Estimation of handgrip force using frequency-band technique during fatiguing muscle contraction.

In this paper, we propose a force estimation model to compute the handgrip force from SEMG signal during fatiguing muscle contraction tasks. The appropriate frequency range was analyzed using various combinations of a wavelet scale, and the highest accuracy was achieved at a range from 242 to 365 Hz. After that, eight healthy individuals performed a series of static (70%, 50%, 30%, and 20% MVC) and dynamic (0-50% MVC) muscle contraction tasks to evaluate the performance of this technique in comparison with that of former method using the Root Mean Square of the SEMG signal. Both methods had comparable results at the beginning of the experiments, before the onset of muscle fatigue. However, differences were clearly observed as the degree of muscle fatigue began to increase toward the endurance time. Under this condition, the estimated handgrip force using the proposed method improved from 17% to 134% for static contraction tasks and 40% for dynamic contraction tasks. This study overcomes the limitation of the former method during fatiguing muscle contraction tasks and, therefore, unlocks the potential of utilizing the SEMG signal as an indirect force estimation method for various applications.

Quantitative estimation of muscle fatigue using surface electromyography during static muscle contraction.

Muscle fatigue is commonly associated with the musculoskeletal disorder problem. Previously, various techniques were proposed to index the muscle fatigue from electromyography signal. However, quantitative measurement is still difficult to achieve. This study aimed at proposing a method to estimate the degree of muscle fatigue quantitatively. A fatigue model was first constructed using handgrip dynamometer by conducting a series of static contraction tasks. Then the degree muscle fatigue can be estimated from electromyography signal with reasonable accuracy. The error of the estimated muscle fatigue was less than 10% MVC and no significant difference was found between the estimated value and the one measured using force sensor. Although the results were promising, there were still some limitations that need to be overcome in future study.

Simultaneous measurement of force and muscle fatigue using frequency-band wavelet analysis.

Static and dynamic handgrip experiments are performed in order to evaluate the effectiveness of utilizing frequency-band wavelet analysis in measuring force and muscle fatigue simultaneously. SEMG signals are recorded from flexor muscle and analyzed using continuous wavelet transform (CWT). The wavelet coefficients are grouped into high frequency (65Hz - 350Hz) and low frequency (5Hz - 45Hz) band. A significant correlation is discovered between amplitude of high frequency band and force level. On the other hand, the amplitude of low frequency band is associated with muscle fatigue. These results have an important implication for estimating force and muscle fatigue simultaneously especially during dynamic contraction.

A fMRI study of the cross-modal interaction in the brain with an adaptable EMG prosthetic hand with biofeedback.

Mutual adaptation between man and machine is necessary for the development of more efficient devices that allows easy adaptation. The interaction with intelligent machines involves adaptation processes from both the user and the machine. The human body has the ability to change its body schema to include external tools in it, using this fact we proposed the design of intelligent machines with biofeedback to the user, permitting in this way, development of subconscious control of external devices. We propose the case of an EMG prosthetic hand with biofeedback to study the adaptation process between man-machine. Our system includes an EMG classification system to acquire the intended movement from the user. We use electrical stimulation as a provider of tactile feedback, to interact with the human body. We use a functional Magnetic Resonance Image study while using the prosthetic device while receiving biofeedback to measure the activation levels in the amputee's brain.

New shape memory alloy actuator: design and application in the prosthetic hand.

This paper describes a new SMA actuator design and its application in the prosthetic hand replacing conventional servo motors which are bulky and noisy in nature. Two one-way memory SMA wires are used in the development of the actuator. The proposed actuator consists of two 0.3mm in diameter SMA wires inserted from both ends of a stainless outer tube which functions as a guide and simultaneously a heat sink for the dissipation of heat from the SMA. These wires meet at the centre of the stainless tube where an electrode is placed. There are 2 other electrodes, each located at the end of the outer tube. These electrodes are the points where current is passed through each of the SMA wire asynchronously. In order to actuate a degree of freedom (DOF) of a robotic finger, 2 actuators are used each for the flexion and extension actions respectively. A high voltage PWM signal of very short intervals is used in actuation to avoid excessive heat build-up in the SMA due to long unnecessary heating.

Study on the Effects of Electrical Stimulation on the Pattern Recognition for an EMG Prosthetic Application.

The need of biofeedback in Man-Machine interfaces is of vital importance for the development of subconscious control with external devices. In order to obtain extended proprioception, in other words, to include the external devices into the body schema, we need to provide with more feedback channels to the human body. In this study we look into the use of electrical stimulation as biofeedback and its effects over the pattern recognition process from the EMG signals that controls the hand movements.