Procesamiento y caracterización de bioseñales para su uso en interfaces de control y afectividad

Las interfaces HCI y PC basadas en bioseñales constan de 3 fases: la captación de los datos, procesamiento y actuación sobre el sistema. El trabajo de esta tesis está centrado en el bloque de procesamiento de la información registrada por los electrodos. La naturaleza heterogénea de las bioseñales implica diferentes técnicas de captación y procesamiento para destacar y detectar aquellos elementos que son útiles para el objetivo que se busca. Para interfaces HCI, las señales deben se susceptibles de ser modificadas según la voluntad del individuo, destacando los transitorios asociados a estas acciones y minimizando aquellos elementos que puedan interferir negativamente, mientras que para PC los datos deben de contener información relativa al estado emocional del sujeto. El procesamiento de los datos es un elemento esencial para obtener unos resultados satisfactorios. A lo largo de la presente tesis se han expuesto dos técnicas de procesamiento basadas en la aplicación de envolventes inferiores, para eliminar o destacar transitorios en forma de campanas cóncavas/convexas de las señales EOG y ECG, y se han analizado las variaciones de las mismas junto a los datos de EEG ante situaciones de estrés y control de un teclado virtual

A new multisensor software architecture for movement detection: Preliminary study with people with cerebral palsy

A five-layered software architecture translating movements into mouse clicks has been developed and tested on an Arduino platform with two different sensors: accelerometer and flex sensor. The archi-tecture comprises low-pass and derivative filters, an unsupervised classifier that adapts continuously to the strength of the user's movements and a finite state machine which sets up a timer to prevent in-voluntary movements from triggering false positives. Four people without disabilities and four people with cerebral palsy (CP) took part in the experi-ments. People without disabilities obtained an average of 100% and 99.3% in precision and true positive rate (TPR) respectively and there were no statistically significant differences among type of sensors and placement. In the same experiment, people with disabilities obtained 97.9% and 100% in precision and TPR respectively. However, these results worsened when subjects used the system to access a commu-nication board, 89.6% and 94.8% respectively. With their usual method of access-an adapted switch- they obtained a precision and TPR of 86.7% and 97.8% respectively. For 3-outof- 4 participants with disabilities our system detected the movement faster than the switch. For subjects with CP, the accelerometer was the easiest to use because it is more sensitive to gross motor motion than the flex sensor which requires more complex movements. A final survey showed that 3-out-of-4 participants with disabilities would prefer to use this new technology instead of their tra-ditional method of access

Envelope filter sequence to delete blinks and overshoots

Background: Eye movements have been used in control interfaces and as indicators of somnolence, workload and concentration. Different techniques can be used to detect them: we focus on the electrooculogram (EOG) in which two kinds of interference occur: blinks and overshoots. While they both draw bell-shaped waveforms, blinks are caused by the eyelid, whereas overshoots occur due to target localization error and are placed on saccade. They need to be extracted from the EOG to increase processing effectiveness. Methods: This paper describes off- and online processing implementations based on lower envelope for removing bell-shaped noise; they are compared with a 300-msmedian filter. Techniques were analyzed using two kinds of EOG data: those modeled from our own design, and real signals. Using a model signal allowed to compare filtered outputs with ideal data, so that it was possible to quantify processing precision to remove noise caused by blinks, overshoots, and general interferences. We analyzed the ability to delete blinks and overshoots, and waveform preservation. Results: Our technique had a high capacity for reducing interference amplitudes (>97%), even exceeding median filter (MF) results. However, the MF obtained better waveform preservation, with a smaller dependence on fixation width. Conclusions: The proposed technique is better at deleting blinks and overshoots than the MF in model and real EOG signals

Stress and heart rate: significant parameters and their variations

The aim of this paper is to identify heart rate parameters with higher significant values when a set of people are performing a task under stress condition. In order to accomplish this, one computer application with arithmetic and memory activities which lets drive the subjects to different stages of activity and stress has been designed. Tests are formed by initial and final rest periods and three task phases with incremental stressful level. Electrocardiogram is measured in each state and parameters are extracted from it. A statistical study using analysis of variance (ANOVA) is done to see which ones are the most significant. It is concluded that the median of RR segments is the parameter to best determine the state of stress.Regional Government of Andalusia (p08-TIC-3631

EEG Feature Variations under Stress Situations

The goal of this study is to identify EEG parameters and electrode positions with the highest significant values to differentiate between tasks and relax periods. Different signals were recorded as 12 subjects are doing arithmetic and memory tasks under stress condition. The test consisted of an initial and final 5-minute relax periods and three 4-minute performance phases with increased stress level. q and a bands concentrated mainly features whose variation were significant, and F3 and P4 were the best positions to distinguish between performed tasks and arousal level

Emotions Detection based on a Single-electrode EEG Device

The study of emotions using multiple channels of EEG represents a widespread practice in the field of research related to brain computer interfaces (Brain Computer Interfaces). To date, few studies have been reported in the literature with a reduced number of channels, which when used in the detection of emotions present results that are less accurate than the rest. To detect emotions using an EEG channel and the data obtained is useful for classifying emotions with an accuracy comparable to studies in which there is a high number of channels, is of particular interest in this research framework. This article uses the Neurosky Maindwave device; which has a single electrode to acquire the EEG signal, Matlab software and IBM SPSS Modeler; which process and classify the signals respectively. The accuracy obtained in the detection of emotions in relation to the economic resources of the hardware dedicated to the acquisition of EEG signal is remarkable

Customizable Software Interface for Monitoring Applications

In this paper we propose an application based on virtual keyboard and automatic scanning to communicate with a PC and the others people. The aim users are the people with disabilities. A high degree of customization is possible in the software. So the user can selected the color of buttons, position of system on screen, the kind of scanning, timer, the interface of communication, etc. Five people without disabilities tested our system. The results of the tests show the application reduce the fatigue of user and increased the text entry rate.Junta de Andalucía p08-TIC-363

A Flexible, Open, Multimodal System of Computer Control Based on Infrared Light

This In this paper, a system architecture that can be adapted to an individual’s motor capacity and preferences, to control a computer is presented. The system uses two different transducers based on the emission and the reflection of infrared light. These let to detect of voluntary blinks, winks, saccadic or head movements and/or sequences of them. Transducer selection and operational mode can be configured. The signal provided by the transducer is adapted, processed and sent to a computer by external hardware. The computer runs a row-column scanned switch-controlled Virtual Keyboard (VK). This sends commands to the operating system to control the computer, making possible to run any application such as a web browser, etc. The main system characteristics are flexibility and relatively low-cost hardware.Junta de Andalucía p08-TIC-363

Fingerprint indoor position system based on OpenMAC

This paper presents a work in progress for the developing of a fingerprint indoor position system based on OpenMAC, an IEEE 802.15.4 embedded software implementation from Atmel to be used in different scenarios like e_health, ambient living or smart building. The system is thought to work as another one that we have yet developed but using the BitCloud Stack, a full-featured, second generation embedded software stack from the same supplier, but improving it. The first steps followed up in the system development are shown in this paper.Junta de Andalucía p08-TIC-363

The IEC-60870-5 standard for a personal server applied to telemedicine

This paper presents a proposal of a flexible telemedicine system for remote patient monitoring. It can be used in different kind of environments where there is only available low speed transmission links like Radio Frequency. This proposal includes the use of a previous work where the IEC-60870-S standard was applied to the development of an open and flexible RTU (Remote Terminal Unit) based in open hardware, a SoCtype design using a FPGA programmed with the open core LEON and open source, so both the hardware and the ISO are open source.Junta de Andalucía p08-TIC-363