Detection of emotions in Parkinson's disease using higher order spectral features from brain's electrical activity

Non-motor symptoms in Parkinson's disease (PD) involving cognition and emotion have been progressively receiving more attention in recent times. Electroencephalogram (EEG) signals, being an activity of central nervous system, can reflect the underlying true emotional state of a person. This paper presents a computational framework for classifying PD patients compared to healthy controls (HC) using emotional information from the brain's electrical activity

Decline and fall:a biological, developmental, and psycholinguistic account of deliberative language processes and ageing

Background: This paper reviews the role of deliberative processes in language: those language processes that require central resources, in contrast to the automatic processes of lexicalisation, word retrieval, and parsing. 10 Aims: We describe types of deliberative processing, and show how these processes underpin high-level processes that feature strongly in language. We focus on metalin- guistic processing, strategic processing, inhibition, and planning. We relate them to frontal-lobe function and the development of the fronto-striate loop. We then focus on the role of deliberative processes in normal and pathological development and ageing, 15 and show how these processes are particularly susceptible to deterioration with age. In particular, many of the commonly observed language impairments encountered in ageing result from a decline in deliberative processing skills rather than in automatic language processes. Main Contribution: We argue that central processing plays a larger and more important 20 role in language processing and acquisition than is often credited. Conclusions: Deliberative language processes permeate language use across the lifespan. They are particularly prone to age-related loss. We conclude by discussing implications for therapy

Role of Therapeutic Devices in Enhancing Speech Intelligibility and Vocal Intensity in an Individual with Parkinson’s Disease

The prevailing speech therapy techniques for treating hypokinetic dysarthria in individuals with Parkinson\u27s disease (PD) yields improvements within the clinical setting, however, maintenance and generalization of acquired behaviors continue to be a challenge. The purpose of this study was to investigate the effects of portable therapeutic devices including Ambulatory Phonation Monitor with biofeedback (APM) and auditory masker in maintenance and carryover of improved speech. Our participant was an individual diagnosed with PD for the past 25 years who continued to display speech disturbances despite undergoing several behavioral speech therapy programs and neurosurgical procedures. Speech intelligibility and average intensity measures under automatic, elicited, and spontaneous speech tasks were recorded pre- and postusage of APM and auditory masker for a period of 1 week each. Preliminary findings showed no significant difference in the measures between means (P\u3e0.05) across all tasks for both the devices. Suggestions for future research on therapeutic devices are discussed

Models and Analysis of Vocal Emissions for Biomedical Applications

The MAVEBA Workshop proceedings, held on a biannual basis, collect the scientific papers presented both as oral and poster contributions, during the conference. The main subjects are: development of theoretical and mechanical models as an aid to the study of main phonatory dysfunctions, as well as the biomedical engineering methods for the analysis of voice signals and images, as a support to clinical diagnosis and classification of vocal pathologies

Assessing Parkinson’s Disease at Scale Using Telephone-Recorded Speech:Insights from the Parkinson’s Voice Initiative

Numerous studies have reported on the high accuracy of using voice tasks for the remote detection and monitoring of Parkinson’s Disease (PD). Most of these studies, however, report findings on a small number of voice recordings, often collected under acoustically controlled conditions, and therefore cannot scale at large without specialized equipment. In this study, we aimed to evaluate the potential of using voice as a population-based PD screening tool in resource-constrained settings. Using the standard telephone network, we processed 11,942 sustained vowel /a/ phonations from a US-English cohort comprising 1078 PD and 5453 control participants. We characterized each phonation using 304 dysphonia measures to quantify a range of vocal impairments. Given that this is a highly unbalanced problem, we used the following strategy: we selected a balanced subset (n = 3000 samples) for training and testing using 10-fold cross-validation (CV), and the remaining (unbalanced held-out dataset, n = 8942) samples for further model validation. Using robust feature selection methods we selected 27 dysphonia measures to present into a radial-basis-function support vector machine and demonstrated differentiation of PD participants from controls with 67.43% sensitivity and 67.25% specificity. These findings could help pave the way forward toward the development of an inexpensive, remote, and reliable diagnostic support tool for PD using voice as a digital biomarker

Future Opportunities for IoT to Support People with Parkinson’s

Recent years have seen an explosion of internet of things (IoT) technologies being released to the market. There has also been an emerging interest in the potentials of IoT devices to support people with chronic health conditions. In this paper, we describe the results of engagements to scope the future potentials of IoT for supporting people with Parkinson’s. We ran a 2-day multi-disciplinary event with professionals with expertise in Parkinson’s and IoT, to explore the opportunities, challenges and benefits. We then ran 4 workshops, engaging 13 people with Parkinson’s and caregivers, to scope out the needs, values and desires that the community has for utilizing IoT to monitor their symptoms. This work contributes a set of considerations for future IoT solutions that might support people with Parkinson’s in better understanding their condition, through the provision of objective measurements that correspond to their, currently unmeasured, subjective experiences

Kinect-based Solution for the Home Monitoring of Gait and Balance in Elderly People with and without Neurological Diseases

Alterations of gait and balance are a significant cause of falls, injuries, and consequent hospitalizations in the elderly. In addition to age-associated motor decline, other factors can impact gait and stability, including the motor dysfunctions caused by neurological diseases such as Parkinson’s disease or hemiplegia after stroke. Monitoring changes and deterioration in gait patterns and balance is crucial for activating rehabilitation treatments and preventing serious consequences. This work presents a Kinect-based solution, suitable for domestic contexts, for assessing gait and balance in individuals at risk of falling. The system captures body movements during home acquisition sessions scheduled by clinicians at definite times of the day and automatically estimates specific functional parameters to objectively characterize the subjects’ performance. The system includes a graphical user interface designed to ensure usability in unsupervised contexts: the human-computer interaction mainly relies on natural body movements to support the self-management of the system, if the motor conditions allow it. This work presents the system’s features and facilities, and the preliminary results on healthy volunteers’ trials