Evaluation of the improvement of walking ability in patients with spinal cord injury using lower limb rehabilitation robots based on data science

Abstract

Spinal cord injury (SCI) is a serious disabling injury, and the main factors causing SCI in patients include car accidents, falls from heights, as well as heavy blows and falls. These factors can all cause spinal cord compression or even complete rupture. After SCI, problems with the movement, balance, and walking ability of the lower limbs are most common, and SCI can cause abnormalities in patient’s movement, sensation, and other aspects. Therefore, in the treatment of SCI, it is necessary to strengthen the rehabilitation training (RT) of patients based on data science to improve their motor ability and play a positive role in the recovery of their walking ability. This article used lower limb rehabilitation robot (LLRR) to improve the walking ability of SCI patients and applied them to SCI rehabilitation. The purpose is to improve the limb movement function of patients by imitating and assisting their limb movements, thereby achieving pain relief and muscle strength enhancement and promoting rehabilitation. The experimental results showed that the functional ambulation category (FAC) scale scores of Group A and Group B were 0.79 and 0.81, respectively, in the first 10 weeks of the experiment. After 10 weeks of the experiment, the FAC scores of Group A and Group B were 2.42 and 4.36, respectively. After the experiment, the FAC score of Group B was much higher than that of Group A, indicating that Group B was more effective in improving patients’ walking ability compared to Group A. This also indicated that LLRR rehabilitation training can enhance the walking ability of SCI patients.

Improving Outcomes in People with Spinal Cord Injury: Encouraging Results from a Multidisciplinary Advanced Rehabilitation Pathway

“…During daily locomotor training, the partial unloading of body weight, combined with rhythmic cyclic movements, facilitates stable stepping and reduces inappropriate activation of the tibialis anterior. This aspect highlights the significance of movement awareness and quality, which is facilitated by multisensory feedback [42][43][44]. On the other hand, VR provides immediate feedback through multisensory stimulation, teaching the body and brain how to correct patients' movements based on what they have learned (reinforcement learning).…”