Sensor-Derived Trunk Stability and Gait Recovery: Evidence of Neuromechanical Associations Following Intensive Robotic Rehabilitation
| dc.contributor.author | Sirzai, Hulya | |
| dc.contributor.author | Gokhan, Yigit Can | |
| dc.contributor.author | Yavuzer, Gunes | |
| dc.contributor.author | Argunsah, Hande | |
| dc.date.accessioned | 2026-11-05T11:04:14Z | |
| dc.date.issued | 2026 | |
| dc.description.abstract | This quantitative observational study with pre-post design aimed to examine joint-specific kinematic adaptations and the relationship between trunk stability and spatiotemporal gait parameters following intensive robotic rehabilitation. A total of 12 neurological patients completed 16 sessions of gait training using the Tecnobody Smart Gravity Walker. Pre- and post-training kinematic data were collected for bilateral hip and knee flexion-extension, trunk flexion-extension, trunk lateral flexion, and center-of-gravity displacement. Waveforms were normalized to 100% stride. Paired t-tests assessed pre-post differences, and correlations examined associations between trunk stability and gait performance. Significant increases were found in right hip flexion-extension (t = 3.44, p < 0.001), trunk flexion-extension (t = 9.49, p < 0.001), and center-of-gravity displacement (t = 15.15, p < 0.001), with reduced trunk lateral flexion (t = -8.64, p < 0.001). Trunk flexion-extension correlated with gait speed (r = 0.74), step length (r = 0.68), and stride length (r = 0.71); trunk lateral flexion correlated with cadence (r = 0.66) and stride length (r = 0.70). Intensive robotic rehabilitation improved trunk and hip kinematics, supporting trunk stability as an important biomechanical correlate of gait recovery. Sensor-derived metrics revealed strong neuromechanical coupling between postural control and locomotion in neurological patients. | |
| dc.description.issue | 2 | |
| dc.description.pages | 573 | |
| dc.description.sponsorship | The APC was funded by Acibadem Mehmet Ali Aydinlar University, The Academic Activity Support Commission. | |
| dc.description.volume | 26 | |
| dc.identifier.doi | 10.3390/s26020573 | |
| dc.identifier.issn | 1424-8220 | |
| dc.identifier.uri | https://doi.org/10.3390/s26020573 | |
| dc.identifier.uri | https://openaccess.acibadem.edu.tr/handle/11443/11163 | |
| dc.identifier.wos | WOS:001672724000001 | |
| dc.language.iso | en | |
| dc.publisher | MDPI | |
| dc.relation.funding | Acibadem Mehmet Ali Aydinlar University, The Academic Activity Support Commission | |
| dc.relation.hasversion | 10.3390/s26020573 | |
| dc.relation.ispartof | SENSORS | |
| dc.subject | sensor-based rehabilitation | |
| dc.subject | trunk stability | |
| dc.subject | robotic gait training | |
| dc.subject | kinematic analysis | |
| dc.subject | neurological disorders | |
| dc.subject | gait recovery | |
| dc.subject | neuromechanical coupling | |
| dc.subject | Tecnobody Smart Gravity Walker | |
| dc.subject | Chemistry, Analytical | |
| dc.subject | Engineering, Electrical & Electronic | |
| dc.subject | Instruments & Instrumentation | |
| dc.subject | Chemistry | |
| dc.subject | Engineering | |
| dc.title | Sensor-Derived Trunk Stability and Gait Recovery: Evidence of Neuromechanical Associations Following Intensive Robotic Rehabilitation | |
| dc.type | Article | |
| oaire.citation.edition | Science Citation Index Expanded (SCI-EXPANDED) | |
| oaire.citation.issue | 2 | |
| oaire.citation.volume | 26 | |
| person.identifier.orcid | 0009-0003-7234-227X | |
| person.identifier.rid | NWI-0772-2025 |
