Integration of smart insoles for gait assessment in exoskeleton assisted rehabilitation

A robotic exoskeleton enables individuals with limited or no mobility to engage in moderate exercises, thereby promoting physical fitness and overall well-being. However, exoskeletons alone do not provide comprehensive insights into gait pattern monitoring and analysis over time. This study proposes...

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Veröffentlicht in:Scientific reports Jg. 15; H. 1; S. 28350 - 16
Hauptverfasser: D’Arco, Luigi, Wang, Haiying, Zheng, Huiru
Format: Journal Article
Sprache:Englisch
Veröffentlicht: London Nature Publishing Group UK 04.08.2025
Nature Publishing Group
Nature Portfolio
Schlagworte:
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Adult
Algorithms
Biomechanical Phenomena
Brain Injuries, Traumatic - physiopathology
Brain Injuries, Traumatic - rehabilitation
Exercise Therapy - methods
Exoskeleton
Exoskeleton Device
Female
Fitness equipment
Foot Orthoses
Gait
Gait - physiology
Gait analysis
Gait kinematic parameters
Gait kinetic parameters
Humanities and Social Sciences
Humans
Kinematics
Male
Middle Aged
multidisciplinary
Multiple sclerosis
Multiple Sclerosis - physiopathology
Multiple Sclerosis - rehabilitation
Musculoskeletal diseases
Physical fitness
Rehabilitation
Robotics
Science
Science (multidisciplinary)
Sensors
Shoes
Smart insoles
Spinal cord injuries
Spinal Cord Injuries - physiopathology
Spinal Cord Injuries - rehabilitation
Stroke Rehabilitation
Traumatic brain injury
Walking
Gait kinetic parameters
Gait kinematic parameters
Exoskeleton
Rehabilitation
Smart insoles
Gait analysis
ISSN:2045-2322, 2045-2322
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Zusammenfassung:A robotic exoskeleton enables individuals with limited or no mobility to engage in moderate exercises, thereby promoting physical fitness and overall well-being. However, exoskeletons alone do not provide comprehensive insights into gait pattern monitoring and analysis over time. This study proposes the integration of smart insoles as a cost-effective and non-invasive tool for gait assessment in exoskeleton-assisted rehabilitation. Ten participants, including three unimpaired subjects used only as a reference, one stroke, one spinal cord injury, one traumatic brain injury, and four multiple sclerosis subjects were involved in a 12-week program where weekly rehabilitation exercises were conducted and gait patterns were monitored in three assessment sessions. Gait phases were identified using a Finite State Machine, with transitions guided by predictions from a fuzzy c-means clustering algorithm. Kinematic and kinetic analyses revealed significant disparities in stride time, stance time, and the trajectories of the centre of pressure. The findings demonstrated that while the exoskeleton enabled participants with limited or no mobility to walk similarly to unimpaired individuals, the use of smart insoles identified notable differences in their gait patterns. These differences could be traced back to choices in the rehabilitation plan, underscoring the importance of such devices for understanding rehabilitation progress. An acceptability analysis showed that participants found the smart insoles comfortable and expressed a willingness to use them for future rehabilitation. In conclusion, this study demonstrates the potential of smart insoles for the assessment of individuals’ rehabilitation progress while using an exoskeleton, laying the groundwork for a system that can support clinicians in developing tailored rehabilitation plans.
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ISSN:2045-2322
2045-2322
DOI:10.1038/s41598-025-10032-y