Dataset Information

Design of a Multi-Control Objective Rescue Mechanical Ventilation System (Linshomator).

ABSTRACT: In recent years, the need for a low-cost emergency ventilation system has increased unprecedentedly. Mechanical ventilation systems are widely used to cater to sudden oxygen demands, low breathing rates, and critical conditions during bradycardia and tachycardia. In this research, a new design of mechanical ventilation system synced with the tidal volume requirements of the patient using a piezoelectric belt has been proposed. The device proposed has various modes of ventilation-ACV (assisted controlled ventilation), SIMV (synchronized intermittent mandatory ventilation), and NIV (non-invasive ventilation), depending on the patient's requirements. A digital interface or user-friendly software has also been developed to help medical professionals easily monitor a patient's medical conditions. Finally, the automation that controls the ventilation mechanism of the device has been tested and validated with a conventional ventilator, and it has been found that the accuracy of the device in terms of delivering the exact quantity of air into the patient according to his requirements has been improved significantly. Further, the comparative study of the experimental data indicated that 5-10% error in detecting inhale and exhale attempt of a patient was detected with the conventional ventilator.

SUBMITTER: Roy A

PROVIDER: S-EPMC8757753 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Background: Interlimb neural coupling implies that arm swing should be included during gait training to improve rehabilitation outcomes. We previously developed several systems for production of walking with arm swing, but the reaction forces on the foot sole during usage of the systems were not satisfactory and there was potential to improve control system performance. This work aimed to design and technically evaluate a novel system for producing walking with synchronised arm and leg movement and with dynamic force loading on the foot soles. Methods: The robotic system included a passive curved treadmill and a trunk frame, upon which the rigs for the upper and lower limbs were mounted. Ten actuators and servocontrollers with EtherCAT communication protocol controlled the bilateral shoulder, elbow, hip, knee and ankle joints. Impedance control algorithms were developed and ran in an industrial PC. Flexible pressure sensors recorded the plantar forces on the foot soles. The criteria of implementation and responsiveness were used to formally evaluate the technical feasibility of the system. Results: Using impedance algorithms, the system produced synchronous walking with arm swing on the curved treadmill, with mean RMS angular tracking error <2° in the 10 joint profiles. The foot trajectories relative to the hip presented similar shapes to those during normal gait, with mean RMS displacement error <1.5 cm. A force pattern that started at the heel and finished at the forefoot was observed during walking using the system, which was similar to the pattern from overground walking. Conclusion: The robotic system produced walking-like kinematics in the 10 joints and in the foot trajectories. Integrated with the curved treadmill, the system also produced walking-like force patterns on the foot soles. The system is considered feasible as far as implementation and responsiveness are concerned. Future work will focus on improvement of the mechanical system for future clinical application.

Project description:BackgroundRNAs are attractive molecules as the biological parts for synthetic biology. In particular, the ability of conformational changes, which can be encoded in designer RNAs, enables us to create multistable molecular switches that function in biological circuits. Although various algorithms for designing such RNA switches have been proposed, the previous algorithms optimize the RNA sequences against the weighted sum of objective functions, where empirical weights among objective functions are used. In addition, an RNA design algorithm for multiple pseudoknot targets is currently not available.ResultsWe developed a novel computational tool for automatically designing RNA sequences which fold into multiple target secondary structures. Our algorithm designs RNA sequences based on multi-objective genetic algorithm, by which we can explore the RNA sequences having good objective function values without empirical weight parameters among the objective functions. Our algorithm has great flexibility by virtue of this weight-free nature. We benchmarked our multi-target RNA design algorithm with the datasets of two, three, and four target structures and found that our algorithm shows better or comparable design performances compared with the previous algorithms, RNAdesign and Frnakenstein. In addition to the benchmarks with pseudoknot-free datasets, we benchmarked MODENA with two-target pseudoknot datasets and found that MODENA can design the RNAs which have the target pseudoknotted secondary structures whose free energies are close to the lowest free energy. Moreover, we applied our algorithm to a ribozyme-based ON-switch which takes a ribozyme-inactive secondary structure when the theophylline aptamer structure is assumed.ConclusionsCurrently, MODENA is the only RNA design software which can be applied to multiple pseudoknot targets. Successful design results for the multiple targets and an RNA device indicate usefulness of our multi-objective RNA design algorithm.

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Design of a Multi-Control Objective Rescue Mechanical Ventilation System (Linshomator).

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