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Completed

NCT Number: NCT04939818

Clinical Feasibility of Speech Phenotyping for Remote Assessment of Neurodegenerative and Psychiatric Disorders

The primary objective of the study is to evaluate the feasibility of eliciting continuous narrative speech in different neurodegenerative and psychiatric indications, using remote, self-administered speech tasks, as measured by the average length of speech elicitation for each speech task during the first week of self-assessment. Secondary objectives include (1) evaluating the reliability of speech tasks in the remote self-administered setting, as measured by the intra- and inter-subject variance; (2) accessing the adherence of speech tasks in this setting, as measured by the subject average fraction of days during the first week, where at least one task response is submitted; (3) evaluating the feasibility of using speech tasks in the setting of a telemedicine videoconference, as measured by the average length of speech elicited in each group; (4) evaluate whether a set of acoustic and linguistic patterns can detect each indication, compare to either a control group or all other indications, as measured by the area under the receiver operating characteristic curve (AUC), sensitivity, specificity and Cohen's kappa of the relevant binary classifier; (5) evaluating how the performance of such algorithms can be impacted by speaker and environment covariates, as measured by the Kendall rank correlation coefficient of the AUC of each classifier and each of age group, gender and speech-to-reverberation modulation energy ratio.

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Key information

Conditions

Alzheimer Disease Amyotrophic Lateral Sclerosis Aphasia Aphasia, Primary Progressive Arterial Occlusive Diseases Arteriosclerosis Basal Ganglia Diseases Behavior Bipolar Disorder Bipolar and Related Disorders Brain Diseases Cardiovascular Diseases Central Nervous System Diseases Cerebrovascular Disorders Cognition Disorders Cognitive Dysfunction Communication Communication Disorders Dementia Dementia With Lewy Bodies Dementia, Vascular Depressive Disorder Depressive Disorder, Major Frontotemporal Dementia Frontotemporal Lobar Degeneration Intracranial Arterial Diseases Intracranial Arteriosclerosis Language Language Disorders Leukoencephalopathies Lewy Body Disease Major Depressive Disorder Mental Disorders Metabolic Diseases Mild Cognitive Impairment Mood Disorders Motor Neuron Disease Movement Disorders Nervous System Diseases Neurobehavioral Manifestations Neurocognitive Disorders Neurodegenerative Diseases Neurologic Manifestations Neuromuscular Diseases Nutritional and Metabolic Diseases Parkinson Disease Parkinsonian Disorders Pathological Conditions, Signs and Symptoms Primary Progressive Aphasia Proteostasis Deficiencies Signs and Symptoms Speech Speech Disorders Spinal Cord Diseases Synucleinopathies TDP-43 Proteinopathies Tauopathies Vascular Diseases Verbal Behavior

Age range

18 year–85 year

Sex eligibility

All sexes

Study type

Observational

Primary location

King's College Hospital NHS Foundation Trust, London, Greater London, United Kingdom

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Who can participate

Healthy volunteers accepted: Yes

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

  • Willing to participate, having been provided full information about the study components and details.
  • Native language is English.
  • Has the capacity to provide fully informed consent.
  • Has access to and able to use, or has a caregiver who has access to and able to use a smartphone device running an operation system of iOS 11.0 or later, or Android 7.0 or later.
  • Able to use, or has a caregiver who is able to use a personal computer, notebook or tablet.
  • Has access to a personal computer, notebook or tablet that is (1) Running an operating system of:

macOS X with macOS 10.9 or later; OR Windows 7 or above; AND (2) Capable of audio recording; AND (3) Able to connect to the internet; AND (4) Have access to one of following internet browser software: Internet Explorer version 11 or above; OR Microsoft Edge version 12 or above; OR Firefox version 27 or above; OR Google Chrome version 30 or above; OR Safari version 7 or above.

Exclusion criteria

  • Diagnosis of alcohol or drug use disorder;
  • History or presence of stroke within the past 2 years;
  • Documented history of transient ischemic attack or unexplained loss of consciousness within the last 12 months.
  • At risk of suicide: score of 10 or above on the PHQ scale, and 10 or above on the MINI suicide questionnaire

Treatment and study plan

Primary outcomes

  1. The average length of speech elicitation for each speech task (in seconds) during the first week of self-assessments.

    Time frame: One week

Secondary outcomes

  1. The intra-subject variance of length of speech elicitation for each speech task during the first week of self-assessments, as measured by Coefficients of Individual Agreement (CIA).

    Time frame: One week

  2. The inter-subject variance of length of speech elicitation for each speech task during the first week of self-assessments, as measured by Coefficients of Individual Agreement (CIA).

    Time frame: One week

  3. The subject average fraction of days during the first week of remote, self-assessment, where participants submitted at least one task response.

    Time frame: One week

  4. The average length of speech elicitation for each speech task, during the telemedicine video conference.

    Time frame: baseline

  5. The AUC of the binary classifier distinguishing between the AD diagnostic groups vs the applicable control group.

    Time frame: One month

  6. The AUC of the binary classifier distinguishing between the Dementia with Lewy Bodies (LBD) diagnostic groups vs the applicable control group.

    Time frame: One month

  7. The AUC of the binary classifier distinguishing between the PD diagnostic groups vs the applicable control group.

    Time frame: One month

  8. The AUC of the binary classifier distinguishing between the MND diagnostic groups vs the applicable control group.

    Time frame: One month

  9. The AUC of the binary classifier distinguishing between the Frontotemporal Dementia and Vascular Dementia (FTD/VCI) diagnostic groups vs the applicable control group.

    Time frame: One month

  10. The AUC of the binary classifier distinguishing between the MDD diagnostic groups vs the applicable control group.

    Time frame: One month

  11. The AUC of the binary classifier distinguishing between the BD diagnostic groups vs the applicable control group.

    Time frame: One month

  12. The sensitivity of the binary classifier distinguishing between the AD diagnostic groups vs the applicable control group.

    Time frame: One month

  13. The sensitivity of the binary classifier distinguishing between the LBD diagnostic groups vs the applicable control group.

    Time frame: One month

  14. The sensitivity of the binary classifier distinguishing between the PD diagnostic groups vs the applicable control group.

    Time frame: One month

  15. The sensitivity of the binary classifier distinguishing between the MND diagnostic groups vs the applicable control group.

    Time frame: One month

  16. The sensitivity of the binary classifier distinguishing between the FTD/VCI diagnostic groups vs the applicable control group.

    Time frame: One month

  17. The sensitivity of the binary classifier distinguishing between the MDD diagnostic groups vs the applicable control group.

    Time frame: One month

  18. The sensitivity of the binary classifier distinguishing between the BD diagnostic groups vs the applicable control group.

    Time frame: One month

  19. The specificity of the binary classifier distinguishing between the AD diagnostic groups vs the applicable control group.

    Time frame: One month

  20. The specificity of the binary classifier distinguishing between the LBD diagnostic groups vs the applicable control group.

    Time frame: One month

  21. The specificity of the binary classifier distinguishing between the PD diagnostic groups vs the applicable control group.

    Time frame: One month

  22. The specificity of the binary classifier distinguishing between the MND diagnostic groups vs the applicable control group.

    Time frame: One month

  23. The specificity of the binary classifier distinguishing between the FTD/VCI diagnostic groups vs the applicable control group.

    Time frame: One month

  24. The specificity of the binary classifier distinguishing between the MDD diagnostic groups vs the applicable control group.

    Time frame: One month

  25. The specificity of the binary classifier distinguishing between the BD diagnostic groups vs the applicable control group.

    Time frame: One month

  26. The Cohen's kappa of the binary classifier distinguishing between the AD diagnostic groups vs the applicable control group.

    Time frame: One month

  27. The Cohen's kappa of the binary classifier distinguishing between the LBD diagnostic groups vs the applicable control group.

    Time frame: One month

  28. The Cohen's kappa of the binary classifier distinguishing between the PD diagnostic groups vs the applicable control group.

    Time frame: One month

  29. The Cohen's kappa of the binary classifier distinguishing between the FTD/VCI diagnostic groups vs the applicable control group.

    Time frame: One month

  30. The Cohen's kappa of the binary classifier distinguishing between the MDD diagnostic groups vs the applicable control group.

    Time frame: One month

  31. The Cohen's kappa of the binary classifier distinguishing between the BD diagnostic groups vs the applicable control group.

    Time frame: One month

  32. The AUC of the binary classifier distinguishing between the following diagnostic groups vs all other diagnostic groups (pooled): AD, LBD, PD, MND, FTD/VCI, MDD, BD.

    Time frame: One month

  33. The sensitivity of the binary classifier distinguishing between the following diagnostic groups vs the other groups (pooled): AD, LBD, PD, MND, FTD/VCI, MDD, BD.

    Time frame: One month

  34. The specificity of the binary classifier distinguishing between the following diagnostic groups vs the other groups (pooled): AD, LBD, PD, MND, FTD/VCI, MDD, BD.

    Time frame: One month

  35. The Cohen's kappa of the binary classifier distinguishing between the following diagnostic groups vs the other groups (pooled): AD, LBD, PD, MND, FTD/VCI, MDD, BD.

    Time frame: One month

  36. For each classifier/regressor in the outcomes, the correlation between the AUC/CIA and each age group, gender and speech-to-reverberation modulation energy ratio group, as measured by the Kendall rank correlation coefficient.

    Time frame: One month

Sponsors and collaborators

Lead sponsor

Novoic Limited

Industry

Collaborators

  • King's College London

Registry information

Official study title

A Study to Investigate the Feasibility of Administration of a Speech Battery and the Use of Speech-based Biomarkers for the Clinical Assessment of Common Neurodegenerative and Psychiatric Disorders in a Remote Setting.

Acronym: RHAPSODY

Important dates

Study start
2021
Primary completion
2022
Study completion
2022
First posted
Jun 25, 2021
Registry last updated
Mar 22, 2023

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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