Promoting Rehabilitation Using a Multimodal Internet of Things-Based Patient Monitoring System in a Smart Hospital

OBJECTIVE: Continuous monitoring of patients' physical and psychological status using wearable sensors and Internet of Things platforms may enhance rehabilitation. We aimed to assess the feasibility of an Internet of Things-based smart hospital system integrating multi-source data to support individualized rehabilitation in patients with gait disturbances. METHODS: We conducted a single-center feasibility study at Yongin Severance Hospital, Korea, including 15 inpatients with subacute central nervous system injuries (mean age, [Formula: see text] years). The system integrated smart insoles, smart bands, real-time location system data, and mobile application data into the electronic medical record. Gait parameters, including step count, walking distance, gait speed, stride length, and symmetry, were measured during self-exercise. The app collected self-reported scores on pain, anxiety, depression, appetite, sleep, and general condition. Compliance, patient satisfaction, and nurses' qualitative feedback were analyzed descriptively. RESULTS: Monitoring lasted [Formula: see text] days. Patients averaged 7,[Formula: see text],520 steps/day and walked 3,[Formula: see text],198 m/day; 87% showed reduced stride length and 27% had marked gait asymmetry. Application-based symptom monitoring enabled tailored interventions, including medication adjustments and referrals. Smart band data were sometimes incomplete owing to recording errors. Operational challenges included battery depletion, data transfer interruptions, and device registration errors. Overall satisfaction averaged 4.28/5; comfort rated the highest, durability the lowest. Nurses valued real-time condition detection and improved self-report honesty but noted increased workload. CONCLUSION: Implementing an Internet of Things-based system that integrates wearable and self-reported data into an electronic medical record is feasible in inpatient rehabilitation, facilitating individualized feedback and clinical decision-making while maintaining high patient adherence and satisfaction. Clinical Impact-This study shows the feasibility of an IoT-based smart hospital system integrating multisource data into EMRs, enabling personalized rehabilitation, improving clinical decision-making, and supporting scalable digital healthcare models.