# A Smart Motor Rehabilitation System Based on the Internet of Things and Humanoid Robotics  
[PERSON]  
1 Department of Computer Science and Engineering, University of Bologna, 40126 Bologna, Italy; [EMAIL_ADDRESS] (A.E. ); [EMAIL_ADDRESS] (I.Z. ); [EMAIL_ADDRESS] (M.D.F.) [PERSON]  
1 Department of Computer Science and Engineering, University of Bologna, 40126 Bologna, Italy; [EMAIL_ADDRESS] (A.E. ); [EMAIL_ADDRESS] (I.Z. ); [EMAIL_ADDRESS] (M.D.F.) [PERSON]  
1 Department of Computer Science and Engineering, University of Bologna, 40126 Bologna, Italy; [EMAIL_ADDRESS] (A.E. ); [EMAIL_ADDRESS] (I.Z. ); [EMAIL_ADDRESS] (M.D.F.) [PERSON]  
2 Department of Statistical Sciences, University of Bologna, 40126 Bologna, Italy; [EMAIL_ADDRESS] (M.D.F.) [PERSON]  
3 Laboratory for Applied Ontology (LOA), ISTC-CNR, 38123 Trento, Italy; [EMAIL_ADDRESS] (S.B. ); claudio.mosol  
medical professionals [2; 3]. In parallel, the COVID-19 pandemic has underlined the need to reduce pressure on healthcare workers and highlighted the importance of building sustainable healthcare systems that can leverage emerging information technologies (IT) [4]. Researchers have identified that monitoring vital signs, such as heart rate and oxygen saturation, is essential for timely intervention and prevention [5]. Through continuous monitoring, Internet of Things (IoT) systems can deliver real-time feedback to healthcare providers and reduce the need for frequent in-person visits [6; 7; 8]. Of the few works that simultaneously collect Inertial Measurement Unit (IMU) and physiological data [9; 10; 11], none are able to handle rehabilitation sessions composed of groups of patients. Furthermore, little effort has been devoted to automating such sessions, while ensuring high patient engagement. This paper focuses on motor rehabilitation techniques for groups of patients performing moderate physical routines in controlled indoor environments, such as gyms or dedicated hospital rooms. Wearable IoT devices equipped with IMU sensors have been identified as portable and non-invasive solutions for patient monitoring, contributing to personalized healthcare management [6; 7]. Similarly, camera-based solutions enhanced by Deep Learning (DL) techniques have been successfully applied to posture detection, gait analysis, and automatic error detection during exercises [12; 13]. However, limited innovation has been brought about in the way physiotherapy sessions are delivered to patients. While telerehabilitation systems, now accessible via portable devices [14], enable home-based physiotherapy sessions and remote monitoring, they often lack the ability to personalize and adapt to the patient's individual condition. In this paper, we propose a novel concept for a smart motor rehabilitation system that leverages the convergence of IoT, Artificial Intelligence (AI), and Robotics, to improve healthcare sustainability, enable fine-grained patient monitoring and provide personalized diagnoses. We call this system I-TROPHYTS ([[https://site.unibo.it/itrophys/en](https://site.unibo.it/itrophys/en)]([https://site.unibo.it/itrophys/en](https://site.unibo.it/itrophys/en)) accessed on 1 December 2024), an acronym for _IoT and humanoid RObtics for autonomic PHYsio-Therapeutic monitoring, coaching and supervision in smart Spaces_. In our proposed scenario, patients are continuously monitored during physiotherapy sessions using wearable IoT sensors that capture both movement and physiological responses, such as heart rate and oxygen saturation already mentioned. At the same time, a humanoid robot partially takes over the role of the physiotherapist by imitating certain human behaviors. Based on the collected IoT data and domain-specific information, the robot can decide to start the next exercise in the motor routine, suggest alternative exercises, assign cool-down periods, or alert medical personnel in case of detected anomalies.