Ana Londral

Quality of life in amyotrophic lateral sclerosis patients and caregivers: Impact of assistive communication from early stages

Introduction: In this study we performed a longitudinal investigation to assess the impact of early introduction of assistive communication devices (ACDs) on quality of life (QoL) in amyotrophic lateral sclerosis (ALS) patients and their caregivers. Methods: Patients were followed for 7–10 months (3 evaluation periods). Bulbar‐onset ALS patients (N = 27) and paired caregivers (N = 17) were included. Fifteen randomly selected patients received early support in ACD use. Patients were assessed using the ALS Functional Rating Scale—revised (ALSFRS‐R), the McGill QoL (MQoL), the Communication Effectiveness Index (CETI), and performance in writing; and caregivers were assessed with the MQoL and World Health Organization Quality of Life questionnaire (WHOQOL‐BREF). Results: Patients with early support had higher MQoL Psychological and MQoL Existential well‐being domains; caregivers had higher MQoL Support domain and their MQoL Psychological domain positively associated with patient CETI. Most patients could communicate using a touchscreen keyboard to write, even when handwriting and speech were not possible. Conclusion: Early intervention with an ACD seems to have a positive impact on QoL and gives patients the opportunity to improve skills for communication in later disease stages. Muscle Nerve 52: 933–941, 2015

Monitoring amyotrophic lateral sclerosis by biomechanical modeling of speech production

Neuromotor Degenerative Diseases (NDD) affecting mainly sub-thalamic and extra-pyramidal neuromotor structures leave significant marks in speech and phonation correlates. These may be used in the characterization, detection, grading and monitoring diseases and their progress in a non-invasive way. Considering that speech and phonation recording can be carried out using handy and low-cost instrumentation, speech and phonation correlates may be quite adequate candidates to define specific NDD biomarkers for disease progress monitoring protocols. The purpose of the paper is to present the fundamentals of speech articulation biomechanical modeling from the level of signal processing to neuromotor activity inference. This backward pathway involves several inverse problems, which are addressed separately. Results from study cases relevant in Amyotrophic Lateral Sclerosis are presented and discussed. The conclusions of the research show that several correlates may be reliably established, and that monitoring disease state and progress may rely on some biomechanical correlates informing on jaw and tongue neuromotor residual activity. Possible applications of the methodology to other neurodegenerative diseases are also discussed.

Application of the Lognormal Model to the Vocal Tract Movement to Detect Neurological Diseases in Voice

In this paper a novel method to evaluate the quality of the voice signal is presented. Our novel hypothesis is that the first and second formants allow the estimation of the jaw-tongue dynamics. Once the velocity is computed, it is approximated by the Sigma-Lognormal model whose parameters enable to distinguish between normal and pathological voices. Three types of pathologies are used to test the method: Laryngeal Diseases, Parkinson and Amyotrophic Lateral Sclerosis. Preliminary results show that the novel features proposed are able to distinguish between parameters of normal and pathological voice. Moreover, it is also possible to discriminate between the three types of pathologies studied in this work.

Neurotechnology, Electronics, and Informatics

Balance control plays a key role in neuromotor rehabilitation after stroke or spinal cord injuries. Computerized Dynamic Posturography (CDP) is a classic tool to assess the status of balance control and to identify potential disorders. In this paper, we present the development of a low cost system and tool for the assessment and training of balance based on static posturography and functional electrical stimulation (FES). The assessment features are built upon a classic a CDP basis, while for training routines, the system uses bioinspired FES patterns and algorithms based on muscle synergies. This system includes low cost technology like the Wii Fit Balance Board and the Kinect. The work described is this paper includes the implementation of the system and first results as a CDP tool.

Towards Improving the Usability of Electromyographic Interfaces

Biosignals have been extensively used within the field of Human- Computer Interaction (HCI) for the development of brain and neuronal computer interaction systems, in particular, targeting augmentative and alternative communication. Electromyography is a commonly used technique in this context, however, conventional signal acquisition procedures require the use of conductive paste or pre-gelled electrodes on the interface with the skin, thus introducing usability constraints and recurrent costs associated with the daily use. Our work is focused on the comparison between standard pre-gelled Ag/AgCl electrodes, dry Ag/AgCl electrodes and conductive fabrics, as a way of improving the usability of electromyographic interfaces for HCI. Experimental results have shown that dry and gelled electrodes perform similarly, thus applicability of alternative electrode materials, and further extending the toolbox of the rehabilitation engineer.

Biomarkers of Neurodegenerative Progression from Spontaneous Speech Recorded in Mobile Devices: An Approach based on Articulation Speed Estimation - A Study of Patients Suffering from Amyotrophic Lateral Sclerosis.

A majority of patients with Amyotrophic Lateral Sclerosis (ALS) experiment a rapid evolution of symptoms related to a progressive decline in movement function that affects different systems. Clinical assessment is based on measures of progression for identifying the need and the pace of medical decisions, and to measure also the effects of novel therapies. But assessment is limited to the periodicity of clinical appointments that are increasingly difficult for patients due to progressive mobility impairments. In this paper, we present a novel method to assess neurodegeneration process through speech analysis. An articulation kinematic model is proposed to identify markers of neuromotor functional progression in speech. We analysed speech samples that were collected with a mobile device, in 3-month intervals, from a group of six subjects with ALS. Results suggest that the method proposed is sensitive to the symptoms of the disease, as rated by observational clinical scales, and it may contribute to assist clinicians and researchers with better and continuous measures of disease progression.

Monitoring ALS from speech articulation kinematics

AbstractPatients affected by amyotrophic lateral sclerosis (ALS) show specific dysarthria in their speech resulting in specific marks which could be used to detect early symptoms and monitor the evolution of the disease in time. Classically articulation marks have been mainly based on static premises. Articulation kinematics from acoustic correlates may help in producing measurements depending on the dynamic behaviour of speech. Specifically, distribution functions from the absolute kinematic velocity estimated on a simplified articulation model can be used in establishing distances based on information theory concepts between running speech segments from patients and controls. As an example, several cases of ALS were studied longitudinally using this methodology. The study shows that the performance of dynamic articulation quality correlates may be sensitive and robust in tracking illness progress. Conclusions foresee the use of speech as a valuable monitoring methodology for ALS timely neurodegenerative progression.

Articulation acoustic kinematics in ALS speech

Patients affected by Amyotrophic Lateral Sclerosis (ALS) show specific dysarthric clues in speech. These marks could be used to detect early symptoms and monitor the evolution of the disease in time. Classically articulation marks have been mainly based on static premises. Articulation Kinematics from acoustic correlates may help in producing measurements based on the dynamic behavior of speech. Specifically, distribution functions from the absolute kinematic velocity estimated by a simplified articulation model can be used in establishing distances based on Information Theory concepts between running speech segments from patients and controls. As an example, a longitudinal case of ALS has been studied using this methodology. It shows that the performance of dynamic articulation quality correlates may be more sensitive and robust than static ones. Conclusions foresee the use of speech as a valuable monitoring methodology for ALS timely evolution.

Augmenting communication, emotion expression and interaction capabilities of individuals with cerebral palsy

This work was supported by the FP7 Framework EU Research Project ABC (No. 287774). This paper only reflects the authors views and funding agencies are not liable for any use that may be made of the information contained herein.

Characterization of Speech from Amyotrophic Lateral Sclerosis by Neuromorphic Processing

Amyotrophic Lateral Sclerosis is a severe disease which dramatically reduces the speech communication skills of the patient as illness progresses. The present study is devoted to define accurate and objective estimates to characterize the loss of communication skills, to help in monitoring illness progress, and in rehabilitating speech by specialists. The methodology proposed is based on the perceptual (neuromorphic) definition of speech dynamics, concentrated in vowel sounds in character and duration. A longitudinal study carried out on an ALS patient during a year is shown, its results discussed and conclusions for a further study are also presented.