Defect corrections for coherent optical information processing of grayscale images in a DMD-based 4f-system using a collimated light source.

Digital micromirror device (DMD)-based 4f-systems, a type of coherent optical information processing system, have become a powerful tool for optical convolutional neural networks taking advantage of their fast modulation speed and high-resolution capability. However, proper high bit-depth image information processing remains challenging due to the optical diffractions that arise from the binary nature of DMD operation. In this paper, we first characterize the diffraction phenomena that cause irradiance defects, namely the nonlinear grayscale and unintended dark lines. Then to resolve the issues, we propose a DMD operation method and a modified structure of the 4f-system based on blazed diffraction grating theory and numerical calculation of the Rayleigh-Sommerfeld propagation model. As a demonstration, we implement high bit-depth image information processing with an optimized optical 4f-system using DMDs and a collimated coherent light source.

A wearable electromyography-controlled functional electrical stimulation system improves balance, gait function, and symmetry in older adults.

BACKGROUND: Wearable technologies have been developed for healthy aging. The technology for electromyography (EMG)-controlled functional electrical stimulation (FES) systems has been developed, but research on how helpful it is in daily life has been insufficient. OBJECTIVE: The purpose of this study was to investigate the effect of the EMG-controlled FES system on muscle morphology, balance, and gait in older adults. METHODS: Twenty-nine older adults were evaluated under two randomly assigned conditions (non-FES and FES assists). Muscle morphology, balance, gait function, and muscle effort during gait were measured using ultrasonography, a physical test, a gait analysis system, and EMG. RESULTS: The EMG-controlled FES system improved gait speed by 11.1% and cadence by 15.6% (P< 0.01). The symmetry ratio of the bilateral gastrocnemius was improved by 9.9% in the stance phase and 11.8% in the swing phase (P< 0.05). The degrees of coactivation of the knee and ankle muscles were reduced by 45.1% and 50.5%, respectively (P< 0.05). Balance improved by 6-10.7% (P< 0.01). CONCLUSION: The EMG-controlled FES system is useful for balance and gait function by increasing muscle symmetry and decreasing muscle coactivation during walking in older adults.

Volitional EMG Estimation Method during Functional Electrical Stimulation by Dual-Channel Surface EMGs.

We propose a novel dual-channel electromyography (EMG) spatio-temporal differential (DESTD) method that can estimate volitional electromyography (vEMG) signals during time-varying functional electrical stimulation (FES). The proposed method uses two pairs of EMG signals from the same stimulated muscle to calculate the spatio-temporal difference between the signals. We performed an experimental study with five healthy participants to evaluate the vEMG signal estimation performance of the DESTD method and compare it with that of the conventional comb filter and Gram-Schmidt methods. The normalized root mean square error (NRMSE) values between the semi-simulated raw vEMG signal and vEMG signals which were estimated using the DESTD method and conventional methods, and the two-tailed t-test and analysis of variance were conducted. The results showed that under the stimulation of the gastrocnemius muscle with rapid and dynamically modulated stimulation intensity, the DESTD method had a lower NRMSE compared to the conventional methods (p < 0.01) for all stimulation intensities (maximum 5, 10, 15, and 20 mA). We demonstrated that the DESTD method could be applied to wearable EMG-controlled FES systems because it estimated vEMG signals more effectively compared to the conventional methods under dynamic FES conditions and removed unnecessary FES-induced EMG signals.

Volitional EMG Controlled Wearable FES System for Lower Limb Rehabilitation.

Muscle rehabilitation by functional electrical stimulation (FES) is one of the effective treatments for the patients with neuromuscular diseases. The conventional FES applications, however, have limitations that utilize predetermined or repetitive stimulation patterns with the help of experts such as physical therapists. Therefore, we propose a wearable FES system in which the stimulus intensity is dynamically controlled by the motion intention of user in this paper. The proposed FES system utilizes electromyography (EMG) and inertial measurement unit (IMU) sensors for estimating the motion intention regardless of electrical stimulation, and is designed for the lower limb rehabilitation. The overall system configurations including hardware and software are presented in this paper, and the system performance was tested by lower limb exercises, e.g., squat, heel lift, and gait.