Tatsuhiro Nakamura

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.

Brain-machine interface to control a prosthetic arm with monkey ECoGs during periodic movements

Brain–machine interfaces (BMIs) are promising technologies for rehabilitation of upper limb functions in patients with severe paralysis. We previously developed a BMI prosthetic arm for a monkey implanted with electrocorticography (ECoG) electrodes, and trained it in a reaching task. The stability of the BMI prevented incorrect movements due to misclassification of ECoG patterns. As a trade-off for the stability, however, the latency (the time gap between the monkeys actual motion and the prosthetic arm movement) was about 200 ms. Therefore, in this study, we aimed to improve the response time of the BMI prosthetic arm. We focused on the generation of a trigger event by decoding muscle activity in order to predict integrated electromyograms (iEMGs) from the ECoGs. We verified the achievability of our method by conducting a performance test of the proposed method with actual achieved iEMGs instead of predicted iEMGs. Our results confirmed that the proposed method with predicted iEMGs eliminated the time delay. In addition, we found that motor intention is better reflected by muscle activity estimated from brain activity rather than actual muscle activity. Therefore, we propose that using predicted iEMGs to guide prosthetic arm movement results in minimal delay and excellent performance.

Control strategy for a myoelectric hand: Measuring acceptable time delay in human intention discrimination

In order to enhance controllability of a myoelectric hand, we focus on a gap between the time when a human intends to move a myoelectric hand and the time when the hand actually moves (i.e., time delay). Normally, the myoelectric hand users dislike the time delay because it makes them feel uncomfortable. However, the users learn the time delay within some time ranges and, eventually, get feel comfortable to operate the hand. Thus, we assume, if we reveal the acceptable delay time (i.e., the time the users accept the gap with their learning ability), we can provide more time in a human intention discrimination process, and enhance its success rate. Therefore, we developed a mobile myoelectric hand system with an embedded linux computer, and conducted a ball catch experiment: we investigate the acceptable delay time by adding the delay time (i.e., 120[ms], 170[ms], 220[ms], 270[ms], 320[ms]) into the human intention discrimination process. As a result, we confirmed that the max accept delay time was approximately 170 [ms] that achieves 61% success rate.

Development and evaluation of simplified EMG prosthetic hands

Millions of physical disabilities, who have lost a hand or both hands, are in need of prosthetic hands not only for decoration but also for the functions to help them with basic daily activities. Although EMG prosthetic hands are being extensively studied to satisfy this need, most of them are too expensive to be economically available, difficult to operate and maintain by a user him/herself, or over heavy for longtime wearing. The aim of this study is therefore to develop a simplified EMG prosthetic hand (sim-EMGPH) to solve these problems. The sim-EMGPH consists of five parts: a lightweight robotic hand with two motors to realize the most frequent hand activities, a highly stretchable cosmetic glove with little load on the motors, an EMG measurement system including sensors with high wearability made of soft conductive materials, a controller implemented by a 32-bit microprocessor which performs EMG signal processing, pattern recognition, and motor control, and a human-friendly tablet interface for the user to operate the sim-EMGPH by him/herself. We manufactured three sim-EMGPHs for three subjects: two with congenital upper limb deficiency and one with upper limb amputation. Free task experiments showed that the subjects could operate the sim-EMGPHs by themselves to perform basic activities of daily living. Limitations revealed and improvement plans are also discussed in this paper.

Walking assistance by functional clothes with highly elastic fabric

We proposed a novel approach to walking assistance by using functional clothes with highly elastic fabric. This strategy can achieve walking assistance without external forces generated by an actuator. In order to examine the effectiveness of the proposed approach, we produced a functional girdle and assessed the extent to which it assisted the hip flexor muscles. We confirmed that the load on the hip flexor muscles decreased during hip flexion while subjects wore the functional clothes.

Development of mobile controller for EMG prosthetic hand with tactile feedback

In this paper, we introduce a mobile controller for a five-fingered myoelectric prosthetic hand with tactile feedback. When constructing a system for use in daily life, the following design requirements should be satisfied: 1) limitations on the total weight of the system; 2) sufficient degrees of freedom of motion; and 3) sufficient sensory feedback information for the result of the interaction with circumstance. At first, we limited the degrees of operations for the wrist motion and switching operations, because too many degrees of freedom cause an increase in overall weight. Next, we constructed the controller, which has a suitable processing performance with mobile PC and microcomputer. Moreover, for lightweight tactile feedback system, we employed the technique of Phantom Sensation (PS) with only two electrodes. Finally, we discuss the appropriate parameter combinations for PS.

Evaluation of frequency band technique in estimating muscle fatigue during dynamic contraction task

Long-time exposure to repetitive or monotonous work is associated with increased risk for musculoskeletal disorders that are due to muscle fatigue. Previously, researchers reported that muscle fatigue can be estimated using a low-frequency band of an SEMG signal. However, these studies were performed exclusively during static contraction tasks. The objective of the present study was to evaluate and determine the frequency range for a low-frequency band. In addition, the performance during dynamic contraction tasks was analyzed. A group of healthy university students (8 males) was recruited, and endurance handgrip tasks were conducted. SEMG signals were captured from the forearm muscle. The frequency range for the low-frequency band was redefined as 5 – 40Hz. The results from a dynamic contraction task indicated that a low-frequency band is a reliable method for indexing muscle fatigue from SEMG signals.

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.

Structure design for a Two-DoF myoelectric prosthetic hand to realize basic hand functions in ADLs

Prosthetic hands are desired by those who have lost a hand or both hands not only for decoration but also for the functions to help them with their activities of daily living (ADL). Prosthetic robotic hands that are developed to fully realize the function of a human hand are usually too expensive to be economically available, difficult to operate and maintain, or over heavy for longtime wearing. The aim of this study is therefore to develop a simplified prosthetic hand (sim-PH), which is to be controlled by myoelectric signals from the user, to realize the most important grasp motions in ADL by trading off the cost and performance. This paper reports the structure design of a two-DoF sim-PH with two motors to drive the CM joint of the thumb and the interlocked MP joints of the other four fingers. In order to optimize the structure, the model of the sim-PH was proposed based on which 7 sim-PHs with different structural parameters were manufactured and tested in a pick-and-place experiment. Correspondence analysis of the experimental results clarified the relationship between the hand functions and the shapes of fingers.

The Relationship Between Changes in Amplitude and Instantaneous Mean Frequency at Low and High Frequency Bands During Dynamic Contraction

Surface Electromyography (SEMG) analysis of dynamic contraction is becoming more important to understand the muscle condition in real life activities. The objective of the study is to discover the relationship between the changes of amplitude and frequency at high and low frequency bands. Continuous Wavelet Transform (CWT) is utilized in order to process the SEMG data in both time and frequency domain. The result shows the potential to estimate the force level by analyzing the amplitude of high frequency band. However the influence of muscle fatigue and force variation should be identified during dynamic contraction. The proposed method provides an alternative solution for analyzing SEMG signals in different perspective.