• Journal of Biomedical Engineering Research
• /
• v.20 no.4
• /
• pp.451-459
• /
• 1999

During the electromyographic evaluation for the diagnosis of neuropathy, presence for site of lesion could be predicted by a detection of denervation potentials such as fibrillation potentials or positive sharp waves in a group of muscles. Unfortunately, since denervation potentials are distinguished by examiner's experience, it is possible to make mistake identifying endplate spikes as a denervation potential. The aim of the study was to extract parameters to make an algorithm for quantitative distinction between denervation potentials and endplate spikes. It will help to minimize the examiner's bias and to localize the site of lesion thus increase the reliability on EMG diagnosis. There types of signals, endplate spike, fibrillation potential and positive sharp wave were obtained from the EDB(extensor digitorum brevis) muscle using then neuropathic patients. Eight parameters such as duration, area, slope, peak-to-peak amplitude, positive peak negative peak amplitude, ratio of positive to negative peak amplitude, and number of phase were extracted and compared. As a results, peak-to-peak amplitude, positive peak amplitude, ratio of positive to negative peak amplitude showed statistically significant differences between endplate spikes and denervation potentials. It was concluded that those parameters could be used to establish an algorithm which will improve the accuracies in automated quantitative EMG diagnosis.

• Journal of Institute of Control, Robotics and Systems
• /
• v.21 no.6
• /
• pp.538-546
• /
• 2015

This paper describes an intelligent ankle assistive robot which provides assistive power to reduce ankle torque based on an analysis of ankle motion and muscle patterns during walking on level and sloped floors. The developed robot can assist ankle muscle power by driving an electric geared motor at the exact timing through the use of an accelerometer that detects gait phase and period, and a potentiometer to measure floor slope angle. A simple muscle assistive link mechanism is proposed to convert the motor torque into the foot assistive force. In particular, this mechanism doesn't restrain the wearer's ankle joint; hence, there is no danger of injury if the motor malfunctions. During walking, the link mechanism pushes down the top of the foot to assist the ankle torque, and it can also lift the foot by inversely driving the linkage, so this robot is useful for foot drop patients. The developed robot and control algorithm are experimentally verified through walking experiments and EMG (Electromyography) measurements.

• Journal of the Institute of Electronics Engineers of Korea SC
• /
• v.45 no.6
• /
• pp.132-140
• /
• 2008

Conventional rectal catheters which are used for the measurement of abdominal pressure can cause erroneous result affecting detrusor pressure, and the catheter itself is not comfortable to the patients. To reduce these problems, we invented a new method for measuring abdominal pressure in non invasive manner using surface electromyography (EMG) signals of the rectus abdominis muscle. Our results showed that the correlation coefficient and root mean square error (RMSE) between the measured abdominal pressures by the conventional rectal catheters and the estimated values by our proposed algorithm were $0.79{\pm}0.06$ and $0.10{\pm}0.07$, respectively. These findings suggest that the surface EMG of rectus abdominis muscle might be used indirectly for more convenient measurement of abdominal pressure on ambulatory urodynamic study.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.11 no.10
• /
• pp.3658-3665
• /
• 2010

As the population of elderly people and disabled people are increased, various demands for human welfare using robot system are raised. Especially autonomous rehabilitation system using robot could reduce the human effort while maintaining the its intrinsic efficacy. This study deals with mobile gait rehabilitation system which combined with BWS (Body Weight Support) for training of elderly and handicapped people who suffer the muscle force weakness of lower extremity. BWS which is designed by kinematic analysis of body lifting characteristics and walking guide system are integrated with main control system and wheeled platform. This mobile platform is operated by UCS (User Command System) and autonomous trajectory planning algorithm. Finally, through the EMG (Electromyography) signal measuring and its analysis for subject, performance and feasibility of developed system is verified.

• The Journal of Korea Robotics Society
• /
• v.12 no.2
• /
• pp.132-143
• /
• 2017

While working in an industrial environment which requires extended periods of upright posture; workers tend to develop muscle fatigue due to the constant load on lower-limb muscles. In addition, when working while bending knees; muscle fatigue of lower back and hamstrings is increased due to the abnormal posture. This can lead to damage of muscles, induce musculoskeletal disorders, and reduce long-term working efficiency. Recent medical studies have shown that long-term working in an upright posture can induce musculoskeletal disorders such as foot fatigue, edema, pain and varicose veins. Likewise, medical and rehabilitation expenses have grown due to the increase in musculoskeletal conditions suffered by workers. For this problem, we aim to develop a device that can reduce the physical fatigue on the lower limbs by supporting the weight of workers during the extended periods of upright and bending postures in the industrial environments. In this paper, we have designed and manufactured a wearable weight support system; with a user intention algorithm that the users can maintain various postures. For validation of the developed system, we measured the muscle activity of the users wearing the system with EMG sensors.

• Journal of Institute of Control, Robotics and Systems
• /
• v.21 no.5
• /
• pp.393-400
• /
• 2015

This paper describes the development of a chest-wearable robot that can efficiently perform self walking rehabilitation without a helper. The features of the developed robot are divided into three parts. First, as a mechanical characteristic, the conventional elbow crutch is attached at the forearm. However, the proposed robot is attached to the patient's chest, enabling them to feel free to use their hands and eliminate the burden of the arms. Second, as a characteristic of the driving algorithm, pressure sensors attached to the chest automatically perceive the patient's walking intention and move the robot-leg thereafter. Also, for safety, it stops operating when an obstacle is found in front of the patient by using ultrasonic sensors and generates a beeping sound. Finally, by using the scotch yoke mechanism, supporting legs are moved up and down using a rotary servo motor without excessive torque that is generated by large ground reaction forces. We showed that the developed robot can effectively perform self walking rehabilitation through walking experiments, and its performance was verified using Electromyograph (EMG) sensors.

• The Transactions of the Korean Institute of Electrical Engineers D
• /
• v.55 no.11
• /
• pp.502-510
• /
• 2006

In this paper, we describe implementation of a computer access device for the severly motor-disability. Many people with severe motor disabilities need an augmentative communication technology. Those who are totally paralyzed, or 'locked-in' cannot use conventional augmentative technologies, all of which require some measure of muscle control. The forehead is often the last site to suffer degradation in cases of severe disability and degenerative disease. For example, In ALS(Amyotrophic Lateral Sclerosis) and MD(Muscular dystrophy) the ocular motorneurons and ocular muscles are usually spared permitting at least gross eye movements, but not precise eye pointing. We use brain and body forehead bio-potentials in a novel way to generate multiple signals for computer control inputs. A bio-amplifier within this device separates the forehead signal into three frequency channels. The lowest channel is responsive to bio-potentials resulting from an eye motion, and second channel is the band pass derived between 0.5 and 45Hz, falling within the accepted Electroencephalographic(EEG) range. A digital processing station subdivides this region into eleven components frequency bands using FFT algorithm. The third channel is defined as an Electromyographic(EMG) signal. It responds to contractions of facial muscles and is well suited to discrete on/off switch closures, keyboard commands. These signals are transmitted to a PC that analyzes in a time series and a frequency region and discriminates user's intentions. That software graphically displays user's bio-potential signals in the real time, therefore user can see their own bio-potentials and control their physiological signals little by little after some training sessions. As a result, we confirmed the performance and availability of the developed system with experimental user's bio-potentials.

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.41 no.8
• /
• pp.691-701
• /
• 2017

The barbell squat is a fundamental physical exercise for strengthening the lower body and core muscles. It is an integral part of training and conditioning programs in sports, rehabilitation, and fitness. In this paper, we proposed a virtual test framework for squat exercises using a Smith machine to simulate joint torques and muscle forces, based on an integrated product-human model and motion synthesis algorithms. We built a muscular skeletal human model with boundary conditions modeling the interactions between the human body and a machine or the ground. To validate the model, EMG, external forces, and squat motions were captured through physical experiments by varying the foot position. A regression-based motion synthesis algorithm was developed based on the captured squat motions to generate a new motion for a given foot position. The proposed approach is expected to reduce the need for physical experiments in the development of training programs.

• Journal of Biomedical Engineering Research
• /
• v.12 no.1
• /
• pp.1-7
• /
• 1991

This paper describes and discusses the employment of HMG pattern analysis to provide upper-motor-neuron paraplegics with patient-responsive control of FES ( functional electrical stimulation) for the purpose of walker-supported walking. The use of above-lesion EMG signals as a solution to the control problem is considered. The AR(autoregressive)parameters are identified by time-varying nonstationary Kalman filler algorithm using DSP chip and classified by fuzzy theory. The control and stimuli part of the below-lesion are based on micro-processor(8031). The designed stimulator is a 4-channel version. The experiments described above have only attempted to discriminate between standing function and sit-down function A further advantge of the this system Is applied for motor rehabilitation of social readaption of paralyzed humans.

• Proceedings of the KOSOMBE Conference
• /
• v.1997 no.05
• /
• pp.430-433
• /
• 1997

We present the preliminary algorithms for automatic sleep scoring. According to the Rechtschaffen & Kales[3]'s critera, we developed six events detectors and eight parameters which contain the background information of signals, such as EEG, EMG, EOG. With the calculated parameters, we scored each epoch by IF-THEN rules, ANFIS for REM preiods, and finally Neural Network for unobvious epochs. The typical point of this algorithm is that the epoch which had good data sets were calculated in the first stage, and unobvious epochs were postponed until the final stage. After staging the good epochs, we classified unobvious epochs by the dominant stage of previous and posterior epochs.