Human Hand Anatomy-Based Prosthetic Hand

Dunai, Larisa; Novák, Martin; Espert, Carmen García

doi:10.3390/s21010137

Cited by 42 publications

(35 citation statements)

References 22 publications

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“…This property is important because more closer the system designed to the natural anatomy, more functional the robotic hand will be. There are many design suggestions about the mechanical design in the literature [12], [13]. After the literature survey performed, InMoov company's open source robotic hand prototype was selected as the base design for the project [14].…”

Section: Mechanical Design Of Robotic Handmentioning

confidence: 99%

Design of Steady-State Visually-Evoked Potential Based Brain-Computer Interface System

Avci

Hamurcu

Bozbas³

et al. 2022

J Intell Syst Appl

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In this study, Steady-State Visual Evoked Potential (SSVEP)-based Brain-Computer Interface (BCI) system, which is popular in many sectors (game, defense, sports, etc.), especially in medicine, was composed. In addition, a robot hand was designed to be integrated into the BCI system, especially to help partially or completely disabled individuals. For this purpose, feature extraction was performed using discrete wavelet transform (Db6) from SSVEP signals recorded from seven different frequencies (6, 6.5, 7, 7.5, 8.2, 9.3, 10 Hz) and four different individuals. Extracted features were classified by support vector machine (SVM) and k-nearest neighbor (k-NN) algorithms. According to the classification results, the highest performance was obtained in the SVM algorithm with an accuracy of 84%.

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Section: Mechanical Design Of Robotic Handmentioning

confidence: 99%

Design of Steady-State Visually-Evoked Potential Based Brain-Computer Interface System

Avci

Hamurcu

Bozbas³

et al. 2022

J Intell Syst Appl

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“…These bones are called phalanges. Each fingers is built of four phalanges namely distal, middle and proximal phalanges and metacarpal bones 33) . The movement of fingers (flexion or abduction) is done with the help of tendons and ligaments.…”

Section: -D Modellingmentioning

confidence: 99%

Non-Invasive Invitro Modelling and Finite Elemental Analysis of a Uniquely Designed Prosthetic Hand

Jha¹,

Soni²,

Suhaib³

2022

Evergreen

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In the presented work a unique design for the upper limb prosthesis is evaluated for the stress concentration by the help of finite element analysis method. This paper gives validation for the novel prosthesis design. Human hand is most difficult body part to mimic both aesthetically and functionally. To obtain a functional prosthesis studying stresses developed in the most functional parts of hand prosthesis is mandatory. A static 3D structural finite element approach was followed. This study gives overall distribution of stress on the tendon, pulley and palm being the maximum force exerting parts. Thus, design efficiency is validated and fabrication of said hand is done using 3D printing. Fabrication of the prosthetic hand has been designed with the safe limits of factor of safety and have been designed for a maximum of weight lifted of 0.5 kg and it is tested safe as per finite element analysis.

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“…The human anatomy inspires a prosthetic hand presented by Dunai et al [211]. It works by using sEMG sensors to allow the user to activate the prosthesis and FSR sensors to simulate the touch pressure of the fingers.…”

Section: Biopotentials and Image-based Systemsmentioning

confidence: 99%

“…Krasoulis et al [211] proposed a multimodal control for prosthetic hand, which combines sEMG sensors with IMU systems. In detail, each EMG electrode incorporated a nine-degree-of-freedom (DOF) IMU, i.e., a triaxial accelerometer; gyroscope; and magnetometer measuring acceleration, angular velocity, and magnetic field, respectively.…”

Section: Biopotentials and Image-based Systemsmentioning

confidence: 99%

Biosignal-Based Human–Machine Interfaces for Assistance and Rehabilitation: A Survey

Esposito

Centracchio

Andreozzi

et al. 2021

Sensors

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As a definition, Human–Machine Interface (HMI) enables a person to interact with a device. Starting from elementary equipment, the recent development of novel techniques and unobtrusive devices for biosignals monitoring paved the way for a new class of HMIs, which take such biosignals as inputs to control various applications. The current survey aims to review the large literature of the last two decades regarding biosignal-based HMIs for assistance and rehabilitation to outline state-of-the-art and identify emerging technologies and potential future research trends. PubMed and other databases were surveyed by using specific keywords. The found studies were further screened in three levels (title, abstract, full-text), and eventually, 144 journal papers and 37 conference papers were included. Four macrocategories were considered to classify the different biosignals used for HMI control: biopotential, muscle mechanical motion, body motion, and their combinations (hybrid systems). The HMIs were also classified according to their target application by considering six categories: prosthetic control, robotic control, virtual reality control, gesture recognition, communication, and smart environment control. An ever-growing number of publications has been observed over the last years. Most of the studies (about 67%) pertain to the assistive field, while 20% relate to rehabilitation and 13% to assistance and rehabilitation. A moderate increase can be observed in studies focusing on robotic control, prosthetic control, and gesture recognition in the last decade. In contrast, studies on the other targets experienced only a small increase. Biopotentials are no longer the leading control signals, and the use of muscle mechanical motion signals has experienced a considerable rise, especially in prosthetic control. Hybrid technologies are promising, as they could lead to higher performances. However, they also increase HMIs’ complexity, so their usefulness should be carefully evaluated for the specific application.

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Human Hand Anatomy-Based Prosthetic Hand

Cited by 42 publications

References 22 publications

Design of Steady-State Visually-Evoked Potential Based Brain-Computer Interface System

Design of Steady-State Visually-Evoked Potential Based Brain-Computer Interface System

Non-Invasive Invitro Modelling and Finite Elemental Analysis of a Uniquely Designed Prosthetic Hand

Biosignal-Based Human–Machine Interfaces for Assistance and Rehabilitation: A Survey

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