Advancing Precision Rehabilitation Through a Sensor-Based 6-DoF Robotic Exoskeleton: Clinical Validation and Ergonomic Assessment
| dc.contributor.author | Argunsah, Hande | |
| dc.contributor.author | Yalcin, Begum | |
| dc.contributor.author | Ergin, Mehmet Alper | |
| dc.contributor.author | Coruhlu, Gokay | |
| dc.contributor.author | Yalcin, Mustafa | |
| dc.contributor.author | Patoglu, Volkan | |
| dc.contributor.author | Guven, Zeynep | |
| dc.date.accessioned | 2026-11-05T11:03:14Z | |
| dc.date.issued | 2025 | |
| dc.description.abstract | Effective upper-extremity rehabilitation requires intensive and precise movement training, yet conventional therapies lack accurate motion tracking. Robotic exoskeletons address this limitation but are often hindered by ergonomic misalignment and limited adaptability. The AssistOn-Arm, a novel self-aligning exoskeleton, integrates ergonomic design and back-drivable actuation to enhance comfort and facilitate natural user interaction. This study aimed to assess the usability and ergonomics of the device in healthy participants and to conduct a pilot clinical evaluation in individuals with upper-extremity impairments. Thirty healthy participants and twelve patients with shoulder impairments performed predefined tasks under participant-active and device-active conditions. Kinematic data captured concurrently with AssistOn-Arm and Xsens MVN demonstrated strong agreement between conditions. Quantitative analysis revealed no significant differences (p > 0.05) in flexion, elevation, abduction-adduction, and external rotation, indicating reliable alignment with natural joint axes. Significant differences (p < 0.05) were observed only in sagittal hyperextension and internal rotation, reflecting device mechanical constraints. The study confirms the clinical feasibility of AssistOn-Arm as a sensor-driven, self-aligning exoskeleton that bridges engineering innovation and precision rehabilitation, paving the way for its integration into clinical practice. | |
| dc.description.issue | 1 | |
| dc.description.pages | 88 | |
| dc.description.sponsorship | This research was funded by TUBITAK (grant number 111M186 and 120N523). | |
| dc.description.volume | 26 | |
| dc.identifier.doi | 10.3390/s26010088 | |
| dc.identifier.issn | 1424-8220 | |
| dc.identifier.uri | https://doi.org/10.3390/s26010088 | |
| dc.identifier.uri | https://openaccess.acibadem.edu.tr/handle/11443/11032 | |
| dc.identifier.wos | WOS:001658647200001 | |
| dc.language.iso | en | |
| dc.publisher | MDPI | |
| dc.relation.funding | TUBITAK(Turkiye Bilimsel ve Teknolojik Arastirma Kurumu (TUBITAK)) | |
| dc.relation.funding | TUBITAK [111M186, 120N523] | |
| dc.relation.hasversion | 10.3390/s26010088 | |
| dc.relation.ispartof | SENSORS | |
| dc.subject | sensor-based rehabilitation | |
| dc.subject | upper-extremity exoskeleton | |
| dc.subject | human-robot interaction | |
| dc.subject | ergonomic design | |
| dc.subject | clinical validation | |
| dc.subject | kinematic assessment | |
| dc.subject | assistive robotics | |
| dc.subject | MOTION | |
| dc.subject | SHOULDER | |
| dc.subject | STROKE | |
| dc.subject | Chemistry, Analytical | |
| dc.subject | Engineering, Electrical & Electronic | |
| dc.subject | Instruments & Instrumentation | |
| dc.subject | Chemistry | |
| dc.subject | Engineering | |
| dc.title | Advancing Precision Rehabilitation Through a Sensor-Based 6-DoF Robotic Exoskeleton: Clinical Validation and Ergonomic Assessment | |
| dc.type | Article | |
| oaire.citation.edition | Science Citation Index Expanded (SCI-EXPANDED) | |
| oaire.citation.issue | 1 | |
| oaire.citation.volume | 26 | |
| person.identifier.orcid | 0000-0002-5776-1797 | |
| person.identifier.orcid | 0000-0002-9883-3742 | |
| person.identifier.rid | NWI-0772-2025 | |
| person.identifier.rid | NXX-7750-2025 | |
| person.identifier.rid | HJP-0324-2023 | |
| person.identifier.rid | AAC-5081-2019 |
