AIMC Topic: Biomechanical Phenomena

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Model-free motion control of continuum robots based on a zeroing neurodynamic approach.

Neural networks : the official journal of the International Neural Network Society
As a result of inherent flexibility and structural compliance, continuum robots have great potential in practical applications and are attracting more and more attentions. However, these characteristics make it difficult to acquire the accurate kinem...

Improving data acquisition speed and accuracy in sport using neural networks.

Journal of sports sciences
Video analysis is used in sport to derive kinematic variables of interest but often relies on time-consuming tracking operations. The purpose of this study was to determine speed, accuracy and reliability of 2D body landmark digitisation by a neural ...

Prediction of ground reaction force and joint moments based on optical motion capture data during gait.

Medical engineering & physics
The standard camera- and force plate-based set-up for motion analysis suffers from the disadvantage of being limited to laboratory settings. Since adaptive algorithms are able to learn the connection between known inputs and outputs and generalise th...

Customised Selection of the Haptic Design in C-Loop Intraocular Lenses Based on Deep Learning.

Annals of biomedical engineering
In order to increase the probability of having a successful cataract post-surgery, the customisation of the haptic design of the intraocular lens (IOL) according to the characteristics of the patient is recommended. In this study, we present two pred...

Spring-loaded inverted pendulum modeling improves neural network estimation of ground reaction forces.

Journal of biomechanics
Inertial-measurement-unit (IMU)-based wearable gait-monitoring systems provide kinematic information but kinetic information, such as ground reaction force (GRF) are often needed to assess gait symmetry and joint loading. Recent studies have reported...

Kinematic parameters obtained with the ArmeoSpring for upper-limb assessment after stroke: a reliability and learning effect study for guiding parameter use.

Journal of neuroengineering and rehabilitation
BACKGROUND: After stroke, kinematic measures obtained with non-robotic and robotic devices are highly recommended to precisely quantify the sensorimotor impairments of the upper-extremity and select the most relevant therapeutic strategies. Although ...

Biomechanical monitoring and machine learning for the detection of lying postures.

Clinical biomechanics (Bristol, Avon)
BACKGROUND: Pressure mapping technology has been adapted to monitor over prolonged periods to evaluate pressure ulcer risk in individuals during extended lying postures. However, temporal pressure distribution signals are not currently used to identi...

Automatic Grading of Stroke Symptoms for Rapid Assessment Using Optimized Machine Learning and 4-Limb Kinematics: Clinical Validation Study.

Journal of medical Internet research
BACKGROUND: Subtle abnormal motor signs are indications of serious neurological diseases. Although neurological deficits require fast initiation of treatment in a restricted time, it is difficult for nonspecialists to detect and objectively assess th...

Rapid two-anchor crawling from a milliscale prismatic-push-pull (3P) robot.

Bioinspiration & biomimetics
Many crawling organisms such as caterpillars and worms use a method of movement in which two or more anchor points alternately push and pull the body forward at a constant frequency. In this paper we present a milliscale push-pull robot which is capa...

Kinematic Calibration of a Parallel 2-UPS/RRR Ankle Rehabilitation Robot.

Journal of healthcare engineering
In order to better perform rehabilitation training on the ankle joint complex in the direction of dorsiflexion/plantarflexion and inversion/eversion, especially when performing the isokinetic muscle strength exercise, we need to calibrate the kinemat...