Development and control of a home-based training device for hand rehabilitation with a spring and cable driven mechanism
-
Kasim Serbest
,
Mustafa Kutlu
Abstract
Rehabilitation at home is rapidly increasing. Although successful results are achieved with treatment methods applied in rehabilitation clinics, there are also some disadvantages in this process, such as dependence on an expert and high costs. Developments in mechatronic technologies have accelerated the development of assistive devices which are designed for use at home. One of the rehabilitation applications is on a hemiplegic hand. In previous studies, some useful devices have been developed for hand rehabilitation. In this study, we suggest a new, low-cost and wearable robotic glove for hand rehabilitation. The specific component of this device is the spring and cable driven system proposed for transmission of motion and force. The device was tested on both unimpaired participants and patients with the hemiplegic hand, and it was proven to be beneficial for hand rehabilitation. As a result of trials with unimpaired participants, the muscle activation of the extensor digitorum and the flexor carpi radialis were increased by 184.1 and 197.8% respectively. The weight of the device was less than 400 g, thanks to 3D printed parts.
Funding source: The Scientific and Technological Research Council of Turkey (TUBITAK)
Award Identifier / Grant number: 115M622
Acknowledgments
A special thanks is extended to Assoc. Prof. Dr. Arno H. A. Stienen of Northwestern University for his contribution to spring mechanism design.
Research funding: This study was supported by The Scientific and Technological Research Council of Turkey (TUBITAK) with project No. 115M622.
Author contributions: All authors have accepted responsibility for the entire content of this manuscript and approved its submission.
Competing interest: Authors state no conflict of interest.
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© 2021 Walter de Gruyter GmbH, Berlin/Boston
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Articles in the same Issue
- Frontmatter
- Research Articles
- Attention based convolutional network for automatic sleep stage classification
- Emotion recognition using time–frequency ridges of EEG signals based on multivariate synchrosqueezing transform
- A novel signal to image transformation and feature level fusion for multimodal emotion recognition
- PVC arrhythmia classification based on fractional order system modeling
- A clinical set-up for noninvasive blood pressure monitoring using two photoplethysmograms and based on convolutional neural networks
- Virtual simulation of otolith movement for the diagnosis and treatment of benign paroxysmal positional vertigo
- Development and control of a home-based training device for hand rehabilitation with a spring and cable driven mechanism
- An easy and low-cost biomagnetic methodology to study regional gastrointestinal transit in rats
- Detection of adverse events leading to inadvertent injury during laparoscopic cholecystectomy using convolutional neural networks
- Comparison of a standardized four-point bending test to an implant system test of an osteosynthetic system under static and dynamic load condition
- An application of finite element method in material selection for dental implant crowns
