ABSTRACT
Objective To explore the effectiveness of a myoelectricity-driven hand robot on the recovery of hand motor function early after a stroke.Methods Thirty stroke survivors were randomly assigned to either a control group (n=15) or an experimental group (n =15).Both groups received routine rehabilitation exercises,while the experimental group additionally received hand training using a robotic hand exoskeleton.Before and after 4 weeks of treatment,the motor function of the wrist and fingers in both groups were measured using the Fugl-Meyer assessment.Spasticity in the index,middle,ring and little fingers was quantified using the modified Ashworth scale.The muscle force of the fourth finger,thumb and all of the fingers during maximum voluntary extension and flexion were recorded using the robot's surface electromyography system.Results Significant increases in the average Fugl-Meyer scores in both groups were observed after 4 weeks of treatment,but the experimental group's average score was by then significantly higher than that of the control group.The experimental group's average Ashworth score and the average sEMG amplitudes were also significantly better than those of the control group.Conclusion Supplementing routine rehabilitation exercises with a hand robot can improve hand motor function and muscle force significantly,as well as relieving hand spasticity early after a stroke.
ABSTRACT
Power line interference in the surrounding environment could usually introduce many difficulties when collecting and analyzing physiological signals. Since power line interference is usually several orders of amplitude larger than the physiological electrical signals, methods of suppressing power line interference should be considered during the signal acquisition. Many studies used a hardware or software band-stop filter to suppress power line interference but it could easily cause attenuations and distortions to the signal of interest. In this study, two kinds of methods that used different signals to drive the shields of the electrodes were proposed to reduce the impacts of power line interference. Three channels of two physiological signals (ECG and EMG) were simultaneously collected when the electrodes were not shielded (No-Shield), shielded by ground signals (GND-Shield) and shielded by buffered signals of the corresponding electrodes (Active-Shield), respectively, on a custom hardware platform based on TI ADS1299. The results showed that power line interference would be significantly suppressed when using shielding approaches, and the Active-Shield method could achieve the best performance with a power line interference reduction up to 36dB. The study suggested that the Active-Shield method at the analog front-end was a great candidate to reduce power line interference in routine acquisitions of physiological signals.
Subject(s)
Signal Processing, Computer-Assisted , Algorithms , Electricity , Electrocardiography , Electrodes , SoftwareABSTRACT
@#Objective To develop a non-invasive means that monitoring surface electromyography (sEMG) of abdominal muscles for bladder function. Methods SEMG of abdominal muscles from 10 healthy subjects were collected, and the parameters were analyzed in time domain and frequency domain quantificationally based on MATLAB. Results and Conclusion The sEMG of abdominal muscles are related with the process of storing and expelling urine.
