相关论文: Estimating Continuous Muscle Fatigue For Multi-Mus…
Investigating the impact of fatigue on human physiological function and motor behavior is crucial for developing biomechanics and medical applications aimed at mitigating fatigue, reducing injury risk, and creating sophisticated ergonomic…
Natural gestures are crucial for mid-air interaction, but predicting and managing muscle fatigue is challenging. Existing torque-based models are limited in their ability to model above-shoulder interactions and to account for fatigue…
Voluntary human motion is the product of muscle activity that results from upstream motion planning of the motor cortical areas. We show that muscle activity can be artificially generated based on motion features such as position, velocity,…
Injuries to the lower extremity joints are often debilitating, particularly for professional athletes. Understanding the onset of stressful conditions on these joints is therefore important in order to ensure prevention of injuries as well…
Muscle fatigue is usually defined as a decrease in the ability to produce force. The surface electromyography (sEMG) signals have been widely used to provide information about muscle activities including detecting muscle fatigue by various…
Background The development of a simulation model of full body reaching tasks that can predict endeffector trajectories and joint excursions consistent with experimental data is a non-trivial task. Because of the kinematic redundancy…
The existing computational models used to estimate motion sickness are incapable of describing the fact that the predictability of motion patterns affects motion sickness. Therefore, the present study proposes a computational model to…
Mental fatigue is a leading cause of motor vehicle accidents, medical errors, loss of workplace productivity, and student disengagements in e-learning environment. Development of sensors and systems that can reliably track mental fatigue…
Motor control is a set of time-varying muscle excitations which generate desired motions for a biomechanical system. Muscle excitations cannot be directly measured from live subjects. An alternative approach is to estimate muscle…
In this paper, we present a simulation and control framework for generating biomechanically plausible motion for muscle-actuated characters. We incorporate a fatigue dynamics model, the 3CC-r model, into the widely-adopted Hill-type muscle…
Biomechanics and human movement research often involves measuring multiple kinematic or kinetic variables regularly throughout a movement, yielding data that present as smooth, multivariate, time-varying curves and are naturally amenable to…
Multiple sclerosis is a disease that affects the brain and spinal cord, it can lead to severe disability and has no known cure. The majority of prior work in machine learning for multiple sclerosis has been centered around using Magnetic…
Virtual human techniques have been used a lot in industrial design in order to consider human factors and ergonomics as early as possible. The physical status (the physical capacity of virtual human) has been mostly treated as invariable in…
Purpose: From the myofibrils to the whole muscle scale, muscle micro-constituents exhibit passive and active mechanical properties, potentially coupled to electrical, chemical, and thermal properties. Experimental characterization of some…
Functional magnetic resonance imaging (fMRI) is a neuroimaging technique that records neural activations in the brain by capturing the blood oxygen level in different regions based on the task performed by a subject. Given fMRI data, the…
Nowadays, there are many fatigue detection methods and the majority of them are tracking eye in real-time using one or two cameras to detect the physical responses in eyes. It is indicated that the responses in eyes have high relativity…
Practical determination of physical recovery after intense exercise is a challenging topic that must include mechanical aspects as well as cognitive ones because most of physical sport activities, as well as professional activities…
Background. Wearable accelerometry devices allow collection of high-density activity data in large epidemiological studies both in-the-lab as well as in-the-wild (free-living). Such data can be used to detect and identify periods of…
In recent years, single modality based gait recognition has been extensively explored in the analysis of medical images or other sensory data, and it is recognised that each of the established approaches has different strengths and…
Multiple sclerosis (MS) is a progressive inflammatory and neurodegenerative disease of the central nervous system affecting over 2.5 million people globally. In-clinic six-minute walk test (6MWT) is a widely used objective measure to…