This study proposes a real-time joint angle estimation method of human elbow by processing a biomedical signal of surface synergistic EMG (electromyogram) measured between biceps brachii and triceps brachii simultaneously. Actually, the EMG is known as a non-stationary signal, but the authors assume that it is quasi-stationary because a physical or physiological system has limitations in the rate at which it can change its characteristics. Based on the assumption, a pre-processing method to obtain pre-angle values from the raw synergistic EMG signal is firstly suggested, and then a method to estimate the joint angle through normalisation when there are external loads is discussed. In addition, an optimisation method to minimise the error between the normalised angle and real joint angle is proposed. Finally, the authors show the effectiveness of the suggested algorithm through experimental results.

Did you like this research project?

To get this research project Guidelines, Training and Code... Click Here

PROJECT TITLE : Learning Compact Features for Human Activity Recognition Via Probabilistic First-Take-All ABSTRACT: With the rise in popularity of mobile sensor technologies, smart wearable devices provide a once-in-a-lifetime
PROJECT TITLE : On the Personalization of Classification Models for Human Activity Recognition ABSTRACT: A considerable portion of recent literature on machine learning approaches has focused on automatic recognition of people's
PROJECT TITLE : Outlier Detection in Wearable Sensor Data for Human Activity Recognition (HAR) Based on DRNNs ABSTRACT: Wearable sensors enable the development of tailored apps by providing a user-friendly and non-intrusive approach
PROJECT TITLE : Kinetic Modeling of Hyperpolarized Carbon-13 Pyruvate Metabolism in the Human Brain ABSTRACT: Modeling pyruvate to lactate conversion in vivo is essential to understanding abnormal cancer metabolism that exhibits
PROJECT TITLE :  A Structure-Based Human Facial Age Estimation Framework under a Constrained Condition ABSTRACT: In computer vision and pattern recognition, developing an automatic age estimation approach for human faces continues

Ready to Complete Your Academic MTech Project Work In Affordable Price ?

Project Enquiry