Manuel Merino

A Method of EOG Signal Processing to Detect the Direction of Eye Movements

In this paper, a signal processing algorithm to detect eye movements is developed. The algorithm works with two kinds of inputs: derivative and amplitude level of electrooculographic signal. Derivative is used to detect signal edges and the amplitude level is used to filter noise. Depending of movement direction, different kinds of events are generated. Events are associated with a movement and its route. A hit rate equal to 94% is reached. This algorithm has been used to implement an application that allows computer control using ocular movement.

Envelopment filter and K-means for the detection of QRS waveforms in electrocardiogram.

The electrocardiogram (ECG) is a well-established technique for determining the electrical activity of the heart and studying its diseases. One of the most common pieces of information that can be read from the ECG is the heart rate (HR) through the detection of its most prominent feature: the QRS complex. This paper describes an offline version and a real-time implementation of a new algorithm to determine QRS localization in the ECG signal based on its envelopment and K-means clustering algorithm. The envelopment is used to obtain a signal with only QRS complexes, deleting P, T, and U waves and baseline wander. Two moving average filters are applied to smooth data. The K-means algorithm classifies data into QRS and non-QRS. The technique is validated using 22 h of ECG data from five Physionet databases. These databases were arbitrarily selected to analyze different morphologies of QRS complexes: three stored data with cardiac pathologies, and two had data with normal heartbeats. The algorithm has a low computational load, with no decision thresholds. Furthermore, it does not require any additional parameter. Sensitivity, positive prediction and accuracy from results are over 99.7%.

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

Abstract 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 architecture comprises low-pass and derivative filters, an unsupervised classifier that adapts continuously to the strength of the users movements and a finite state machine which sets up a timer to prevent involuntary movements from triggering false positives. Four people without disabilities and four people with cerebral palsy (CP) took part in the experiments. 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 communication 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-out-of-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 traditional method of access.

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.

The Role of Small Robots in Designed Play Workshops in Centers of Adults with Cerebral Palsy

An experience that took place in ASPACE (Association of People with Cerebral Palsy in Seville) showed that the intervention with games based on tangible devices like small robots is a good alternative in the case of people with cerebral palsy (CP). The aim is to develop skills in three facets: cognitive, motor and social. From three to six sessions with seven subjects allowed obtaining information on the evolution of them and their involvement in the activity.

Envelope filter sequence to delete blinks and overshoots.

BackgroundEye 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.MethodsThis paper describes off- and online processing implementations based on lower envelope for removing bell-shaped noise; they are compared with a 300-ms-median 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.ResultsOur 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.ConclusionsThe proposed technique is better at deleting blinks and overshoots than the MF in model and real EOG signals.

Assessment of biosignals for managing a virtual keyboard

In this paper we propose an assessment of biosignals for handling an application based on virtual keyboard and automatic scanning. The aim of this work is to measure the effect of using such application, through different interfaces based on electromyography and electrooculography, on cardiac and electrodermal activities. Five people without disabilities have been tested. Each subject wrote twice the same text using an electromyography interface in first test and electrooculography in the second one. Each test was divided into four parts: instruction, initial relax, writing and final relax. The results of the tests show important differences in the electrocardiogram and electrodermal activity among the parts of tests.

A Wearable System for Multisensory Stimulation Therapy for Children

Multisensory stimulation therapy involves the simultaneous stimulation of several senses in a relaxing environment to achieve a variety of therapeutic outcomes for clients with conditions affecting sensory and cognitive processes. We present, StimuHat, a wearable system for therapists to visually stimulate patients. We conducted a pilot study in which a therapist used StimuHat in sessions with three children with profound brain damage. The results showed that StimuHat appears to have stimulated the children and created positive relaxation and engagement in them.

A Hardware/Software Platform to Acquire Bioelectrical Signals. A Case Study: Characterizing Computer Access through Attention.

This paper describes a hardware/software platform to acquire human body signals. In the field of physiological computing it is desirable to have a system that allows the synchronized acquisition of signals coming from different sources. Here is described how to unify the whole process of acquiring signals from both customized hardware and low cost commercial devices such as Neurosky’s mindwave. A case study using this platform is also shown: studying the feasibility of using sustained attention to access a computer. In order to do that brain activity was measured using Neurosky’s mindwave. The participants in this study were asked to keep their attention high/low for as long as possible during several trials. Experimentation was performed by 7 normally developed subjects and 3 people with cerebral palsy (CP). Our preliminary work shows that 60% of participants might be potential users of this technology. Eventually, modulating the attention to access a communication board needs a scanning period greater than 5.76s.

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. θ and α bands concentrated mainly features whose variation were significant, and F3 and P4 were the best positions to distinguish between performed tasks and arousal level.