Details

Enhancing trunk balance and stability is a key objective in SCI rehabilitation. Various exercise modalities, including proprioceptive training, core strengthening, yoga, and Pilates, are employed to improve motor skills, coordination, and quality of life. Recently, virtual reality (VR)-based approaches, such as the C-Mill treadmill (Hocoma AG, Switzerland), have gained prominence. The C-Mill integrates visual and motor training through a suspension-supported system that ensures safe ambulation while adapting to the patient's pace. Unlike conventional treadmills and robotic-assisted devices, it uniquely incorporates VR to simulate real-world gait challenges, bridging the gap between traditional therapies and independent walking. This study aims to investigate the effects of gait exercises performed with the C-Mill treadmill on trunk balance and stability by leveraging its advantages, such as gradual weight-bearing, improved gait stability, and reduced fatigue. Our study is a prospective observational study. Regardless of whether exercises are performed conventionally or on an alternative gait platform such as the C-Mill, all interventions are part of routine clinical practice. Patients whose treatment programs already align with the aforementioned procedures will be included. In robotic rehabilitation and assisted gait device laboratories equipped with the C-Mill platform, spinal cord injury patients follow a standardized rehabilitation protocol. These laboratories operate on an appointment-based system. After random group allocation, patients in the study group will undergo assessments at the beginning and end of C-Mill therapy, while control group patients will be enrolled before initiating C-Mill treatment. Following data collection for the control group, these patients will also receive C-Mill therapy. The study aims to identify differences in outcomes between the applied interventions. Data Quality and Management Procedures Patients admitted for inpatient treatment at the Spinal Cord Injury Rehabilitation Clinic of Ankara Bilkent City Hospital, who meet the inclusion criteria and voluntarily agree to participate in the study by reading and signing the informed consent form, will be included in the study. The medical status of all participants will be evaluated and recorded by the clinical research responsible physician. A predefined data management plan will be implemented for missing, inconsistent, or erroneous data. Missing data will be identified and analyzed using statistical methods such as multiple imputation when necessary. To ensure the integrity of data entry, regular audits and consistency checks will be performed by a physiotherapist involved in the study. To increase the reliability of the data, patient records and assessment reports will be cross-checked with the collected data. This will include comparisons made with electronic health records, paper-based case reports, and direct observation notes. All study procedures, including patient recruitment, data collection, data entry, data analysis, and reporting of adverse events, will be carried out according to predefined criteria. Any adverse events or unexpected complications occurring during the study will be systematically documented and reported. The determination of the appropriate sample size was based on the study by Khurana et al. A priori power analysis was conducted using the G\* Power software (version 3.0.10, Universität Düsseldorf, Düsseldorf, Germany). The sample size for our study was calculated to include a minimum of 11 patients per group, ensuring 80% power with an alpha error rate of 0.05. For statistical analysis, descriptive statistics will be presented as the mean and standard deviation for numerical variables if the parametric assumptions are met, and as the median and minimum-maximum values if the parametric assumptions are not met. For categorical variables, frequency and percentage values will be reported. The statistical significance of differences between groups will be examined using the Independent Samples T-Test if parametric assumptions are met, and the Mann-Whitney U Test if parametric assumptions are not met. Analyses will be conducted with a significance level of p \< 0.05.