ArticleFrontiers in bioengineering and biotechnology2020
Verification of Finger Joint Stiffness Estimation Method With Soft Robotic Actuator.
Article in Frontiers in bioengineering and biotechnology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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10 citing papers in PubMed.
- Optimal position fuzzy control for coordinated movement of the ring and little fingers in an impaired human hand.Biological cybernetics · 2025Article
- Optimal position fuzzy control for coordinated movement of the ring and little fingers in an impaired human hand.Biological cybernetics · 2025Article
- An interactive soft robotic hand-task training system with wireless task boards and daily objects on post-stroke rehabilitation.Wearable technologies · 2025Article
- Energy conservation-based on-line tuning of an analytical model for accurate estimation of multi-joint stiffness with joint modular soft actuators.Wearable technologies · 2025Article
- A Pneumatic Soft Exoskeleton System Based on Segmented Composite Proprioceptive Bending Actuators for Hand Rehabilitation.Biomimetics (Basel, Switzerland) · 2024Article
- Article
- Parameter estimation of a model describing the human fingers.Healthcare technology letters · 2024Article
- Addressing data imbalance in Sim2Real: ImbalSim2Real scheme and its application in finger joint stiffness self-sensing for soft robot-assisted rehabilitation.Frontiers in bioengineering and biotechnology · 2024Article
- A bidirectional fabric-based soft robotic glove for hand function assistance in patients with chronic stroke.Journal of neuroengineering and rehabilitation · 2023Article
- An online method to monitor hand muscle tone during robot-assisted rehabilitation.Frontiers in robotics and AI · 2023Article
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Authors and funding
5 authors.
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Abstract
Stroke has been the leading cause of disability due to the induced spasticity in the upper extremity. The constant flexion of spastic fingers following stroke has not been well described. Accurate measurements for joint stiffness help clinicians have a better access to the level of impairment after stroke. Previously, we conducted a method for quantifying the passive finger joint stiffness based on the pressure-angle relationship between the spastic fingers and the soft-elastic composite actuator (SECA). However, it lacks a ground-truth to demonstrate the compatibility between the SECA-facilitated stiffness estimation and standard joint stiffness quantification procedure. In this study, we compare the passive metacarpophalangeal (MCP) joint stiffness measured using the SECA with the results from our designed standalone mechatronics device, which measures the passive metacarpophalangeal joint torque and angle during passive finger rotation. Results obtained from the fitting model that concludes the stiffness characteristic are further compared with the results obtained from SECA-Finger model, as well as the clinical score of Modified Ashworth Scale (MAS) for grading spasticity. These findings suggest the possibility of passive MCP joint stiffness quantification using the soft robotic actuator during the performance of different tasks in hand rehabilitation.
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