NeuroPhone: Brain-Mobile Phone Interface using a Wireless EEG Headset

Neural signals are everywhere just like mobile phones. We propose to use neural signals to control mobile phones for hands-free, silent and effortless human-mobile interaction. Until recently, devices for detecting neural signals have been costly, bulky and fragile. We present the design, implementation and evaluation of the NeuroPhone system, which allows neural signals to drive mobile phone applications on the iPhone using cheap off-the-shelf wireless electroencephalography (EEG) headsets. We demonstrate a mind-controlled address book dialing app, which works on similar principles to P300-speller brain-computer interfaces: the phone flashes a sequence of photos of contacts from the address book and a P300 brain potential is elicited when the flashed photo matches the person whom the user wishes to dial. EEG signals from the headset are transmitted wirelessly to an iPhone, which natively runs a lightweight classifier to discriminate P300 signals from noise. When a person\u27s contact-photo triggers a P300, his/her phone number is automatically dialed. NeuroPhone breaks new ground as a brain-mobile phone interface for ubiquitous pervasive computing. We discuss the challenges in making our initial prototype more practical, robust, and reliable as part of our on-going research

A Novel Real-Time Intelligent Tele Cardiology System Using Wireless Technology to Detect Cardiac Abnormalities

This study presents a novel wireless, ambulatory,real- time, and auto alarm intelligent telecardiology system to improve healthcare for cardiovascular disease, which is one of the most prevalent and costly health problems in the world.This system consists of a lightweight and power-saving wireless ECG device equipped with a built-in automatic warning expert system. A temperature sensor is fixed to the user2019;s body, which senses temperature in the body, and delivers it to the ECG device. This device is connected to a microcontroller and ubiquitous real-time display platform. The acquired ECG signals which are transmitted to the microcontroller is then, processed by the expert system in order to detect the abnormality. An alert signal is sent to the remote database server, which can be accessed by an Internet browser, once an abnormal ECG is detected. The current version of the expert system can identify five types of abnormal cardiac rhythms in real-time, including sinus tachycardia, sinus bradycardia, wide QRS complex, atrial fibrillation (AF), and cardiac asystole, which is very important for both the subjects who are being monitored and the healthcare personnel tracking cardiac-rhythm disorders. The proposed system also activates an emergency medical alarm system when problems occur. We believe that in the future a business-card-like ECG device, accompanied with a Personal Computer, can make universal cardiac protection service possible

Subject Combination and Electrode Selection in Cooperative Brain-Computer Interface Based on Event Related Potentials

New paradigms are required in Brain-Computer Interface (BCI) systems for the needs and expectations of healthy people. To solve this issue, we explore the emerging field of cooperative BCIs, which involves several users in a single BCI system. Contrary to classical BCIs that are dependent on the unique subject’s will, cooperative BCIs are used for problem solving tasks where several people shall be engaged by sharing a common goal. Similarly as combining trials over time improves performance, combining trials across subjects can significantly improve performance compared with when only a single user is involved. Yet, cooperative BCIs may only be used in particular settings, and new paradigms must be proposed to efficiently use this approach. The possible benefits of using several subjects are addressed, and compared with current single-subject BCI paradigms. To show the advantages of a cooperative BCI, we evaluate the performance of combining decisions across subjects with data from an event-related potentials (ERP) based experiment where each subject observed the same sequence of visual stimuli. Furthermore, we show that it is possible to achieve a mean AUC superior to 0.95 with 10 subjects and 3 electrodes on each subject, or with 4 subjects and 6 electrodes on each subject. Several emerging challenges and possible applications are proposed to highlight how cooperative BCIs could be efficiently used with current technologies and leverage BCI applications

(IEEE 2019) The Method of Integrating Virtual Reality with Brainwave Sensor for an Interactive Math's Game

The implementation of the Virtual Reality (VR) on game is practical for in various fields, especially in the field of Education. The implementation of a mobile based VR game is example where the players of game feel as in the real world. However, the VR game has the weakness on limited interaction of their player with the virtual environment created by the game. Currently, the interactions pass through the buttons on mobile phone and joysticks. For this reason, this research investigates the alternative media to control the virtual environment of the game using brain sensor. The prototype was created using “mindwave neurosky” as brain sensor and thingkgear as sensor drive to construct the experiment of mobile based virtual reality math game. This research tests three modes signal including meditation, attention and beta signal. A meditation signal was taken when the player open and close the eye. While attention and beta signals were taken when the player focuses. The result is some model to control the VR math game with brain sensor for child five or six year old's

Architecture and system level concept for wireless brain machine interface

The recent progresses in the field of medicine and biotechnology have made it possible to implant micro-electronic devices in the human body. In the field of semiconductor technology, the immense progress provides a way for devices at a millimeter scale or less such as micro-implants, but still there are some challenges in the miniaturization of the power source. This is the major hurdle in the development of a BMI device with micro electrodes for clinical use that are less or fully invasive. In upcoming BMI models, it is possible to implant data extraction electrodes and controls the device as a natural part of its representation of the body. As a short term solution for all these vast bulk of implantable electronic devices consists of harvesting components or energy storage. The revolutions and innovations in last era, to develop the interface of neuroscience and engineering lead to the advent of the field of Brain Machine Interfaces (BMIs). In a BMI system, it is difficult to analyze the brain waves because it carries a large amount of information. Data acquisition unit can receive the particular information through wired or wireless system. The neural recordings will also need to go through a process of pre-signaling for feature extraction and translation algorithm. Brain signal pre-processing can be done by using three methods. These methods are Basic Filtering, Adaptive Filtering and Blind Source Separation. The data from acquisition unit can be sent through a wireless ZigBee/UWB/WiFi module, depending upon the number of electrode arrays used in BMI system. In this thesis, we have proposed an end-to-end wireless BMI system based on available literature that provides a feasible way for paralyzed patients to communicate and control their muscles and robotic body parts by using their neurological signals. According to this idea, the above mentioned systems can enable a high power efficient and wireless BMI development. From a medical point of view an implantable wireless system is necessary for the applications of invasive BMI to reduce the risk of infection

A Design Framework for Engaging Collective Interaction Applications for Mobile Devices

The main objective of this research is to define the conceptual and technological key factors of engaging collective interaction applications for mobile devices. To answer the problem, a throwaway prototyping software development method is utilized to study design issues. Furthermore, a conceptual framework is constructed in accordance with design science activities. This fundamentally exploratory research is a combination of literature review, design and implementation of mobile device based prototypes, as well as empirical humancomputer interaction studies, which were conducted during the period 2008 - 2012. All the applications described in this thesis were developed mainly for research purposes in order to ensure that attention could be focused on the problem statement. The thesis presents the design process of the novel Engaging Collective Interaction (ECI) framework that can be used to design engaging collective interaction applications for mobile devices e.g. for public events and co-creational spaces such as sport events, schools or exhibitions. The building and evaluating phases of design science combine the existing knowledge and the results of the throwaway prototyping approach. Thus, the framework was constructed from the key factors identified of six developed and piloted prototypes. Finally, the framework was used to design and implement a collective sound sensing application in a classroom setting. The evaluation results indicated that the framework offered knowledge to develop a purposeful application. Furthermore, the evolutionary and iterative framework building process combined together with the throwaway prototyping process can be presented as an unseen Dual Process Prototyping (DPP) model. Therefore it is claimed that: 1) ECI can be used to design engaging collective interaction applications for mobile devices. 2) DPP is an appropriate method to build a framework or a model. This research indicates that the key factors of the presented framework are: collaborative control, gamification, playfulness, active spectatorship, continuous sensing, and collective experience. Further, the results supported the assumption that when the focus is more on activity rather than technology, it has a positive impact on the engagement. As a conclusion, this research has shown that a framework for engaging collective interaction applications for mobile devices can be designed (ECI) and it can be utilized to build an appropriate application. In addition, the framework design process can be presented as a novel model (DPP). The framework does not provide a step-by-step guide for designing applications, but it helps to refine the design of successful ones. The overall benefit of the framework is that developers can pay attention to the factors of engaging application at an early stage of design