sensors susceptible to damage due to continuous impacts [28].