Data Acquisition Glove for Hand Movement Impairment Rehabilitation

Tavares, R.; Abreu, Paulo; Quintas, Manuel Rodrigues

doi:10.3991/ijoe.v12i04.5141

Cited by 7 publications

(6 citation statements)

References 4 publications

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“…The glove design allows embedding several tactile cells in a single sensor patch with arbitrary perimeter and free-form surface. The instrumented glove reported in [20][21][22] uses feedback technique by means of rotation measurement of each finger joint and pressure on fingertips. Angular position sensors and pressure sensors are used at this purpose.…”

Section: Glove-based Systemsmentioning

confidence: 99%

“…Then they are well suited for implementation in advanced wearable interfaces. 21,22,29,30 Sensors based on optical fibers are basically represented by waveguides placed on fingers: due to finger bending, stresses are induced into the waveguides due to the differences on mechanical properties of fiber and substrate, resulting in light attenuation. Therefore, the intensity of optical signals can be correlated to the angular displacements of finger joints.…”

Section: Sensors Typologiesmentioning

confidence: 99%

“…Present a gamelike interface. [20][21][22] A graphical application has been developed in order to monitor each finger displacement and to implement rehabilitation exercises. This GUI uses the microchip graphics library functions and has been developed with the graphics display designer GDDX.…”

Section: Graphical Interfacementioning

confidence: 99%

See 2 more Smart Citations

Glove-based systems for medical applications: review of recent advancements

Pasquale¹,

Mastrototaro²

2018

JTEFT

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Human hand motion analysis is attracting researchers in the areas of neuroscience, biomedical engineering, robotics, human-machines interfaces (HMI), humancomputer interaction (HCI), and artificial intelligence (AI). Among the others, the fields of medical rehabilitation and physiological assessments are suggesting high impact applications for wearable sensing systems. Glove-based systems are one of the most significant devices in assessing quantities related to hand movements. This paper provides updated survey among the main glove solutions proposed in literature for hand rehabilitation. Then, the process for designing glove-based systems is defined, by including all relevant design issues for researchers and makers. The main goal of the paper is to describe the basics of glove-based systems and to outline their potentialities and limitations. At the same time, roadmap to design and prototype the next generation of these devices is defined, according to the results of previous experiences in the scientific community.

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Section: Glove-based Systemsmentioning

confidence: 99%

Section: Sensors Typologiesmentioning

confidence: 99%

See 1 more Smart Citation

Glove-based systems for medical applications: review of recent advancements

Pasquale¹,

Mastrototaro²

2018

JTEFT

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“…Tavares has developed data acquisition in the form of a glove to detect movement disorders in post-stroke patients [9]. In this development, accelerometer and gyroscope sensors were placed on the glove and were used to detect the position and rotation of the hand movement.…”

Section: Introductionmentioning

confidence: 99%

Investigation of Electrode Location to Improve the Accuracy of Wearable Hand Exoskeleton Trainer Based on Electromyography

Triwiyanto

Rahmawati

Pawana

et al. 2022

JBBBE

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EMG signal has a random and stochastic characteristics, so it is difficult to predict the amplitude. Furthermore, the EMG signal depends on the electrodes location. Therefore, a proper muscle selection determines the system's accuracy value. The purpose of this study was to investigate the exact location of the electrodes to improve the accuracy of the wearable hand exoskeleton trainer based on electromyography (EMG) signal control. The main advantage of the results of this study is that the most dominant muscle was found in the development of a wearable hand exoskeleton based on an EMG signal threshold. Therefore, the model can be controlled using a single electrode pair which can further be applied using a low-cost microcontroller. In this study, ten respondents were involved in the data acquisition. The discovery of the dominant muscle was carried out by investigating the dominant EMG signal in three muscles (Abductor pollicis longus, extensor digitorum) that plays a role in the open and close movements of the hand exoskeleton. Dry electrode was used to detect EMG signal activity on the skin surface. The EMG signal was then extracted using the root mean square (RMS) feature. After the evaluation, the results showed that the flexor digitorum superficialis muscle in the rest position produced higher accuracy value than the other muscles, which was 96.63±0.67%. In the implementation, the product of this research can be applied for rehabilitation steps in post-stroke patients which is carried out either in a medical rehabilitation unit or at home independently.

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“…Rodriguez et al [19] presented a 3-D rehabilitation system, with sensory feedback. Another study by Hatzigiannakoglou et al [20] described a data acquisition wearable device for hand rehabilitation used for patients with hand movement impairment. The rotation of the hand is measured through tracks of gloves that are then translated using the MPU tool.…”

Section: Introductionmentioning

confidence: 99%

Toward Hand Functions Rehabilitation Using the Virtual World for Pre-school Children with Cerebral Palsy

Sabry

Sahib

Nayl

2020

Int. J. Emerg. Technol. Learn.

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Cerebral Palsy (CP)is a collection of permanent, non-progressive disorders that impact the individual’s motor ability. The rehabilitation of patients with CP is very important to improve their motor abilities and to minimize the need for third parties. In this paper, a low-cost hand rehabilitation glove based on finger bend/pressure analysis is presented. The data glove is used to improve hand functioning for pre-school children with cerebral palsy through virtual reality games. The system consists of two parts: the data glove and several virtual games. The data glove consists of a microcontrol-ler, flex sensors, force sensors and radiofrequency transmission units. The use of the newly developed system will assist psychotherapist to follow the CP child daily, weekly or monthly. The rehabilitation model and the predicted physiotherapy results can be extracted from the patient’s record after using the data. Experimental results have shown that the regular usage for the data glove improved 75 % of the participants’ fingers bending angel and the child’s grip ability.

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Data Acquisition Glove for Hand Movement Impairment Rehabilitation

Cited by 7 publications

References 4 publications

Glove-based systems for medical applications: review of recent advancements

Glove-based systems for medical applications: review of recent advancements

Investigation of Electrode Location to Improve the Accuracy of Wearable Hand Exoskeleton Trainer Based on Electromyography

Toward Hand Functions Rehabilitation Using the Virtual World for Pre-school Children with Cerebral Palsy

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