Jang Hwan Kim

Amputees typically experience changes in residual limb volume in their daily lives. It causes an uncomfortable fit of the socket by applying high pressure on the sensitive area of the residual limb or by loosening the socket. In this study, we developed a transfemoral prosthetic socket for above-the-knee amputees that ensures a good socket fit by maintaining uniform and constant contact pressure despite volume changes in the residual limb. The socket has two air bladders in the posterior femoral region, and the pneumatic controller is located on the tibia of the prosthesis. The pneumatic system aims to minimize unstable fitting of the socket and improve walking performance by inflating or deflating the air bladder. The developed socket autonomously maintains the air pressure inside the prosthetic socket at a steady-state error of 3 mmHg or less by adjusting the amount of air in the air bladder via closed-loop control. In the clinical trial, amputee participants walked on flat and inclined surfaces. The displacement between the residual limb and socket during the gait cycle was reduced by up to 33.4% after air injection into the socket. The inflatable bladder increased the knee flexion angle on the affected side, resulting in increased stride length and gait velocity. The pneumatic socket provides a stable and comfortable walking experience not only when walking on flat ground but also on slopes.

Applications of machine learning in the healthcare field have become increasingly diverse. In this review, we investigated the integration of artificial intelligence (AI) in predicting the prognosis of patients with central nervous system disorders such as stroke, traumatic brain injury, and spinal cord injury. AI algorithms have shown promise in prognostic assessment, but challenges remain in achieving a higher prediction accuracy for practical clinical use. We suggest that accumulating more diverse data, including medical imaging and collaborative efforts among hospitals, can enhance the predictive capabilities of AI. As healthcare professionals become more familiar with AI, its role in central nervous system rehabilitation is expected to advance significantly, revolutionizing patient care.