synchronization

Although gait rehabilitation based on sensorimotor synchronization (auditory and visual) is stimulating for patients with neurological disorders and older people, there is little evidence in patients with multiple sclerosis (MS). Therefore, this study investigates the effect of synchronization with rhythmic visual stimulus on gait spatiotemporal parameters, bilateral symmetry, and locomotor rehabilitation index in women with MS.

Spatiotemporal parameters, bilateral symmetry and the locomotor rehabilitation index were obtained before and after 6 weeks (three times per week, 30 min each session) of locomotor training. We compared these findings between two groups of 10 patients, each with an expanded disability status scale (EDSS) of 3-6, who performed the gait training with or without rhythmic visual stimulus.

Time×group interaction effect indicated greater significant improvements in the group with rhythmic visual stimulus in self-selected walking speed (SSWS) (P=0.041), stride frequency (P=0.009), stance time (P=0.021), and locomotor rehabilitation index (P=0.036). Stride length, double stance, and swing time were improved in the group with rhythmic visual stimulus, but this change was not significant. Also, bilateral symmetry did not change significantly in the experimental group. Therefore, rhythmic visual stimulation can help improve functional mobility and locomotor rehabilitation index in patients with MS, especially due to the improvements in the temporal parameters of gait.

Therefore, synchronizing gait with a rhythmic visual stimulus can be an effective therapeutic strategy to improve gait and main temporal parameters in patients with MS.

Transcranial electrical stimulation (tES) has shown promise in enhancing post-stroke patients' neural plasticity and functional abilities. However, determining the optimal protocol for this method remains an open question. Our study proposes a novel approach: synchronized stimulation that combines mechanical and electrical stimuli. We hypothesize that this approach will enhance tactile localization ability in post-stroke patients.

We recruited a total of 23 patients and conducted four different types of experiments involving periodic mechanical stimulation on their fingertips. The primary objective was to assess the participant's ability to localize the location of the mechanical stimulation accurately. In one experiment, only mechanical stimulation was administered. Electrical stimulations were combined with mechanical stimulation in the remaining three experiments. The electrical stimulations comprised of one of the following protocols: (1) (tES) pulses administered solely for the initial five seconds of the session, (2) continuous (tES) pulses throughout the entire duration of the mechanical stimulation, and (3) (tES) pulses synchronized precisely with the timing of the mechanical stimulation.

A noteworthy enhancement in tactile localization ability was observed when the electrical and mechanical stimulations were synchronized.

 Our findings demonstrate that the integration of electrical brain stimulation with simultaneous mechanical stimulation of the fingertips resulted in enhanced neural activities. This synchronized integration holds the potential to improve perception and may serve as a vital approach in the treatment of post-stroke patients.

In this paper, an encryption algorithm for the security of medical images is presented, which has extraordinary security. Given that the confidentiality of patient data is one of the priorities of medical informatics, the algorithm can be used to store and send medical image.

In this paper, the solutions of chaotic differential equations are used to generate encryption keys. This method is more than other methods used in encoding medical images, resistant to statistics attacks, low encryption and decryption time and very high key space. In the proposed algorithm, unlike other methods that use random key generation, this method uses the production of solutions of the chaotic differential equations in a given time period for generating a key. All simulations and coding are done in MATLAB software.

Chaotic Differential Equations have two very important features that make it possible to encode medical images. One is the unpredictability of the system's behavior and the other is a severe sensitivity to the initial condition.

These two features make the method resistant to possible attacks to decode the concept of synchronization chaotic systems. Using the results of the method, medical information can be made safer than existing ones.

This paper addresses synchronizing two coupled chaotic FitzHugh–Nagumo (FHN) neurons with weakly gap junction under external electrical stimulation (EES). To transmit information among coupled neurons, by generalization of the integer-order FHN equations of the coupled system into the fractional-order in frequency domain using Crone approach, the behavior of each coupled neuron relies on its past behavior and the memorized system can be a better fit for the neuron response. An adaptive fractional-order controller Based on the Lyaponuv stability theory has been designed to synchronize two neurons electrically coupled with gap junction in EES. The proposed controller is also robust to the inevitable random noise such as disturbances of ionic channels. The simulation results demonstrate the effectiveness of the control scheme.