# A Smart Motor Rehabilitation System Based on the Internet of Things and Humanoid Robotics
## 3 The I-TROPHYTS Framework  
### System Model  
Here, we consider the system depicted in Figure 1, which involves four primary actors: patients, a humanoid robot, a medical supervisor, and a pervasive IoT sensing and computing platform. Patients face high metabolic, cardio-respiratory and infectious risks, which makes them suitable for physical activities focused on balance, stretching, and posture. These activities are performed in dedicated indoor environments, such as gym spaces or rehabilitation rooms. In this paper, we will not delve further into the medical implications and motivations behind our work; interested readers can refer to [2; 3] for examples of studies exploring the connection between reduced metabolic risk and the benefits of physical activity. Unlike traditional scenarios, where patients follow exercises guided by human physiotherapists, the role of the physiotherapist is taken by a humanoid robot that provides motor routines. The IoT sensing and computing platform enables monitoring of each patient's physiological and motor performance. Each patient is equipped with multiple wearable IoT devices, including IMU sensors that track the position of specific body parts. Additionally, patients wear at least one IoT device to monitor vital signs, such as heart rate and blood pressure. All collected data are transmitted from these devices to an Edge Server (ES), where sensor data from physiotherapy sessions is stored, aggregated and processed. Based on the current detected states of the patients, the robot can decide to continue the therapy plan by executing the next exercise in the sequence, assigning cool-down periods, or performing alternative exercises. It can also alert the human supervisor when necessary. The supervisor is responsible for programming the robot's motor routines,  
\begin{table}
\begin{tabular}{c c c c c c} \hline \multirow{2}{*}{**Paper**} & \multirow{2}{*}{**IMU Sensors**} & \multirow{2}{*}{**Vital Signs**} & \multicolumn{2}{c}{**ML**} & \multicolumn{2}{c}{**Edge**} & **Humanoid** \\  & & & & Techniques & Processing & Robot \\ \hline
[6] & ✓ & ✗ & ✓ & ✗ & ✗ \\
[7] & ✓ & ✗ & ✓ & ✓ & ✗ \\
[9] & ✓ & ✗ & ✗ & ✗ & ✗ \\
[8] & ✓ & ✗ & ✗ & ✗ & ✗ \\
[19] & ✓ & ✗ & ✗ & ✗ & ✗ \\
[10] & ✗ & ✗ & ✗ & ✗ & ✓ \\
[20] & ✓ & ✗ & ✗ & ✗ & ✓ \\
[11] & ✓ & ✗ & ✓ & ✓ & ✓ \\ \hline
**I-TROPHYTS** & ✓ & ✓ & ✓ & ✓ & ✓ \\ \hline \end{tabular}
\end{table}
Table 1: Comparison of I-TROPHYTS with related work.  
and can access all IoT data generated during the sessions for personalized diagnostics. We highlight some unique advantages of our approach compared to both traditional and smart rehabilitation solutions, as detailed in Section 2.  
1. _Scalability_. Our system can serve multiple patients simultaneously and can be easily replicated across different environments or rooms.
2. _Privacy_. Our system was intentionally designed to avoid the use of camera-based solutions for monitoring patients during sessions, focusing instead on wearable IMU-based sensors. Although numerous studies have demonstrated the accuracy of computer vision technologies for posture tracking [21; 22], significant challenges remain, especially regarding the privacy of the recorded individuals, an issue that cannot be overlooked in medical environments.
3. _High Patient Engagement_. The presence of a humanoid robot increases patient engagement, thanks to the empathy induced by somatic similarity recognition, as discussed in [17; 18; 23].
4. _Fine-Grained Personalization_. Our approach enables continuous monitoring of each patient's motor and vital states, allowing long-term data collection to generate personalized clinical reports.  
At the same time, we recognize that our solution is not targeted at a fully automated, AI-driven medical scenario, which could raise concerns about fully delegating decision-making responsibility to AI systems [24; 25]. Instead, the human supervisor retains the ability to intervene in cases of alarms from the IoT system, or any malfunctions, ensuring a balance between automation and human supervision.