Wireless Mouth Motion Recognition System Based on EEG-EMG Sensors for Severe Speech Impairments.

This study aims to demonstrate the feasibility of using a new wireless electroencephalography (EEG)-electromyography (EMG) wearable approach to generate characteristic EEG-EMG mixed patterns with mouth movements in order to detect distinct movement patterns for severe speech impairments. This paper describes a method for detecting mouth movement based on a new signal processing technology suitable for sensor integration and machine learning applications. This paper examines the relationship between the mouth motion and the brainwave in an effort to develop nonverbal interfacing for people who have lost the ability to communicate, such as people with paralysis.

Social context modulates multibrain broadband dynamics and functional brain-to-brain coupling in the group of mice.

Although mice are social, multiple animals' neural activities are rarely explored. To characterise the neural activities during multi-brain interaction, we simultaneously recorded local field potentials (LFP) in the prefrontal cortex of four mice. The social context and locomotive states predominately modulated the entire LFP structure.

A Wearable Multimodal Wireless Sensing System for Respiratory Monitoring and Analysis.

Wireless sensing systems are required for continuous health monitoring and data collection. It allows for patient data collection in real time rather than through time-consuming and expensive hospital or lab visits. This technology employs wearable sensors, signal processing, and wireless data transfer to remotely monitor patients' health.

Extraction and Analysis of Respiratory Motion Using a Comprehensive Wearable Health Monitoring System.

Respiratory activity is an important vital sign of life that can indicate health status. Diseases such as bronchitis, emphysema, pneumonia and coronavirus cause respiratory disorders that affect the respiratory systems. Typically, the diagnosis of these diseases is facilitated by pulmonary auscultation using a stethoscope.

A bird's-eye view of brain activity in socially interacting mice through mobile edge computing (MEC).

Social cognition requires neural processing, yet a unifying method linking particular brain activities and social behaviors is lacking. Here, we embedded mobile edge computing (MEC) and light emitting diodes (LEDs) on a neurotelemetry headstage, such that a particular neural event of interest is processed by the MEC and subsequently an LED is illuminated, allowing simultaneous temporospatial visualization of that neural event in multiple, socially interacting mice. As a proof of concept, we configured our system to illuminate an LED in response to gamma oscillations in the basolateral amygdala (BLA gamma) in freely moving mice.

Identification of Gait Motion Patterns Using Wearable Inertial Sensor Network.

Gait signifies the walking pattern of an individual. It may be normal or abnormal, depending on the health condition of the individual. This paper considers the development of a gait sensor network system that uses a pair of wireless inertial measurement unit (IMU) sensors to monitor the gait cycle of a user.

Extraction and Analysis of Respiratory Motion Using Wearable Inertial Sensor System during Trunk Motion.

Respiratory activity is an essential vital sign of life that can indicate changes in typical breathing patterns and irregular body functions such as asthma and panic attacks. Many times, there is a need to monitor breathing activity while performing day-to-day functions such as standing, bending, trunk stretching or during yoga exercises. A single IMU (inertial measurement unit) can be used in measuring respiratory motion; however, breathing motion data may be influenced by a body trunk movement that occurs while recording respiratory activity.

Active brainwave pattern generation for brain-to-machine communication.

Over the years of research, Electroencephalogram (EEG) signal study has grown to give promising outcomes. A lot of research has been done on implementing brain-computer-interfaces, and the brain-computer interface (BCI) algorithm as well as the study of the effects of different stimuli on brain signals. This paper intends to make progress toward that goal by developing a responsive real-time EEG-based brain-to-machine communication system by generating distinct EEG signals at will and identification of the explicit pattern that they reflect for the presented self-induced internal visual and auditory stimuli.

A Wireless 32-Channel Implantable Bidirectional Brain Machine Interface.

All neural information systems (NIS) rely on sensing neural activity to supply commands and control signals for computers, machines and a variety of prosthetic devices. Invasive systems achieve a high signal-to-noise ratio (SNR) by eliminating the volume conduction problems caused by tissue and bone. An implantable brain machine interface (BMI) using intracortical electrodes provides excellent detection of a broad range of frequency oscillatory activities through the placement of a sensor in direct contact with cortex.

Maximization of acoustic energy difference between two spaces.

There has recently been an increasing interest in the generation of a sound field that is audible in one spatial region and inaudible in an adjacent region. The method proposed here ensures the control of the amplitude and phase of multiple acoustic sources in order to maximize the acoustic energy difference between two adjacent regions while also ensuring that evenly distributed source strengths are used. The performance of the method proposed is evaluated by computer simulations and experiments with real loudspeaker arrays in the shape of a circle and a sphere.

Bio-information scanning technology using an optical pick-up head.

We have developed a low cost and a highly compact bio-chip detection technology by modifying a commercially available optical pick-up head for CD/DVD. The highly parallel and miniaturized hybridization assays are addressed by the fluorescence emitted by the DNA-chip using the optical pick-up head. The gap between the objective lens and the bio-chip is regulated by the focus servo during the detection of the fluorescence signal.