Support Vector Machines
July 1, 2023FDA Updates – July 2023
July 1, 20232008
In 2008, researchers explored robotic systems that could mimic human movements, agility, stability, and precision...
Robotics of human movements:
In 2008 was conducted a deep investigation of robotic systems that can replicate human movements in terms of agility, stability, and precision. Their goal was to achieve a successful robotic system integration in human surroundings.
The primary objective was to create robotic systems that were as near to human movement as possible. They must design systems with similar kinematics and agility: the ability to react and move quickly while exerting strong forces and handling high-energy collisions. These characteristics are strongly related to muscle function, as they have a high energy density while being flexible, allowing vast amounts of energy to be stored in a short period of time. For them, it was also crucial to keep the angle of tendon deflection as narrow as possible to lessen the coupling between wrist and finger movements, which reduces friction. The stiffness of a joint during operation, trajectory planning during voluntary movement, and the mechanics involved.(1)
Robotics of human movements:
In 2008 was conducted a deep investigation of robotic systems that can replicate human movements in terms of agility, stability, and precision. Their goal was to achieve a successful robotic system integration in human surroundings.
The primary objective was to create robotic systems that were as near to human movement as possible. They must design systems with similar kinematics and agility: the ability to react and move quickly while exerting strong forces and handling high-energy collisions.
These characteristics are strongly related to muscle function, as they have a high energy density while being flexible, allowing vast amounts of energy to be stored in a short period of time. For them, it was also crucial to keep the angle of tendon deflection as narrow as possible to lessen the coupling between wrist and finger movements, which reduces friction. The stiffness of a joint during operation, trajectory planning during voluntary movement, and the mechanics involved.(1)
On the other hand, they wanted to create a biologically inspired touch sensor to allow manipulation capabilities to compete with those of humans. Also, to be able to grasp small and structured objects and recognize the applied force for each type of grasp. The system would implement micro-movements consisting of brief bursts of muscular activation that occur in unison. Finally, they would want to design an integrated hand-arm system.
The purpose of the routes for developing the next generation of robotics is to assist or replace people in dangerous circumstances. As well, a new field of application for rehabilitation and prosthetics opens. Patients with paralyzed extremities or replanted hands must retrain how to use their muscles to move (control) their hands and arms after a stroke. Aside from aesthetic hands, they also have an active hand line.(1)
Complexity and spectral analysis of the heart rate variability dynamics for distant prediction of paroxysmal atrial fibrillation with artificial intelligence methods
Atrial fibrillation is a common abnormal heart rhythm found in clinical practice and is associated risk of stroke and mortality. While artificial intelligence was still in development in 2008, a research study was conducted to predict by spectral analysis the paroxysmal atrial fibrillation (PAF) by artificial intelligence. 51 subjects with PAF were analyzed before the onset PAF episode and at least 45 min distant from the PAF event. Artificial neural network classification was implemented in predicting PAF and heart rate variability (HRV).(2)
Artificial neural network (ANN) mimics the brain’s neurons by linking many simple processors, named artificial neurons. An ANN program was trained to capture differences in the subjects’ spectral and complex heart rhythms. The 85 HRV segments immediately before PAF onset and 67 HRV segments distant from the PAF were featured and computed from a database. Using Physionet database were able to predict PAF onset on a database provided in 13 patients 62+ 21 min in advance.(2)
Complexity and spectral analysis of the heart rate variability dynamics for distant prediction of paroxysmal atrial fibrillation with artificial intelligence methods
Atrial fibrillation is a common abnormal heart rhythm found in clinical practice and is associated risk of stroke and mortality. While artificial intelligence was still in development in 2008, a research study was conducted to predict by spectral analysis the paroxysmal atrial fibrillation (PAF) by artificial intelligence.
51 subjects with PAF were analyzed before the onset PAF episode and at least 45 min distant from the PAF event. Artificial neural network classification was implemented in predicting PAF and heart rate variability (HRV).
Artificial neural network (ANN) mimics the brain’s neurons by linking many simple processors, named artificial neurons. An ANN program was trained to capture differences in the subjects’ spectral and complex heart rhythms. The 85 HRV segments immediately before PAF onset and 67 HRV segments distant from the PAF were featured and computed from a database. Using Physionet database were able to predict PAF onset on a database provided in 13 patients 62+ 21 min in advance.(2)