In this paper, we present an assessment of the practical value of existing traditional and nonstandard measures for discriminating healthy people from people with Parkinson's disease (PD) by detecting dysphonia. We introduce a new measure of dysphonia, pitch period entropy (PPE), which is robust to many uncontrollable confounding effects including noisy acoustic environments and normal, healthy variations in voice frequency. We collected sustained phonations from 31 people, 23 with PD. We then selected ten highly uncorrelated measures, and an exhaustive search of all possible combinations of these measures finds four that in combination lead to overall correct classification performance of 91.4%, using a kernel support vector machine. In conclusion, we find that nonstandard methods in combination with traditional harmonics-to-noise ratios are best able to separate healthy from PD subjects. The selected nonstandard methods are robust to many uncontrollable variations in acoustic environment and individual subjects, and are thus well suited to telemonitoring applications.

/pdf/suitability-of-dysphonia-measurements-for-telemonitoring-of-216hm09qs2.pdf

Suitability of Dysphonia Measurements for Telemonitoring of Parkinson's Disease

Over 3 million teachers in the United States use their voice as a primary tool of trade and are thought to be at higher risk for occupation-related voice disorders than the general population. However, estimates regarding the prevalence of voice disorders in teachers and the general population vary considerably. To determine the extent that teachers are at greater risk for voice disorders, 2,531 randomly selected participants from Iowa and Utah (1,243 teachers and 1,288 nonteachers) were interviewed by telephone using a voice disorder questionnaire. Prevalence-the number of cases per population at risk at a specific time-was determined. The prevalence of reporting a current voice problem was significantly greater in teachers compared with nonteachers (11.0% vs. 6.2%), chi(2)(1) = 18.2, p 4 weeks in duration), compared with acute voice disorders (20.9% vs. 13.3%), chi(2)(1) = 8.7, p =.003. To assess the association between past voice disorders and possible risks, adjusted odds ratios (ORs) were estimated using multiple logistic regression. The results identified that being a teacher, being a woman, being between 40 and 59 years of age, having 16 or more years of education, and having a family history of voice disorders were each positively associated with having experienced a voice disorder in the past. These results support the notion that teaching is a high-risk occupation for voice disorders. Important information is also provided regarding additional factors that might contribute to the development of voice disorders.

Prevalence of Voice Disorders in Teachers and the General Population

The study of speech production has largely been divided into investigations of lower-level articulatory motor control and of higher-level linguistic processing, with these research traditions rarely interacting. In this Opinion article, Hickok argues that these approaches have much to offer each other, and he presents a model of speech production that incorporates ideas from both research traditions and findings from neuroscientific studies of sensorimotor integration. Speech production has been studied predominantly from within two traditions, psycholinguistics and motor control. These traditions have rarely interacted, and the resulting chasm between these approaches seems to reflect a level of analysis difference: whereas motor control is concerned with lower-level articulatory control, psycholinguistics focuses on higher-level linguistic processing. However, closer examination of both approaches reveals a substantial convergence of ideas. The goal of this article is to integrate psycholinguistic and motor control approaches to speech production. The result of this synthesis is a neuroanatomically grounded, hierarchical state feedback control model of speech production.

/pdf/computational-neuroanatomy-of-speech-production-4gegz6kngn.pdf

Computational neuroanatomy of speech production

In the United States, the incidence rate of new or recurrent stroke is approximately 795 000 per year, and stroke prevalence for individuals over the age of 20 years is estimated at 6.5 million.1 Mortality rates in the first 30 days after stroke have decreased because of advances in emergency medicine and acute stroke care. In addition, there is strong evidence that organized postacute, inpatient stroke care delivered within the first 4 weeks by an interdisciplinary healthcare team results in an absolute reduction in the number of deaths.2,3 Despite these positive achievements, stroke continues to represent the leading cause of long-term disability in Americans: An estimated 50 million stroke survivors worldwide currently cope with significant physical, cognitive, and emotional deficits, and 25% to 74% of these survivors require some assistance or are fully dependent on caregivers for activities of daily living (ADLs).4,5

Notwithstanding the substantial progress in acute stroke care over the past 15 years, the focus of stroke medical advances and healthcare resources has been on acute and subacute recovery phases, which has resulted in substantial health disparities in later phases of stroke care. Additionally, healthcare providers (HCPs) are often unaware of not only patients’ potential for improvement during more chronic recovery phases but also common issues that stroke survivors and their caregivers experience. Furthermore, even with evidence that documents neuroplasticity potential regardless of age and time after stroke,6 the mean lifetime cost of ischemic stroke (which accounts for 87% of all strokes) in the United States is an estimated $140 000 (for inpatient, rehabilitation, and follow-up costs), with 70% of first-year stroke costs attributed to acute inpatient hospital care1; therefore, fewer financial resources appear to be dedicated to providing optimal care during the later phases of stroke recovery.

Because there remains a …

Comprehensive Overview of Nursing and Interdisciplinary Rehabilitation Care of the Stroke Patient A Scientific Statement From the American Heart Association

Individuals with cerebral palsy (CP) have sensorimotor and developmental issues that affect their daily lives by restricting their mobility, manipulation of objects, and/or communication.1 Within the framework of the World Health Organization’s International Classification of Functioning, Disability and Health (ICF),2,3 the Gross Motor Function Classification System (GMFCS)4 and the Manual Ability Classification System (MACS) for children with CP5 make it possible to classify mobility and handling objects respectively, at the ICF activity/participation level.6 However, no analogous classification of functional communication has been available for use in CP practice and research. The lack of a communication classification tool that is quick, reliable, valid, and easy to use limits the comparison of descriptive CP epidemiology studies as well as the interpretation and generalizability of CP treatment studies.

Communication disorders can be described from several perspectives: body structure and function level, activity level, and participation level, as well as environmental and personal levels.2,3,7–13 Estimates of communication disorders in CP have varied from 31%14 to 88%.15 This wide range is partly a result of the lack of a consensus definition of communication disorders within CP research and practice. A recent study from a Norwegian CP registry reported that 51% of children with CP had speech problems as classified by ratings of ‘slightly indistinct’, ‘obviously indistinct’, ‘severely indistinct’, or ‘no speech’, including 19% who had ‘no speech’.16 This population-based estimate reporting indistinct or no speech may underestimate CP communication disorders as it may not capture other types of communication problems resulting from hearing or language impairments. However, reporting speech, language, and hearing difficulties simply suggests the range of associated impairments in CP, not the more pertinent daily-life issues of how well a child with CP communicates with family, friends, acquaintances, and strangers.13

The purpose of this study was to create and validate a communication function classification system (CFCS) for children with CP, for use by a wide variety of individuals interested in CP. This required a shift from the traditional focus on body structure and function (i.e. assessing components of speech, language, and hearing problems), to a focus on activity/participation, specifically the way in which to classify a person’s communication capacity within real-life situations.

https://onlinelibrary.wiley.com/doi/pdf/10.1111/j.1469-8749.2011.03996.x

Developing and validating the Communication Function Classification System for individuals with cerebral palsy

Part 1: Substrates 1. Defining, Understanding, and Categorizing Motor Speech Disorders 2. Neurologic Bases of Motor Speech and its Pathologies 3. Examination of Motor Speech Disorders Part 2: The Disorders and Their Diagnoses 4. Flaccid Dysarthria 5. Spastic Dysarthria 6. Ataxic Dysarthria 7. Hypokinetic Dysarthria 8. Hyperkinetic Dysarthria 9. Unilateral Upper Motor Neuron Dysarthria 10. Mixed Dysarthrias 11. Apraxia of Speech 12. Neurogenic Mutism 13. Other Neurogenic Speech Disturbances 14. Acquired Psychogenic Speech Disturbances 15. Differential Diagnosis Part 3: Management 16. Managing Motor Speech Disorders: General Principles 17. Managing the Dysarthrias 18. Managing Apraxia of Speech 19. Managing Other Neurogenic Speech Disturbances 20. Managing Acquired Psychogenic Speech Disorders

Joseph R. Duffy

Papers

Motor Speech Disorders: Substrates, Differential Diagnosis, and Management