Soft Driving Epicyclical Mechanism for Robotic Finger

Ramírez, José Luis; Rubiano, Astrid; Castiblanco, Paola

doi:10.3390/act8030058

Cited by 6 publications

(2 citation statements)

References 25 publications

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“…8, installed on the remote control, ESP32-Master firmware combined button control and SCR into one framework -with subprograms, headers, and supporting libraries, namely, ESP NOW master register peer & ESP NOW slave callback, Freertos Xtask with semaphore, pulse width modulation (PWM) servo, analog to digital (ADC) compiler, The ESP32-Slave, as shown in Fig. 9, was mounted on the servo controller in this case as a substitution of flexion and extension movement patterns for the Exo-glove poly using a hand prosthetic and servo mechanism from proto 1 [95], using underactuated pulley mechanism with DC servo as artificial MCP joint or flexion and extension to articulate finger movement which has similar as exo-glove poly servo mechanism [96,97,98,99]. The final firmware will be built with C++ programming with a .cpp extension like a pre-trained model design.…”

Section: G Final Embedded Tinyml Master-slavementioning

confidence: 99%

Development of Speech Command Control Based TinyML System for Post-Stroke Dysarthria Therapy Device

Riyanta,

Irianta,

Kamiel

2023

Journal of Robotics and Control

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Post-stroke dysarthria (PSD) is a widespread outcome of a stroke. To help in the objective evaluation of dysarthria, the development of pathological voice recognition and technology has a lot of attention. Soft robotics therapy devices have been received as an alternative rehabilitation and hand grasp assistance for improving activity daily living (ADL). Despite the significant progress in this field, most soft robotic therapy devices use a complex, bulky, lack of pathological voice recognition model, large computational power, and stationary controller. This study aims to develop a portable wirelessly multi-controller with a simulated dysarthric vowel speech in Bahasa Indonesia and non-dysarthric micro speech recognition, using tiny machine learning (TinyMl) system for hardware efficiency. The speech interface using INMP441, compute with a lightweight Deep Convolutional Neural network (DCNN) design and embedded into ESP-32. Feature model using Short Time Fourier Transform (STFT) and fed into CNN. This method has proven useful in micro-speech recognition with low computational power in both speech scenarios with a level of accuracy above 90%. Realtime inference performance on ESP-32 using hand prosthetics, with 3-level household noise intensity respectively 24db,42db, and 62db, and has respectively resulted from 95%, 85%, and 50% Accuracy. Wireless connectivity success rate with both controllers is around 0.2 - 0.5 ms.

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Section: G Final Embedded Tinyml Master-slavementioning

confidence: 99%

Development of Speech Command Control Based TinyML System for Post-Stroke Dysarthria Therapy Device

Riyanta,

Irianta,

Kamiel

2023

Journal of Robotics and Control

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“…The actuation level criterion of a robotic device concerns whether a device is fullyactuated or underactuated [37]. Fully actuated devices have the same number of DOFs and DOAs, with one actuator per DOF, whereas underactuated devices have more DOFs than actuators.…”

Section: Actuation Levelmentioning

confidence: 99%

Cable-driven underactuated wearable robotic devices for hand assistance

Bernardo¹

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To address the first aim, we carried out a feasibility clinical trial with ten post-stroke patients performing Activities of Daily Living (ADLs). We evaluated the physiological and kinematic effects of using a preliminary version of our hand exoskeleton that supported only finger extension combined with an elbow-assisting soft wearable robot (exosuit). We observed a reduction in the mean electromyographic (EMG) activity of the Biceps Brachii (BB), Anterior Deltoid (AD) and Extensor Digitorum Communis (EDC) muscles, as well as in the coactivation of pairs of muscles typically associated with pathological synergies. Questionnaires filled out by the participants, alongside discussions with healthcare professionals, provided positive and constructive feedback. This encouraged our continued efforts to develop and refine the device to expand its functionalities.The next step was to develop a model of the behaviour of the structures for defined input tensions on the wires. The main design parameter considered in the model is the rotational stiffness of the joints. By selecting different joint stiffness values, specific motions can be achieved. An optimisation-based framework was developed to automatically adjust the design of the structures to the dimensions of the user's hands. The optimisation goal was to follow the first postural synergy of the hand, which is known to encode a large amount of information regarding common patterns of human hands in daily life.We experimentally verified the created model, and obtained low error of the angular trajectory of the structure's joints, also observing low Cartesian position error of the elements. Then, a 3D-printed index finger (dimensioned following the average male user) was actuated by a structure, and the finger's angular trajectories were compared to the simulated ones. Low errors were obtained for the Metacarpophalangeal (MCP) and Proximal Interphalangeal (PIP) joints, and a moderate error for the Distal Interphalangeal (DIP) joint. Importantly, we observed that the stiffness of the structure could be modulated by controlling the tensions applied on the flexion and extension tendons: increasing the co-contraction of the tendons resulted in an increased stiffness at the joints. The fingertip forces exerted by the structure were evaluated, and reached the desired threshold corresponding to the values typically applied by therapists on low to moderately impaired stroke patients. Finally, in a qualitative manner, we demonstrated the successful grasping of a diverse set of objects typically used in rehabilitation settings.The first main contribution of this thesis is the demonstration of the potential that wearable robots have in aiding the upper limbs of impaired users in ADLs. This provides an important building block of evidence towards the use of robotic devices for assistance. The next main contribution is an underactuated mechanism for hand assistance. This is coupled with an automatic, model-based procedure that designs structures optimised to achieve the first postur...

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