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Biomimicry is a field of research that uses the functional and structural components of nature, at macroscopic and microscopic scales, to inspire solutions to problems in our industrial world. Soft robotics is an area of research that uses biomimicry, in this case, mimicking skeletal muscles (referred to in this field as “muscle-mimicking actuators”, to perform task of high difficulty, that can be operated in a harmlessly in different environments. One of the most recent advancements to develop from this field is the “Hydraulically amplified self-healing electrostatics (HASEL) actuator”. However, this method also brings many of the issues associated with the geometry of its design, especially with respect to the efficiency of the system. Though this system mimics the functionality of the skeletal muscle, there is room to adjust the existing electrostatic mechanisms, that distribute the locally produced force, to mimic the structure of the mechanism that distributes the force to the skeletal muscular, which is also locally produced. In this paper, we show that the current electrostatic parallel electrodes, as well as the zipping mechanisms, can be replaced with the sliding mechanism. This eliminates issues associated with compartmentalizing of the primary electrostatic force and the secondary hydraulic forces leading to a more efficient and controlled transmission electrostatic and hydrostatic forces to the load compared to current iterations and their geometric components.
Levi Tynan; Ganesh Naik; Gaetano D. Gargiulo; Upul Gunawardana. Implementation of the Biological Muscle Mechanism in HASEL Actuators to Leverage Electrohydraulic Principles and Create New Geometries. Actuators 2021, 10, 38 .
AMA StyleLevi Tynan, Ganesh Naik, Gaetano D. Gargiulo, Upul Gunawardana. Implementation of the Biological Muscle Mechanism in HASEL Actuators to Leverage Electrohydraulic Principles and Create New Geometries. Actuators. 2021; 10 (2):38.
Chicago/Turabian StyleLevi Tynan; Ganesh Naik; Gaetano D. Gargiulo; Upul Gunawardana. 2021. "Implementation of the Biological Muscle Mechanism in HASEL Actuators to Leverage Electrohydraulic Principles and Create New Geometries." Actuators 10, no. 2: 38.
Upper limb amputation is a condition that significantly restricts the amputees from performing their daily activities. The myoelectric prosthesis, using signals from residual stump muscles, is aimed at restoring the function of such lost limbs seamlessly. Unfortunately, the acquisition and use of such myosignals are cumbersome and complicated. Furthermore, once acquired, it usually requires heavy computational power to turn it into a user control signal. Its transition to a practical prosthesis solution is still being challenged by various factors particularly those related to the fact that each amputee has different mobility, muscle contraction forces, limb positional variations and electrode placements. Thus, a solution that can adapt or otherwise tailor itself to each individual is required for maximum utility across amputees. Modified machine learning schemes for pattern recognition have the potential to significantly reduce the factors (movement of users and contraction of the muscle) affecting the traditional electromyography (EMG)-pattern recognition methods. Although recent developments of intelligent pattern recognition techniques could discriminate multiple degrees of freedom with high-level accuracy, their efficiency level was less accessible and revealed in real-world (amputee) applications. This review paper examined the suitability of upper limb prosthesis (ULP) inventions in the healthcare sector from their technical control perspective. More focus was given to the review of real-world applications and the use of pattern recognition control on amputees. We first reviewed the overall structure of pattern recognition schemes for myo-control prosthetic systems and then discussed their real-time use on amputee upper limbs. Finally, we concluded the paper with a discussion of the existing challenges and future research recommendations.
Nawadita Parajuli; Neethu Sreenivasan; Paolo Bifulco; Mario Cesarelli; Sergio Savino; Vincenzo Niola; Daniele Esposito; Tara J. Hamilton; Ganesh R. Naik; Upul Gunawardana; Gaetano D. Gargiulo. Real-Time EMG Based Pattern Recognition Control for Hand Prostheses: A Review on Existing Methods, Challenges and Future Implementation. Sensors 2019, 19, 4596 .
AMA StyleNawadita Parajuli, Neethu Sreenivasan, Paolo Bifulco, Mario Cesarelli, Sergio Savino, Vincenzo Niola, Daniele Esposito, Tara J. Hamilton, Ganesh R. Naik, Upul Gunawardana, Gaetano D. Gargiulo. Real-Time EMG Based Pattern Recognition Control for Hand Prostheses: A Review on Existing Methods, Challenges and Future Implementation. Sensors. 2019; 19 (20):4596.
Chicago/Turabian StyleNawadita Parajuli; Neethu Sreenivasan; Paolo Bifulco; Mario Cesarelli; Sergio Savino; Vincenzo Niola; Daniele Esposito; Tara J. Hamilton; Ganesh R. Naik; Upul Gunawardana; Gaetano D. Gargiulo. 2019. "Real-Time EMG Based Pattern Recognition Control for Hand Prostheses: A Review on Existing Methods, Challenges and Future Implementation." Sensors 19, no. 20: 4596.
The Open-electroencephalography (EEG) framework is a popular platform to enable EEG measurements and general purposes Brain Computer Interface experimentations. However, the current platform is limited by the number of available channels and electrode compatibility. In this paper we present a fully configurable platform with up to 32 EEG channels and compatibility with virtually any kind of passive electrodes including textile, rubber and contactless electrodes. Together with the full hardware details, results and performance on a single volunteer participant (limited to alpha wave elicitation), we present the brain computer interface (BCI)2000 EEG source driver together with source code as well as the compiled (.exe). In addition, all the necessary device firmware, gerbers and bill of materials for the full reproducibility of the presented hardware is included. Furthermore, the end user can vary the dry-electrode reference circuitry, circuit bandwidth as well as sample rate to adapt the device to other generalized biopotential measurements. Although, not implemented in the tested prototype, the Biomedical Analogue to Digital Converter BIOADC naturally supports SPI communication for an additional 32 channels including the gain controller. In the appendix we describe the necessary modification to the presented hardware to enable this function.
Gaetano D. Gargiulo; Paolo Bifulco; Mario Cesarelli; Alistair McEwan; Armin Nikpour; Craig Jin; Upul Gunawardana; Neethu Sreenivasan; Andrew Wabnitz; Tara J. Hamilton. Fully Open-Access Passive Dry Electrodes BIOADC: Open-Electroencephalography (EEG) Re-Invented. Sensors 2019, 19, 772 .
AMA StyleGaetano D. Gargiulo, Paolo Bifulco, Mario Cesarelli, Alistair McEwan, Armin Nikpour, Craig Jin, Upul Gunawardana, Neethu Sreenivasan, Andrew Wabnitz, Tara J. Hamilton. Fully Open-Access Passive Dry Electrodes BIOADC: Open-Electroencephalography (EEG) Re-Invented. Sensors. 2019; 19 (4):772.
Chicago/Turabian StyleGaetano D. Gargiulo; Paolo Bifulco; Mario Cesarelli; Alistair McEwan; Armin Nikpour; Craig Jin; Upul Gunawardana; Neethu Sreenivasan; Andrew Wabnitz; Tara J. Hamilton. 2019. "Fully Open-Access Passive Dry Electrodes BIOADC: Open-Electroencephalography (EEG) Re-Invented." Sensors 19, no. 4: 772.
In developing countries, due to the high cost involved, amputees have limited access to prosthetic limbs. This constitutes a barrier for this people to live a normal life. To break this barrier, we are developing ultra-low-cost closed-loop myoactivated prostheses that are easy to maintain manufacture and that do not require electrodes in contact with the skin to work effectively. In this paper, we present the implementation for a simple but functional hand prosthesis. Our simple design consists of a low-cost embedded microcontroller (Arduino), a wearable stretch sensor (adapted from electroresistive bands normally used for “insulation of gaskets” against EM fields), to detect residual muscle contraction as direct muscle volumetric shifts and a handful of common, not critical electronic components. The physical prosthesis is a 3D printed claw-style two-fingered hand (PLA plastic) directly geared to an inexpensive servomotor. To make our design easier to maintain, the gears and mechanical parts can be crafted from recovered materials. To implement a closed loop, the amount of closure of prosthesis is fed back to the user via a second stretch sensor directly connected to claw under the form of haptic feedback. Our concept design comprised of all the parts has an overall cost below AUD 30 and can be easily scaled up to more complicated devices suitable for other uses, i.e., multiple individual fingers and wrist rotation.
Neethu Sreenivasan; Diego Felipe Ulloa Gutierrez; Paolo Bifulco; Mario Cesarelli; Upul Gunawardana; Gaetano D. Gargiulo. Towards Ultra Low-Cost Myoactivated Prostheses. BioMed Research International 2018, 2018, 1 -14.
AMA StyleNeethu Sreenivasan, Diego Felipe Ulloa Gutierrez, Paolo Bifulco, Mario Cesarelli, Upul Gunawardana, Gaetano D. Gargiulo. Towards Ultra Low-Cost Myoactivated Prostheses. BioMed Research International. 2018; 2018 ():1-14.
Chicago/Turabian StyleNeethu Sreenivasan; Diego Felipe Ulloa Gutierrez; Paolo Bifulco; Mario Cesarelli; Upul Gunawardana; Gaetano D. Gargiulo. 2018. "Towards Ultra Low-Cost Myoactivated Prostheses." BioMed Research International 2018, no. : 1-14.