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Inputs resembling "words about animals" or "countries" are such examples. Uncontrolled setups from 5 completely different people are used to guage the methods for finetuning on individual dataset. One participant stated that utilizing the robotic at house would be their "number one" use case for the technology (S10), and others highlighted the potential for robotic exercise coaches to improve telemedicine for individuals who live far away from clinics (S04) or have difficulty leaving their homes (S01). Several individuals noted the system’s potential to assist individuals with mobility issues (S02) and sedentary lifestyles (S04). Example of integrating the robotic into a clinical setting embrace using the robot for affected person warm-ups (S08) and being "more efficient with the clinic time" (S04). Also, utilizing a robotic to guide PT exercises creates a chance to collect and observe rich, lengthy-time period health knowledge inside and out of doors of the clinic, which will be used by ES to enhance treatment plans. The upper inter-class separability of information samples in UI-PRMD in comparison with REHAB24-6 reduces classification complexity, making it more appropriate for conventional deep-learning fashions. Tools like Technology Acceptance Models (TAMs) (venkatesh2000theoretical,