Data Transmission Enhancement Using Optimal Coding Technique Over Channel for Interbody Communication.

Wireless actuators and sensors are examples of sophisticated technologies. Another breakthrough is the use of wireless medical devices, which provide scalable and cost-effective solutions for wearable device integration. wireless body area networks devices reduce surgery invasiveness and provide continuous health monitoring.

Diagnosis of Alzheimer Disease Using 2D MRI Slices by Convolutional Neural Network.

There are many kinds of brain abnormalities that cause changes in different parts of the brain. Alzheimer's disease is a chronic condition that degenerates the cells of the brain leading to memory asthenia. Cognitive mental troubles such as forgetfulness and confusion are one of the most important features of Alzheimer's patients.

Classification of Resting-State Status Based on Sample Entropy and Power Spectrum of Electroencephalography (EEG).

An electroencephalogram (EEG) is a significant source of diagnosing brain issues. It is also a mediator between the external world and the brain, especially in the case of any mental illness; however, it has been widely used to monitor the dynamics of the brain in healthy subjects. This paper discusses the resting state of the brain with eyes open (EO) and eyes closed (EC) by using sixteen channels by the use of conventional frequency bands and entropy of the EEG signal.

Social Touch Gesture Recognition Using Convolutional Neural Network.

Recently, social touch gesture recognition has been considered an important topic for touch modality, which can lead to highly efficient and realistic human-robot interaction. In this paper, a deep convolutional neural network is selected to implement a social touch recognition system for raw input samples (sensor data) only. The touch gesture recognition is performed using a dataset previously measured with numerous subjects that perform varying social gestures.