Upper limb motor recovery using a digital health-driven IoT rehabilitation system: a case report

Digital health-driven rehabilitation systems incorporating Internet of Things (IoT) technologies have attracted increasing attention as a means to support upper limb motor recovery after stroke. However, detailed clinical descriptions of their implementation in routine inpatient rehabilitation remain limited.

We report the case of a right-handed man in his forties with right-sided upper limb motor impairment following putaminal hemorrhage. The patient underwent rehabilitation using a digital health-driven IoT-based upper limb rehabilitation system starting approximately one month after stroke onset during the convalescent rehabilitation phase.

The intervention was conducted over a two-week period, consisting of 10 sessions (approximately 40 min per session) as part of routine inpatient rehabilitation. The system integrated a portable smart projector, a three-dimensional motion capture sensor, and a communication robot to deliver interactive, task-oriented training. Five activities of daily living-oriented tasks (wiping, unlocking, squeezing, cup transfer, and typing) were implemented, with task difficulty adjusted by the treating occupational therapist according to the patient's performance.

Upper limb motor function assessed by the Fugl-Meyer Assessment for the Upper Extremity improved from 63 to 66. Real-world arm use assessed by the Motor Activity Log showed an Amount of Use score of 5 both before and after the intervention, suggesting a ceiling effect, while the Quality of Movement score improved slightly from 4.8 to 5. The patient demonstrated high engagement and adherence throughout the intervention, and no adverse events were observed.

This case report demonstrates the clinical feasibility of integrating a digital health-driven IoT rehabilitation system into routine inpatient stroke rehabilitation. Although generalization is limited by the single-case design, the present case highlights the potential of IoT-based digital health technologies to support task-oriented training and patient engagement in upper limb rehabilitation.