*Result*: Advancing Precision Rehabilitation Through a Sensor-Based 6-DoF Robotic Exoskeleton: Clinical Validation and Ergonomic Assessment.

Title:
Advancing Precision Rehabilitation Through a Sensor-Based 6-DoF Robotic Exoskeleton: Clinical Validation and Ergonomic Assessment.
Authors:
Argunsah H; Department of Biomedical Engineering, Faculty of Engineering and Natural Sciences, Acibadem Mehmet Ali Aydinlar University, Istanbul 34752, Turkey., Yalcin B; Department of Biomedical Engineering, Graduate School of Natural and Applied Sciences, Acibadem Mehmet Ali Aydinlar University, Istanbul 34752, Turkey., Ergin MA; Faculty of Engineering, Natural Sciences of Sabancı University, Istanbul 34956, Turkey., Coruhlu G; Faculty of Engineering, Natural Sciences of Sabancı University, Istanbul 34956, Turkey., Yalcin M; Faculty of Engineering, Natural Sciences of Sabancı University, Istanbul 34956, Turkey., Patoglu V; Faculty of Engineering, Natural Sciences of Sabancı University, Istanbul 34956, Turkey., Guven Z; Department of Physical Medicine and Rehabilitation, School of Medicine, Acibadem Mehmet Ali Aydinlar University, Istanbul 34752, Turkey.
Source:
Sensors (Basel, Switzerland) [Sensors (Basel)] 2025 Dec 23; Vol. 26 (1). Date of Electronic Publication: 2025 Dec 23.
Publication Type:
Journal Article
Language:
English
Journal Info:
Publisher: MDPI Country of Publication: Switzerland NLM ID: 101204366 Publication Model: Electronic Cited Medium: Internet ISSN: 1424-8220 (Electronic) Linking ISSN: 14248220 NLM ISO Abbreviation: Sensors (Basel) Subsets: MEDLINE
Imprint Name(s):
Original Publication: Basel, Switzerland : MDPI, c2000-
References:
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J Shoulder Elbow Surg. 2020 Jan;29(1):68-78. (PMID: 31378683)
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Grant Information:
111M186 Scientific and Technological Research Council of Turkey; 120N523 Scientific and Technological Research Council of Turkey
Contributed Indexing:
Keywords: assistive robotics; clinical validation; ergonomic design; human–robot interaction; kinematic assessment; sensor-based rehabilitation; upper-extremity exoskeleton
Entry Date(s):
Date Created: 20260110 Date Completed: 20260110 Latest Revision: 20260113
Update Code:
20260130
PubMed Central ID:
PMC12788030
DOI:
10.3390/s26010088
PMID:
41516523
Database:
MEDLINE

*Further Information*

*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.*