A Comparison of Surface and Internally Measured Myoelectric Signals for use in Prosthetic Control

نویسندگان

  • L. Hargrove
  • B. Hudgins
  • K. Englehart
چکیده

INTRODUCTION The surface myoelectric signal (MES) has proven to be an effective control input for powered prostheses. Pattern recognition based controllers use multi-channel surface MES as inputs to discriminate between the desired classes of limb activation. There are two major methods which may be pursued to increase the accuracy of the controller: 1) use signal processing to extract more information from the input signals; or 2) provide more informative raw signals to the controller. As a result of recent technological advances, it is reasonable to assume that there will soon be implantable myoelectric sensors which will enable the internal MES to be used as inputs to controllers [1]. An internal MES measurement should have less muscular crosstalk allowing for more independent control sites. However, it remains unclear if this benefit outweighs the loss of the more global information contained in the surface MES. This study compares the classification accuracy of several pattern based myoelectric controllers which use information extracted from surface MES to the same controllers which use information extracted from finewire intramuscular MES.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

sEMG Sensor Using Polypyrrole-Coated Nonwoven Fabric Sheet for Practical Control of Prosthetic Hand

One of the greatest challenges of using a myoelectric prosthetic hand in daily life is to conveniently measure stable myoelectric signals. This study proposes a novel surface electromyography (sEMG) sensor using polypyrrole-coated nonwoven fabric sheet as electrodes (PPy electrodes) to allow people with disabilities to control prosthetic limbs. The PPy electrodes are sewn on an elastic band to ...

متن کامل

Adaptive Switching in Practice: Improving Myoelectric Prosthesis Performance through Reinforcement Learning

Myoelectrically controlled prostheses are a class of assistive device that use electrical signals generated by muscle activation. These electromyographic (EMG) signals are used to control one or more electromechanical actuators that move prosthetic joints. Myoelectric control signals are typically measured with electrodes on the surface of the skin, with one pair of electrodes over each muscle ...

متن کامل

Prediction of Above-elbow Motions in Amputees, based on Electromyographic(EMG) Signals, Using Nonlinear Autoregressive Exogenous (NARX) Model

Introduction In order to improve the quality of life of amputees, biomechatronic researchers and biomedical engineers have been trying to use a combination of various techniques to provide suitable rehabilitation systems. Diverse biomedical signals, acquired from a specialized organ or cell system, e.g., the nervous system, are the driving force for the whole system. Electromyography(EMG), as a...

متن کامل

Implantable Myoelectric Sensors (IMES)

We are developing a multi-channel/multifunction prosthetic hand/arm controller system capable of receiving and processing signals from up to sixteen Implanted MyoElectric Sensors (IMES). The appeal of implanted sensors for myoelectric control is that EMG signals can be measured at their source providing relatively cross-talk free signals that can be treated as independent control sites. Therefo...

متن کامل

Myoelectric control of prosthetic hands: state-of-the-art review

Myoelectric signals (MES) have been used in various applications, in particular, for identification of user intention to potentially control assistive devices for amputees, orthotic devices, and exoskeleton in order to augment capability of the user. MES are also used to estimate force and, hence, torque to actuate the assistive device. The application of MES is not limited to assistive devices...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2005