Development of a novel real-time simulation of human skeleton/muscles

Roozbahani, Hamid; Alizadeh, Marjan; Ustinov, Stanislav; Handroos, Heikki

doi:10.1016/j.jbiomech.2020.110157

Cited by 4 publications

(1 citation statement)

References 11 publications

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“…Tetragonal phase is the premise of piezoelectric properties of the composites, so it is particularly important to make the Curie temperature of the composites higher than the service temperature range. [40] The service temperature range of artificial bone is -30 ℃~50 ℃, so the samples of 95BT+5HA would maintain certain piezoelectricity in the service temperature range.…”

Section: Electrical Performancementioning

confidence: 99%

Preparation and properties of artificial bone with lead-free piezoelectric materials

Cheng¹

2023

MatLab

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In order to fabricate the artificial bone with high bioactive property, lead-free barium titanate (BaTiO3, BT) piezoelectric material added hydroxyapatite (HA) composites were prepared in this study. Compared with the pure HA materials, the introduction of BT can increase the electrical properties of the samples while ensuring good biological properties. The electrical properties, such as piezoelectric constant d33, hysteresis loop and dielectric spectrum were measured, respectively. The bending strength, Vickers hardness, cytotoxicity and osteogenic property of the BT/HA composites were also discussed. It is revealed that the non-toxic sample with 95 wt% BT and 5 wt% HA (95BT+5HA) has the best osteoinductivity, the piezoelectric constant d33 of which is 79.2 pC N-1. The bending strength and Vickers hardness of the 95BT+5HA sample are 138.3 MPa and 472.4, respectively, realizing the desired mechanical properties of human bones. Comprehensive analyses of various properties show that the 95BT+5HA composite can meet the requirements of artificial bone, and is expected to be a promising generation of substitute bone materials.

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Section: Electrical Performancementioning

confidence: 99%

Preparation and properties of artificial bone with lead-free piezoelectric materials

Cheng¹

2023

MatLab

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Design and Development of a Robust Control Platform for a 3-Finger Robotic Gripper Using EMG-Derived Hand Muscle Signals in NI LabVIEW

Loskutova,

Roozbahani,

Alizadeh

et al. 2024

J Intell Robot Syst

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Robots are increasingly present in everyday life, replacing human involvement in various domains. In situations involving danger or life-threatening conditions, it is safer to deploy robots instead of humans. However, there are still numerous applications where human intervention remains indispensable. The strategy to control a robot can be developed based on intelligent adaptive programmed algorithms or by harnessing the physiological signals of the robot operator, such as body movements, brain EEG, and muscle EMG which is a more intuitive approach. This study focuses on creating a control platform for a 3-finger gripper, utilizing Electromyography (EMG) signals derived from the operator’s forearm muscles. The developed platform consisted of a Robotiq three-finger gripper, a Delsys Trigno wireless EMG, as well as an NI CompactRIO data acquisition platform. The control process was developed using NI LabVIEW software, which extracts, processes, and analyzes the EMG signals, which are subsequently transformed into control signals to operate the robotic gripper in real-time. The system operates by transmitting the EMG signals from the operator's forearm muscles to the robotic gripper once they surpass a user-defined threshold. To evaluate the system's performance, a comprehensive set of regressive tests was conducted on the forearm muscles of three different operators based on four distinct case scenarios. Despite of the gripper’s structural design weakness to perform pinching, however, the results demonstrated an impressive average success rate of 95% for tasks involving the opening and closing of the gripper to perform grasping. This success rate was consistent across scenarios that included alterations to the scissor configuration of the gripper.

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Artificial neural network can improve the accuracy of a markerless skeletal model in L5/S1 position estimation during symmetric lifting

Liu

Chang

Kao

et al. 2022

Journal of Biomechanics

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Development of a novel real-time simulation of human skeleton/muscles

Cited by 4 publications

References 11 publications

Preparation and properties of artificial bone with lead-free piezoelectric materials

Preparation and properties of artificial bone with lead-free piezoelectric materials

Design and Development of a Robust Control Platform for a 3-Finger Robotic Gripper Using EMG-Derived Hand Muscle Signals in NI LabVIEW

Artificial neural network can improve the accuracy of a markerless skeletal model in L5/S1 position estimation during symmetric lifting

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