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Analysis of Dynamic Interaction in Non-Invasive Multichannel Biosignals for Rehabilitation and Therapy


Problem Description

Neuromuscular, respiratory and neurological disorders have a high social and economic impact. Among respiratory pathologies, for example, Chronic Obstructive Pulmonary Disease (COPD) affects more than 50 million people worldwide, caused 2.5 million deaths in 2000, and is the fourth leading cause of death in the developed world. Obstructive Sleep Apnea Syndrome (OSAS) affects approximately 3.4% of adult men in Spain, according to the European Lung Foundation. In assisted ventilation, evolution of pathophysiological knowledge and technology has resulted in a confusing variety of new modalities and techniques designed to augment alveolar ventilation, decrease work of breathing, improve the match between ventilation and perfusion, and the oxygenation of arterial blood. Most of these ventilatory support modalities are similar technically and physiologically. Nevertheless, the selection and configuration of these modalities depends of anthropometric features, the knowledge of pathophysiological condition of patient and the expertise of medical doctors in the use of mechanical ventilators (Putensen and Wrigge 1998). Consequently, the design of new tools with the capability of assisting the specialists in the decision of which modality and configuration is the appropriate for one specific patient is nowadays an essential field of researching.

On the other hand, Spinal Cord Injury (SCI) is present in many countries around the world, with an annual incidence of 15 to 40 cases per million. Work-related Upper Extremity Disorders (WRUEDs) are conceived as a multifactorial syndrome due to effects of excessive repetitive motions and sustained static postures (Van Galen et al. 2002). Lateral Epicondyilitis is one of the most common WRUEDs and it is characterized by pain in the region of the lateral epicondyle of the humerus, which is exacerbated by the repeated use of either the extensor or flexor forearm muscles. This disorder is closely related to CNS fatigue in forearm extensor muscles and can be reliable investigated by the analysis of SEMG signals, but “crosstalk” due to the close proximity among forearm muscles, is a very important problem to be solved. Besides, these muscles have multiple IZs and potentials propagating simultaneously in both directions changing MUAP waveforms. Furthermore, different isometric and isokinetic (eccentric and concentric) exercises are carried out during rehabilitation, but there are not yet objective indexes for monitoring the activity and fatigability of these forearm muscles and it is not yet well known which type of exercises are more appropriate.

Rehabilitation processes and clinical therapies are absolutely necessary in order to improve the patients’ situation. This project proposes the application of advanced algorithms in multichannel biosignals obtained by Non Invasive Methods for the evaluation and monitoring of this rehabilitation or therapy.


Background and Previous Experience

Our group has large experience in carrying out algorithms for biomedical signal processing, systems modelling and simulation. In this new project we propose to take profit of this knowledge in order to start a new research Topic focused completely on the evaluation of interactions and coordinations: between muscles and between brain areas or respiratory variables during rehabilitation and therapies.

Our group has used linear electrode arrays and have started processing the multichannel EMG signals by means of an Integrated Action (Science and Education Minister from Spain) between an Italian prestigious laboratory (LiSIN: Laboratory for Neuromuscular System Engineering and Motor Rehabilitation directed by Prof Merletti from the Technical University of Turin) and our group (Mañanas et al, 2005; Rojas et al, 2006, 2007). Our group has designed an experimental protocol with and acquisition system composed of linear electrodes arrays for the evaluation of forearm muscles in the framework of this Integrated Action (Mañanas et al. 2005). Our previous results in healthy subjects and patients with epicondylitis showed the necessity to improve the estimation of EMG variables because recorded sEMG signals have a lot of non-propagating potentials due to crosstalk and changes in MUAP’s waveforms (Mañanas et al. 2005), (Rojas et al. 2006).

Our group has developed a respiratory model based on an optimization law provided and a linearization of the complex mechanical plant previously published. It has been validated with data from controls during exercise and hypercapnic stimulus and also with obstructive and restrictive patients (Mañanas et al, 2003, 2004, Hernandez et al, 2007). This work has been developed within the framework of a PhD Thesis (Hernandez, 2007) carried out by one of the members of the research group and directed by the Main Researcher of this Project. The activities proposed in this Project are the natural extension of his Thesis. Thus, it will be possible to add a mechanical ventilator to the developed model in order to simulate different ventilation modes during the proposed Project.

Our research group has experience in the study of respiratory muscles activity in patients with respiratory disease (Mañanas et al., 2000, 2001, 2002, 2003). With respect to Obstructive Sleep Apnea Syndrome, statistically significant differences have been obtained between patients and normal subjects by means of temporal and spectral variables (Mañanas et al., 2002, 2003). Coordination between respiratory muscles has already been studied by means of linear approaches in our research group. However, the assessment of statistical dependencies between respiratory muscles using nonlinear techniques has shown to be more suitable for this purpose. Also in this context, the first results of the application of Mutual Information Function (MIF) to respiratory myographyc signals have been obtained (Alonso et al, 2007).

Our group has been working on EEG signal processing for the last years, particularly, evaluating drug therapy (Barbanoj et al, 2006, 2008) and filtering artifacts from EEG signals by means of BSS-ICA both during wakefulness (Romero et al, 2004, 2008) and sleep (Romero et al, 2003).


Aim and Research Topics

This project proposes advanced algorithms for processing multichannel noninvasive biosignals in order to evaluate interactions between muscles, brain areas, drugs, and respiratory variables and then, to be applied in rehabilitation and therapy to improve their efficiency and success.

In this Project, three research topics have been proposed: