Individual and Developmental Differences in Distributional Learning

Purpose

This study examined whether children and adults with developmental language disorder (DLD) could use distributional information in an artificial language to learn about grammatical category membership similarly to their typically developing (TD) peers and whether developmental differences existed within and between DLD and TD groups.

Method

Sixteen children ages 7–9 with DLD, 26 age-matched TD children, 17 college students with DLD, and 17 TD college students participated in this task. We used an artificial grammar learning paradigm in which participants had to use knowledge of category membership to determine the acceptability of test items that they had not heard during a training phase.

Results

Individuals with DLD performed similarly to TD peers in distinguishing grammatical from ungrammatical combinations, with no differences between age groups. The order in which items were heard at test differentially affected child versus adult participants and showed a relation with attention and phonological working memory as well.

Conclusion

Differences in ratings between grammatical and ungrammatical items in this task suggest that individuals with DLD can form grammatical categories from novel input and more broadly use distributional information. Differences in order effects suggest a developmental timeline for sensitivity to updating distributional information.

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Take Home Points: How to Use Statistical Learning

Purpose

The purpose of this epilogue is to synthesize the main points of the articles in this issue on statistical learning for clinicians. These points can be used to guide practice.

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Reading as Statistical Learning

Purpose

The purpose of this tutorial is to explain how learning to read can be thought of as learning statistical regularities and to demonstrate why this is relevant for theory, modeling, and practice. This tutorial also shows how triangulation of methods and cross-linguistic research can be used to gain insight.

Method

The impossibility of conveying explicitly all of the regularities that children need to acquire in a deep orthography, such as English, can be demonstrated by examining lesser-known probabilistic orthographic cues to lexical stress. Detection of these kinds of cues likely occurs via a type of implicit learning known as statistical learning (SL). The first part of the tutorial focuses on these points. Next, studies exploring how individual differences in the capacity for SL relate to variability in word reading accuracy in the general population are discussed. A brief overview of research linking impaired SL and dyslexia is also provided. The final part of the tutorial focuses on how we might supplement explicit literacy instruction with implicit learning methods and emphasizes the value of testing the efficacy of new techniques in the classroom. The basic and applied research reviewed here includes corpus analyses, behavioral testing, computational modeling, and classroom-based research. Although some of these methods are not commonly used in clinical research, the depth and breadth of this body of work provide a compelling case for why reading can be thought of as SL and how this view can inform practice.

Conclusion

Implicit methods that draw on the principles of SL can supplement the much-needed explicit instruction that helps children learn to read. This synergy of methods has the potential to spark innovative practices in literacy instruction and remediation provided by educators and clinicians to support typical learners and those with developmental disabilities.

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The Role of Statistical Learning in Understanding and Treating Spoken Language Outcomes in Deaf Children With Cochlear Implants

Purpose

Statistical learning—the ability to learn patterns in environmental input—is increasingly recognized as a foundational mechanism necessary for the successful acquisition of spoken language. Spoken language is a complex, serially presented signal that contains embedded statistical relations among linguistic units, such as phonemes, morphemes, and words, which represent the phonotactic and syntactic rules of language. In this review article, we first review recent work that demonstrates that, in typical language development, individuals who display better nonlinguistic statistical learning abilities also show better performance on different measures of language. We next review research findings that suggest that children who are deaf and use cochlear implants may have difficulties learning sequential input patterns, possibly due to auditory and/or linguistic deprivation early in development, and that the children who show better sequence learning abilities also display improved spoken language outcomes. Finally, we present recent findings suggesting that it may be possible to improve core statistical learning abilities with specialized training and interventions and that such improvements can potentially impact and facilitate the acquisition and processing of spoken language.

Method

We conducted a literature search through various online databases including PsychINFO and PubMed, as well as including relevant review articles gleaned from the reference sections of other review articles used in this review. Search terms included various combinations of the following: sequential learning, sequence learning, statistical learning, sequence processing, procedural learning, procedural memory, implicit learning, language, computerized training, working memory training, statistical learning training, deaf, deafness, hearing impairment, hearing impaired, DHH, hard of hearing, cochlear implant(s), hearing aid(s), and auditory deprivation. To keep this review concise and clear, we limited inclusion to the foundational and most recent (2005–2018) relevant studies that explicitly included research or theoretical perspectives on statistical or sequential learning. We here summarize and synthesize the most recent and relevant literature to understanding and treating language delays in children using cochlear implants through the lens of statistical learning.

Conclusions

We suggest that understanding how statistical learning contributes to spoken language development is important for understanding some of the difficulties that children who are deaf and use cochlear implants might face and argue that it may be beneficial to develop novel language interventions that focus specifically on improving core foundational statistical learning skills.

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Statistical Learning and Spelling

Purpose

The purpose of this article is to provide a tutorial on statistical learning and its role in learning to spell and to discuss the implications of the research for educators.

Method

The tutorial begins with a discussion of statistical learning and its characteristics. It then discusses research on how statistical learning plays out in learning to spell, how spelling should be taught, and similarities and differences among learners. The focus is on the learning of English, although studies of other alphabetic writing systems are also considered. Research shows that, from an early age, children use their statistical learning skills to learn about the visual characteristics of written words. Children also use their statistical learning skills to help learn about the relations between visual units and units of language, supplementing what they are explicitly taught in school.

Conclusion

Statistical learning plays an important role in learning to spell, and this can help to explain why some aspects of spelling are more difficult to learn than others. If children are to learn to spell effectively and efficiently, structured instruction is also important.

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Statistical Learning: How it Relates to Speech-Language Pathology

Purpose

The purpose of this special issue is to introduce speech-language pathologists to the topic of statistical learning and how this is relevant to their practice. In the following articles, the concept of statistical learning will be explained, and readers will find (a) research studies showing how children with special needs can use statistical learning to learn language; (b) tutorials that show why statistical learning is meaningful for special populations; and (c) tutorials that show how statistical learning is involved in language, reading, and spelling.

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Distributional Cues to Language Learning in Children With Intellectual Disabilities

Purpose

In typical development, distributional cues—patterns in input—are related to language acquisition processes. Statistical and implicit learning refer to the utilization of such cues. In children with intellectual disability, much less is known about the extent to which distributional cues are harnessed in mechanisms of language learning.

Method

This tutorial presents what is known about the process of language learning in children with language impairments associated with different sources of intellectual disability: Williams syndrome, autism spectrum disorder, Down syndrome, and fragile X syndrome.

Results

A broad view is taken on distributional cues relevant to language learning, including statistical learning (e.g., transitional probabilities) and other patterns that support lexical acquisition (e.g., sensitivities to sound patterns, cross-situational word learning) or relate to syntactic development (e.g., nonadjacent dependencies).

Conclusions

Critical gaps in the literature are highlighted. Research in this area is especially limited for Down syndrome and fragile X syndrome. Future directions for taking learning theories into account in interventions for children with intellectual disability are discussed, with a focus on the importance of language input.

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Learning Without Trying: The Clinical Relevance of Statistical Learning

Purpose

Statistical learning research seeks to identify the means by which learners, with little perceived effort, acquire the complexities of language. In the past 50 years, numerous studies have uncovered powerful learning mechanisms that allow for learning within minutes of exposure to novel language input.

Method

We consider the value of information from statistical learning studies that show potential for making treatment of language disorders faster and more effective.

Results

Available studies include experimental research that demonstrates the conditions under which rapid learning is possible, research showing that these findings apply to individuals with disorders, and translational work that has applied learning principles in treatment and educational contexts. In addition, recent research on memory formation has implications for treatment of language deficits.

Conclusion

The statistical learning literature offers principles for learning that can improve clinical outcomes for children with language impairment. There is potential for further applications of this basic research that is yet unexplored.

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Acquisition of Verb Meaning From Syntactic Distribution in Preschoolers With Autism Spectrum Disorder

Purpose

Our goal was to investigate whether preschool children with autism spectrum disorder (ASD) can begin to learn new word meanings by attending to the linguistic contexts in which they occur, even in the absence of visual or social context. We focused on verbs because of their importance for subsequent language development.

Method

Thirty-two children with ASD, ages 2;1–4;5 (years;months), participated in a verb-learning task. In a between-subjects design, they were randomly assigned to hear novel verbs in either transitive or intransitive syntactic frames while watching an unrelated silent animation or playing quietly with a toy. In an eye-tracking test, they viewed two video scenes, one depicting a causative event (e.g., boy spinning girl) and the other depicting synchronous events (e.g., boy and girl waving). They were prompted to find the referents of the novel verbs, and their eye gaze was measured.

Results

Like typically developing children in prior work, children with ASD who had heard the verbs in transitive syntactic frames preferred to look to the causative scene as compared to children who had heard intransitive frames.

Conclusions

This finding replicates and extends prior work on verb learning in children with ASD by demonstrating that they can attend to a novel verb's syntactic distribution absent relevant visual or social context, and they can use this information to assign the novel verb an appropriate meaning. We discuss points for future research, including examining individual differences that may impact success and contrasting social and nonsocial word-learning tasks directly.

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Statistical Learning and Bilingualism

Purpose

Over the last 2 decades, research on statistical learning has demonstrated its importance in supporting language development. Notably, most of the research to date has focused on monolingual populations (or has not reported the language background of participants). Several recent studies, however, have begun to focus on the impact of bilingualism on statistical learning. To date, the results have been quite mixed, with a handful of studies finding differences between monolinguals and bilinguals and several other studies reporting no differences. Thus, the purpose of this manuscript is to review the literature to date on how bilingualism impacts statistical learning abilities.

Method

We review the contemporary literature, organized by the age of participants and by task when relevant.

Conclusions

We note that there are many discrepant findings within this nascent field, although some trends have emerged. For instance, differences in performance may be attributed to factors such as age of acquisition. However, we note that the state of the field does not yet permit firm clinical recommendations.

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Effects of a Complexity-Based Approach on Generalization of Past Tense – ed and Related Morphemes

Purpose

In a previous article, we reported that beginning treatment for regular past tense –ed with certain types of verbs led to greater generalization in children with developmental language disorder than beginning treatment with other types of verbs. This article provides updated data from that study, including the addition of data from 3 children, results from naturalistic language samples, and data from a third time point.

Method

Twenty 4- to 9-year-old children with developmental language disorder (10 per condition) were randomly assigned to receive language intervention in which the verbs used to teach regular past tense –ed were manipulated. Half received easy first intervention, beginning with highly frequent, telic, phonologically simple verbs, and half received hard first intervention, beginning with less frequent, atelic, and phonologically complex verbs. The design used a train-to-criterion approach, with children receiving up to 36 visits. Performance was assessed using elicited production probes and language samples before intervention, immediately following intervention and 6–8 weeks later.

Results

Children in the hard first group showed greater gains on the use of regular past tense –ed in both structured probes (at immediate post only) and in language samples (at both immediate and delayed post). Gains attributable to therapy were not observed in untreated morphemes.

Conclusions

This study suggests that the choice of therapy materials, with an eye on the role that treatment stimuli play in generalization, is important for treatment efficacy. Clinicians should consider early selection of atelic, lower-frequency, phonologically complex verbs when teaching children to use regular past tense –ed. Further work expanding this to other morphemes and a larger population is needed to confirm this finding.

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Masthead

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via IFTTT

Individual and Developmental Differences in Distributional Learning

Purpose

This study examined whether children and adults with developmental language disorder (DLD) could use distributional information in an artificial language to learn about grammatical category membership similarly to their typically developing (TD) peers and whether developmental differences existed within and between DLD and TD groups.

Method

Sixteen children ages 7–9 with DLD, 26 age-matched TD children, 17 college students with DLD, and 17 TD college students participated in this task. We used an artificial grammar learning paradigm in which participants had to use knowledge of category membership to determine the acceptability of test items that they had not heard during a training phase.

Results

Individuals with DLD performed similarly to TD peers in distinguishing grammatical from ungrammatical combinations, with no differences between age groups. The order in which items were heard at test differentially affected child versus adult participants and showed a relation with attention and phonological working memory as well.

Conclusion

Differences in ratings between grammatical and ungrammatical items in this task suggest that individuals with DLD can form grammatical categories from novel input and more broadly use distributional information. Differences in order effects suggest a developmental timeline for sensitivity to updating distributional information.

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Take Home Points: How to Use Statistical Learning

Purpose

The purpose of this epilogue is to synthesize the main points of the articles in this issue on statistical learning for clinicians. These points can be used to guide practice.

from #Audiology via ola Kala on Inoreader https://ift.tt/2B91sfu
via IFTTT

Reading as Statistical Learning

Purpose

The purpose of this tutorial is to explain how learning to read can be thought of as learning statistical regularities and to demonstrate why this is relevant for theory, modeling, and practice. This tutorial also shows how triangulation of methods and cross-linguistic research can be used to gain insight.

Method

The impossibility of conveying explicitly all of the regularities that children need to acquire in a deep orthography, such as English, can be demonstrated by examining lesser-known probabilistic orthographic cues to lexical stress. Detection of these kinds of cues likely occurs via a type of implicit learning known as statistical learning (SL). The first part of the tutorial focuses on these points. Next, studies exploring how individual differences in the capacity for SL relate to variability in word reading accuracy in the general population are discussed. A brief overview of research linking impaired SL and dyslexia is also provided. The final part of the tutorial focuses on how we might supplement explicit literacy instruction with implicit learning methods and emphasizes the value of testing the efficacy of new techniques in the classroom. The basic and applied research reviewed here includes corpus analyses, behavioral testing, computational modeling, and classroom-based research. Although some of these methods are not commonly used in clinical research, the depth and breadth of this body of work provide a compelling case for why reading can be thought of as SL and how this view can inform practice.

Conclusion

Implicit methods that draw on the principles of SL can supplement the much-needed explicit instruction that helps children learn to read. This synergy of methods has the potential to spark innovative practices in literacy instruction and remediation provided by educators and clinicians to support typical learners and those with developmental disabilities.

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via IFTTT

The Role of Statistical Learning in Understanding and Treating Spoken Language Outcomes in Deaf Children With Cochlear Implants

Purpose

Statistical learning—the ability to learn patterns in environmental input—is increasingly recognized as a foundational mechanism necessary for the successful acquisition of spoken language. Spoken language is a complex, serially presented signal that contains embedded statistical relations among linguistic units, such as phonemes, morphemes, and words, which represent the phonotactic and syntactic rules of language. In this review article, we first review recent work that demonstrates that, in typical language development, individuals who display better nonlinguistic statistical learning abilities also show better performance on different measures of language. We next review research findings that suggest that children who are deaf and use cochlear implants may have difficulties learning sequential input patterns, possibly due to auditory and/or linguistic deprivation early in development, and that the children who show better sequence learning abilities also display improved spoken language outcomes. Finally, we present recent findings suggesting that it may be possible to improve core statistical learning abilities with specialized training and interventions and that such improvements can potentially impact and facilitate the acquisition and processing of spoken language.

Method

We conducted a literature search through various online databases including PsychINFO and PubMed, as well as including relevant review articles gleaned from the reference sections of other review articles used in this review. Search terms included various combinations of the following: sequential learning, sequence learning, statistical learning, sequence processing, procedural learning, procedural memory, implicit learning, language, computerized training, working memory training, statistical learning training, deaf, deafness, hearing impairment, hearing impaired, DHH, hard of hearing, cochlear implant(s), hearing aid(s), and auditory deprivation. To keep this review concise and clear, we limited inclusion to the foundational and most recent (2005–2018) relevant studies that explicitly included research or theoretical perspectives on statistical or sequential learning. We here summarize and synthesize the most recent and relevant literature to understanding and treating language delays in children using cochlear implants through the lens of statistical learning.

Conclusions

We suggest that understanding how statistical learning contributes to spoken language development is important for understanding some of the difficulties that children who are deaf and use cochlear implants might face and argue that it may be beneficial to develop novel language interventions that focus specifically on improving core foundational statistical learning skills.

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via IFTTT

Statistical Learning and Spelling

Purpose

The purpose of this article is to provide a tutorial on statistical learning and its role in learning to spell and to discuss the implications of the research for educators.

Method

The tutorial begins with a discussion of statistical learning and its characteristics. It then discusses research on how statistical learning plays out in learning to spell, how spelling should be taught, and similarities and differences among learners. The focus is on the learning of English, although studies of other alphabetic writing systems are also considered. Research shows that, from an early age, children use their statistical learning skills to learn about the visual characteristics of written words. Children also use their statistical learning skills to help learn about the relations between visual units and units of language, supplementing what they are explicitly taught in school.

Conclusion

Statistical learning plays an important role in learning to spell, and this can help to explain why some aspects of spelling are more difficult to learn than others. If children are to learn to spell effectively and efficiently, structured instruction is also important.

from #Audiology via ola Kala on Inoreader https://ift.tt/2Pa8P95
via IFTTT

Statistical Learning: How it Relates to Speech-Language Pathology

Purpose

The purpose of this special issue is to introduce speech-language pathologists to the topic of statistical learning and how this is relevant to their practice. In the following articles, the concept of statistical learning will be explained, and readers will find (a) research studies showing how children with special needs can use statistical learning to learn language; (b) tutorials that show why statistical learning is meaningful for special populations; and (c) tutorials that show how statistical learning is involved in language, reading, and spelling.

from #Audiology via ola Kala on Inoreader https://ift.tt/2Ba2Jmh
via IFTTT

Distributional Cues to Language Learning in Children With Intellectual Disabilities

Purpose

In typical development, distributional cues—patterns in input—are related to language acquisition processes. Statistical and implicit learning refer to the utilization of such cues. In children with intellectual disability, much less is known about the extent to which distributional cues are harnessed in mechanisms of language learning.

Method

This tutorial presents what is known about the process of language learning in children with language impairments associated with different sources of intellectual disability: Williams syndrome, autism spectrum disorder, Down syndrome, and fragile X syndrome.

Results

A broad view is taken on distributional cues relevant to language learning, including statistical learning (e.g., transitional probabilities) and other patterns that support lexical acquisition (e.g., sensitivities to sound patterns, cross-situational word learning) or relate to syntactic development (e.g., nonadjacent dependencies).

Conclusions

Critical gaps in the literature are highlighted. Research in this area is especially limited for Down syndrome and fragile X syndrome. Future directions for taking learning theories into account in interventions for children with intellectual disability are discussed, with a focus on the importance of language input.

from #Audiology via ola Kala on Inoreader https://ift.tt/2PaT6Ha
via IFTTT

Learning Without Trying: The Clinical Relevance of Statistical Learning

Purpose

Statistical learning research seeks to identify the means by which learners, with little perceived effort, acquire the complexities of language. In the past 50 years, numerous studies have uncovered powerful learning mechanisms that allow for learning within minutes of exposure to novel language input.

Method

We consider the value of information from statistical learning studies that show potential for making treatment of language disorders faster and more effective.

Results

Available studies include experimental research that demonstrates the conditions under which rapid learning is possible, research showing that these findings apply to individuals with disorders, and translational work that has applied learning principles in treatment and educational contexts. In addition, recent research on memory formation has implications for treatment of language deficits.

Conclusion

The statistical learning literature offers principles for learning that can improve clinical outcomes for children with language impairment. There is potential for further applications of this basic research that is yet unexplored.

from #Audiology via ola Kala on Inoreader https://ift.tt/2OBK0C5
via IFTTT

Acquisition of Verb Meaning From Syntactic Distribution in Preschoolers With Autism Spectrum Disorder

Purpose

Our goal was to investigate whether preschool children with autism spectrum disorder (ASD) can begin to learn new word meanings by attending to the linguistic contexts in which they occur, even in the absence of visual or social context. We focused on verbs because of their importance for subsequent language development.

Method

Thirty-two children with ASD, ages 2;1–4;5 (years;months), participated in a verb-learning task. In a between-subjects design, they were randomly assigned to hear novel verbs in either transitive or intransitive syntactic frames while watching an unrelated silent animation or playing quietly with a toy. In an eye-tracking test, they viewed two video scenes, one depicting a causative event (e.g., boy spinning girl) and the other depicting synchronous events (e.g., boy and girl waving). They were prompted to find the referents of the novel verbs, and their eye gaze was measured.

Results

Like typically developing children in prior work, children with ASD who had heard the verbs in transitive syntactic frames preferred to look to the causative scene as compared to children who had heard intransitive frames.

Conclusions

This finding replicates and extends prior work on verb learning in children with ASD by demonstrating that they can attend to a novel verb's syntactic distribution absent relevant visual or social context, and they can use this information to assign the novel verb an appropriate meaning. We discuss points for future research, including examining individual differences that may impact success and contrasting social and nonsocial word-learning tasks directly.

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via IFTTT

Statistical Learning and Bilingualism

Purpose

Over the last 2 decades, research on statistical learning has demonstrated its importance in supporting language development. Notably, most of the research to date has focused on monolingual populations (or has not reported the language background of participants). Several recent studies, however, have begun to focus on the impact of bilingualism on statistical learning. To date, the results have been quite mixed, with a handful of studies finding differences between monolinguals and bilinguals and several other studies reporting no differences. Thus, the purpose of this manuscript is to review the literature to date on how bilingualism impacts statistical learning abilities.

Method

We review the contemporary literature, organized by the age of participants and by task when relevant.

Conclusions

We note that there are many discrepant findings within this nascent field, although some trends have emerged. For instance, differences in performance may be attributed to factors such as age of acquisition. However, we note that the state of the field does not yet permit firm clinical recommendations.

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via IFTTT

Effects of a Complexity-Based Approach on Generalization of Past Tense – ed and Related Morphemes

Purpose

In a previous article, we reported that beginning treatment for regular past tense –ed with certain types of verbs led to greater generalization in children with developmental language disorder than beginning treatment with other types of verbs. This article provides updated data from that study, including the addition of data from 3 children, results from naturalistic language samples, and data from a third time point.

Method

Twenty 4- to 9-year-old children with developmental language disorder (10 per condition) were randomly assigned to receive language intervention in which the verbs used to teach regular past tense –ed were manipulated. Half received easy first intervention, beginning with highly frequent, telic, phonologically simple verbs, and half received hard first intervention, beginning with less frequent, atelic, and phonologically complex verbs. The design used a train-to-criterion approach, with children receiving up to 36 visits. Performance was assessed using elicited production probes and language samples before intervention, immediately following intervention and 6–8 weeks later.

Results

Children in the hard first group showed greater gains on the use of regular past tense –ed in both structured probes (at immediate post only) and in language samples (at both immediate and delayed post). Gains attributable to therapy were not observed in untreated morphemes.

Conclusions

This study suggests that the choice of therapy materials, with an eye on the role that treatment stimuli play in generalization, is important for treatment efficacy. Clinicians should consider early selection of atelic, lower-frequency, phonologically complex verbs when teaching children to use regular past tense –ed. Further work expanding this to other morphemes and a larger population is needed to confirm this finding.

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Masthead

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Special Issue: How Statistical Learning Relates To Speech-Language Pathology

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Special Issue: How Statistical Learning Relates To Speech-Language Pathology

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Maximum Lyapunov exponent revisited: Long-term attractor divergence of gait dynamics is highly sensitive to the noise structure of stride intervals

Publication date: Available online 14 August 2018

Source: Gait & Posture

Author(s): Philippe Terrier, Fabienne Reynard

Abstract

Background

The local dynamic stability method (maximum Lyapunov exponent) can assess gait stability. Two variants of the method exist: the short-term divergence exponent (DE), and the long-term DE. Only the short-term DE can predict fall risk. However, the significance of long-term DE has been unclear so far. Some studies have suggested that the complex, fractal-like structure of fluctuations among consecutive strides correlates with long-term DE. The aim, therefore, was to assess whether the long-term DE is a gait complexity index.

Methods

The study reanalyzed a dataset of trunk accelerations from 100 healthy adults walking at preferred speed on a treadmill for 10 minutes. By interpolation, the stride intervals were modified within the acceleration signals for the purpose of conserving the original shape of the signal, while imposing a known stride-to-stride fluctuation structure. Four types of hybrid signals with different noise structures were built: constant, anti-correlated, random, and correlated (fractal). Short- and long-term DEs were then computed.

Results

The results show that long-term DEs, but not short-term DEs, are sensitive to the noise structure of stride intervals. For example, it was that observed that random hybrid signals exhibited significantly lower long-term DEs than hybrid correlated signals did (0.100 vs 0.144, i.e. a 44% difference). Long-term DEs from constant hybrid signals were close to zero (0.006). Conversely, short-term DEs of anti-correlated, random, and correlated hybrid signals were closely grouped (2.49, 2.50, and 2.51).

Conclusions

The short-term DE and the long-term DE, although they are both computed from divergence curves, should not be interpreted in a similar way. The long-term DE is very likely an index of gait complexity, which may be associated with gait automaticity or cautiousness. Consequently, to better differentiate between short- and long-term DEs, the use of the term attractor complexity index (ACI) is proposed for the latter.

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Maximum Lyapunov exponent revisited: Long-term attractor divergence of gait dynamics is highly sensitive to the noise structure of stride intervals

Publication date: Available online 14 August 2018

Source: Gait & Posture

Author(s): Philippe Terrier, Fabienne Reynard

Abstract

Background

The local dynamic stability method (maximum Lyapunov exponent) can assess gait stability. Two variants of the method exist: the short-term divergence exponent (DE), and the long-term DE. Only the short-term DE can predict fall risk. However, the significance of long-term DE has been unclear so far. Some studies have suggested that the complex, fractal-like structure of fluctuations among consecutive strides correlates with long-term DE. The aim, therefore, was to assess whether the long-term DE is a gait complexity index.

Methods

The study reanalyzed a dataset of trunk accelerations from 100 healthy adults walking at preferred speed on a treadmill for 10 minutes. By interpolation, the stride intervals were modified within the acceleration signals for the purpose of conserving the original shape of the signal, while imposing a known stride-to-stride fluctuation structure. Four types of hybrid signals with different noise structures were built: constant, anti-correlated, random, and correlated (fractal). Short- and long-term DEs were then computed.

Results

The results show that long-term DEs, but not short-term DEs, are sensitive to the noise structure of stride intervals. For example, it was that observed that random hybrid signals exhibited significantly lower long-term DEs than hybrid correlated signals did (0.100 vs 0.144, i.e. a 44% difference). Long-term DEs from constant hybrid signals were close to zero (0.006). Conversely, short-term DEs of anti-correlated, random, and correlated hybrid signals were closely grouped (2.49, 2.50, and 2.51).

Conclusions

The short-term DE and the long-term DE, although they are both computed from divergence curves, should not be interpreted in a similar way. The long-term DE is very likely an index of gait complexity, which may be associated with gait automaticity or cautiousness. Consequently, to better differentiate between short- and long-term DEs, the use of the term attractor complexity index (ACI) is proposed for the latter.

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GN Hearing Introduces World’s First ‘Premium-Plus’ Hearing Aid

GN Hearing introduced the ReSound LiNX Quattro™, the world’s first Premium-Plus hearing aid solution, which will be available on September 1. Powered by new technology, it offers a brilliant sound experience with unprecedented Layers of Sound™, unrivalled streaming capabilities, a unique cloud-based feature that allows remote device fine-tuning and the world’s most advanced rechargeable battery. According to the National Institute of Health, an estimated 28.8 million U.S. adults with mild to severe hearing loss could benefit from hearing aids.
 
This device features the following:

• Sound quality: The most dynamic range available provides clearer, fuller and richer layers of sound, helping people understand more speech and hear the finer details in any social or professional setting. Studies show that ReSound LiNX Quattro™ is preferred 95 percent of the time for music listening, compared to other premium hearing aids.
  
• Rechargeability: The built-in lithium-ion battery eliminates the need to change batteries and provides the longest battery life available– 24 hours of use when streaming 50 percent of the time and 30 hours of use without streaming.
  
• Remote fine-tuning: a user-friendly app enables Hearing Care Professionals (HCPs) to adjust users’ hearing aids from afar, without the need for a clinic visit.
  

 “ReSound LiNX Quattro is the perfect choice for people who want to upgrade to a new class of hearing aids that deliver unprecedented layers of sounds and the longest battery life available in stylish, discreet designs,” said Laurel Christensen, Chief Audiology Officer, GN Hearing. “Most importantly, the richer sound quality helps people hear better and be more present in their daily lives. Whether at a loud dinner party or business meeting in a quiet café, people can hear a fuller, clearer range of sounds, allowing them to focus on the conversation while still hearing the sounds around them.”

Compared to previous generations, the ReSound LiNX Quattro™ provides 100 percent faster processing, double the memory and a 35 percent increase in frequency bandwidth. With a completely rewritten sound processing package, ReSound LiNX Quattro™ generates finer and more complex Layers of Sound™ in real time with fewer distortions, designed to inspire confidence in people with hearing loss, so that they can enjoy the moments that matter most.
 
The ReSound Assist™ feature connects hearing aid users with their HCPs via the ReSound Smart 3D™ app. ReSound Assist™ allows remote adjustment of hearing aids without having to visit the clinic. This is especially beneficial for people who have limited mobility, live in rural areas, have active lives and busy careers, or need to travel long distances to visit their HCP.
 
“I use ReSound Assist regularly,” said Ron Turner, former NFL coach, collegiate head coach and ReSound user. “On one occasion, my audiologist noticed that I kept turning up the volume, so she reached out to me and adjusted my hearing aid immediately. Whether I’m at the football stadium, out to dinner in the city, or visiting with my grandchildren, I know that my hearing can be monitored and adjusted easily and efficiently.”
 
In a study to examine the impact of remote fine-tuning on HCPs and users, results showed that 100 percent of HCPs using the feature said they would recommend remote fine-tuning to peers, and 94 percent said it helps them provide users with a better hearing experience. The same study showed that 77 percent of users think their new settings improve their hearing, while 89 percent said they would recommend remote fine-tuning to other hearing aid users.

Published: 8/13/2018 3:43:00 PM

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GN Hearing Introduces World’s First ‘Premium-Plus’ Hearing Aid

GN Hearing introduced the ReSound LiNX Quattro™, the world’s first Premium-Plus hearing aid solution, which will be available on September 1. Powered by new technology, it offers a brilliant sound experience with unprecedented Layers of Sound™, unrivalled streaming capabilities, a unique cloud-based feature that allows remote device fine-tuning and the world’s most advanced rechargeable battery. According to the National Institute of Health, an estimated 28.8 million U.S. adults with mild to severe hearing loss could benefit from hearing aids.
 
This device features the following:

• Sound quality: The most dynamic range available provides clearer, fuller and richer layers of sound, helping people understand more speech and hear the finer details in any social or professional setting. Studies show that ReSound LiNX Quattro™ is preferred 95 percent of the time for music listening, compared to other premium hearing aids.
  
• Rechargeability: The built-in lithium-ion battery eliminates the need to change batteries and provides the longest battery life available– 24 hours of use when streaming 50 percent of the time and 30 hours of use without streaming.
  
• Remote fine-tuning: a user-friendly app enables Hearing Care Professionals (HCPs) to adjust users’ hearing aids from afar, without the need for a clinic visit.
  

 “ReSound LiNX Quattro is the perfect choice for people who want to upgrade to a new class of hearing aids that deliver unprecedented layers of sounds and the longest battery life available in stylish, discreet designs,” said Laurel Christensen, Chief Audiology Officer, GN Hearing. “Most importantly, the richer sound quality helps people hear better and be more present in their daily lives. Whether at a loud dinner party or business meeting in a quiet café, people can hear a fuller, clearer range of sounds, allowing them to focus on the conversation while still hearing the sounds around them.”

Compared to previous generations, the ReSound LiNX Quattro™ provides 100 percent faster processing, double the memory and a 35 percent increase in frequency bandwidth. With a completely rewritten sound processing package, ReSound LiNX Quattro™ generates finer and more complex Layers of Sound™ in real time with fewer distortions, designed to inspire confidence in people with hearing loss, so that they can enjoy the moments that matter most.
 
The ReSound Assist™ feature connects hearing aid users with their HCPs via the ReSound Smart 3D™ app. ReSound Assist™ allows remote adjustment of hearing aids without having to visit the clinic. This is especially beneficial for people who have limited mobility, live in rural areas, have active lives and busy careers, or need to travel long distances to visit their HCP.
 
“I use ReSound Assist regularly,” said Ron Turner, former NFL coach, collegiate head coach and ReSound user. “On one occasion, my audiologist noticed that I kept turning up the volume, so she reached out to me and adjusted my hearing aid immediately. Whether I’m at the football stadium, out to dinner in the city, or visiting with my grandchildren, I know that my hearing can be monitored and adjusted easily and efficiently.”
 
In a study to examine the impact of remote fine-tuning on HCPs and users, results showed that 100 percent of HCPs using the feature said they would recommend remote fine-tuning to peers, and 94 percent said it helps them provide users with a better hearing experience. The same study showed that 77 percent of users think their new settings improve their hearing, while 89 percent said they would recommend remote fine-tuning to other hearing aid users.

Published: 8/13/2018 3:43:00 PM

from #Audiology via ola Kala on Inoreader https://ift.tt/2nDwgva
via IFTTT