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.

Novoic Limited2 sites in 1 country172 target enrollmentJune 14, 2021

ConditionsAlzheimer Disease Mild Cognitive Impairment Dementia With Lewy Bodies Dementia, Vascular Frontotemporal Dementia Primary Progressive Aphasia Parkinson Disease Motor Neuron Disease Major Depressive Disorder Bipolar Disorder Amyotrophic Lateral Sclerosis

Overview

Phase: Not Applicable
Intervention: Not specified
Conditions: Alzheimer Disease
Sponsor: Novoic Limited
Enrollment: 172
Locations: 2
Primary Endpoint: The average length of speech elicitation for each speech task (in seconds) during the first week of self-assessments.
Status: Completed
Last Updated: 3 years ago

Overview Investigators Eligibility Criteria Outcomes Sites Similar Trials

Overview

Brief Summary

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.

Registry

clinicaltrials.gov

Start Date

June 14, 2021

End Date

September 15, 2022

Last Updated

3 years ago

Study Type

Observational

Sex

All

Investigators

Sponsor

Novoic Limited

Responsible Party

Sponsor

Eligibility Criteria

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

Outcomes

Primary Outcomes

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

The AUC of the binary classifier distinguishing between the Dementia with Lewy Bodies (LBD) diagnostic groups vs the applicable control group.(One month)
The AUC of the binary classifier distinguishing between the MND diagnostic groups vs the applicable control group.(One month)
The AUC of the binary classifier distinguishing between the BD diagnostic groups vs the applicable control group.(One month)
The sensitivity of the binary classifier distinguishing between the LBD diagnostic groups vs the applicable control group.(One month)
The sensitivity of the binary classifier distinguishing between the MDD diagnostic groups vs the applicable control group.(One month)
The sensitivity of the binary classifier distinguishing between the BD diagnostic groups vs the applicable control group.(One month)
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.(One month)
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).(One week)
The subject average fraction of days during the first week of remote, self-assessment, where participants submitted at least one task response.(One week)
The AUC of the binary classifier distinguishing between the AD diagnostic groups vs the applicable control group.(One month)
The AUC of the binary classifier distinguishing between the PD diagnostic groups vs the applicable control group.(One month)
The sensitivity of the binary classifier distinguishing between the AD diagnostic groups vs the applicable control group.(One month)
The sensitivity of the binary classifier distinguishing between the PD diagnostic groups vs the applicable control group.(One month)
The sensitivity of the binary classifier distinguishing between the FTD/VCI diagnostic groups vs the applicable control group.(One month)
The specificity of the binary classifier distinguishing between the AD diagnostic groups vs the applicable control group.(One month)
The specificity of the binary classifier distinguishing between the MDD diagnostic groups vs the applicable control group.(One month)
The sensitivity of the binary classifier distinguishing between the MND diagnostic groups vs the applicable control group.(One month)
The Cohen's kappa of the binary classifier distinguishing between the PD diagnostic groups vs the applicable control group.(One month)
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).(One week)
The AUC of the binary classifier distinguishing between the Frontotemporal Dementia and Vascular Dementia (FTD/VCI) diagnostic groups vs the applicable control group.(One month)
The AUC of the binary classifier distinguishing between the MDD diagnostic groups vs the applicable control group.(One month)
The specificity of the binary classifier distinguishing between the FTD/VCI diagnostic groups vs the applicable control group.(One month)
The specificity of the binary classifier distinguishing between the BD diagnostic groups vs the applicable control group.(One month)
The Cohen's kappa of the binary classifier distinguishing between the MDD diagnostic groups vs the applicable control group.(One month)
The Cohen's kappa of the binary classifier distinguishing between the BD diagnostic groups vs the applicable control group.(One month)
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.(One month)
The average length of speech elicitation for each speech task, during the telemedicine video conference.(baseline)
The specificity of the binary classifier distinguishing between the LBD diagnostic groups vs the applicable control group.(One month)
The specificity of the binary classifier distinguishing between the PD diagnostic groups vs the applicable control group.(One month)
The specificity of the binary classifier distinguishing between the MND diagnostic groups vs the applicable control group.(One month)
The Cohen's kappa of the binary classifier distinguishing between the AD diagnostic groups vs the applicable control group.(One month)
The Cohen's kappa of the binary classifier distinguishing between the LBD diagnostic groups vs the applicable control group.(One month)
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.(One month)
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.(One month)
The Cohen's kappa of the binary classifier distinguishing between the FTD/VCI diagnostic groups vs the applicable control group.(One month)
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.(One month)