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Updated: Jan 30, 2026

Development of a Novel Task-oriented Rehabilitation Program using a Bimanual Exoskeleton Robotic Hand
Published on: May 20, 2020
Multimodal measurement of hand function with the SensorE Exoskeleton: a validation study
Madison Bates1, Makenna Pelfrey1, Amanda C Glueck2
1F. Joseph Halcomb III, MD, Department of Biomedical Engineering, University of Kentucky, Lexington, KY, United States of America.
Abstract:
Objectives.Strokes often cause long-term upper extremity impairments, yet objective, multimodal measurement tools remain scarce. Current clinical assessments rely heavily on subjective scoring based on coarse rating scales, limiting the ability to discern subtle changes in function during therapy. This study aimed to design and validate the SensorE Exoskeleton (SEE), a novel multimodal wearable device capable of simultaneously quantifying finger flexion and applied fingertip force, which is not a common feature in existing tools.Approach.SEE integrates flex and force sensors into a lightweight wearable design intended for use on normal hands as well as those on which wearing a glove would be difficult due to spasticity associated with conditions such as stroke. Static calibration tests confirmed consistent and monotonic sensor responses. Thirty non-clinical, healthy participants (mean age 25.8 ± 4.6 years; both sexes) completed three graded tasks-finger extension, contraction, and force exertion-guided by a graphical user interface (GUI) with four target levels. Participants were divided into two groups, with Group B using a modified GUI informed by feedback from Group A. SEE measurements of finger flexion and applied force were compared against a motion capture system (Leap Motion Controller) and a load cell, respectively.Main results.SEE reliably distinguished movement and force levels between targets in all tasks (p < 0.05). Flex sensor output was strongly correlated with reference motion capture data while the force output correlated well with the load cell measurements (|r|> 0.7). Mean relative errors (mean ± SE) were -0.22 ± 0.04% for flex sensors and -0.43 ± 4.37% for force sensors.Significance.SEE provides a multimodal wearable configuration for accurate, objective tracking of finger flexion and applied force, offering greater sensitivity than existing clinical assessments. These findings support its potential as a novel functional assessment tool for rehabilitation, with future validation in stroke and other patient populations.
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