## 3 Results
### Role of IoT Sensors in Rehabilitation  
Rehabilitation science has significantly evolved since healthcare professionals used a stopwatch to measure a patient's walking time and a plastic goniometer to assess joint angles [17]. The demand from therapists for higher training intensity and more sensitive feedback led to the emergence of small, affordable sensors embedded in splints, shoes, and even coffee cups. Today, their impact is so profound that modern motor rehabilitation programs increasingly integrate sensor-based systems, as shown in the analysis presented in Table 2. These sensors quantitatively assess physiological parameters, process data in real-time, and instantly convert it into mechanical or visual feedback that helps restore mobility. \begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline
**Platform/Source** & **Architecture** & **Key Technologies** & **Purpose** & **Personalization (Qualitative)** & **Evidence Strength** & **Clinical** & **Cost-** & **References** \\ \hline REHOME & IoT + local interfaces & sensors, cognitive games, & comprehensive and motor telegrams, & patient data use: & Pilot studies, & Advanced; multi-domain & Asírings via \\  & & & cognitive and motor telegrams, & & 100\%, & SUS \textgreater{}68 & remote rehab in & reduced hospital & [14] \\  & & & & polarization & potential data use: & & hospitals & use \\ ReMoVES & IoM + remote & telemedicine, IoT & rehabilition for multiple sclerosis & & 100\%, & Feasibility study, & Rehab for MS; positive user & & Potential savings \\  & & & & adsorption: & \(n\) = 2 & positive user & from remote & \\ I-TROPHYS & IoT + humanoid robotics & wearable IoT, sensors, AI, robotics & autonomous monitoring and physiotherapy & & patient data use: & & Partial; home & Scalable; one \\  & & & & monitoring and & 100\% & Small trial, \(n\) = 6; & rehab via AI + therapists for & [12] \\
3D-printing + AI & computer-aided design (CAD) + & AI optimization, bioscanning & vision & patient data use: & & & \\  & & & prosthetics and & 100\%, & Conceptual; no & Limited; wrist & Possible savings & \\  & & & & orthotics & operationalized & & rehab prototype & via 3D-printing \\ AI + CT & cloud-based & ResNet50, segmentation, AI & diagnostics/ & 100\%, & No data available & No data & No data \\  & & & AI & monitoring & & real-time & & available & \\  & & & & data tracking, & patient data use: & & & \\ Pheno4U & cloud-based + & integration with & remote & patient data use: & & & \\ Platform & Mobile App & hospital & remote & clinical study, & with & autonomy; & \\  & & & & rehabilitation & & & \\  & & & system (HIS) & & & & \\ Haofof & & & patient data use: & & & & \\ (ind./comm. model) & online service & multilevel & virtual & 100\%, & & & \\  & & & & adaptation: & & & available & \\  & & & & continuous & & & \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Comparative overview of medical rehabilitation platforms using AI, IoT, and Robotics. Electrocardiography (ECG) remains the gold standard for assessing the heart's electrical activity. Whether using classical Ag/AgCl wet electrodes or modern dry-textile variants, these sensors deliver millivolt precision, enabling the robust calculation of the heart rate and heart-rate variability--metrics indispensable for calibrating exercise intensity in cardiac rehabilitation [18]. Advanced systems now incorporate edge computing to perform initial signal processing--thus reducing the transmission latency and power consumption--and support personalized adaptive protocols in environments such as home-based telerehabilitation [19]. While ECG excels at beat-to-beat accuracy, photoplethysmography (PPG) extends monitoring to everyday contexts. Cost-effectively integrated into smartwatches and rings, PPG sensors track peripheral blood volume changes to provide continuous heart rate and SpO\({}_{2}\) readouts.