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

Study Overview
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Brief Summary
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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.

Official Title
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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.

Conditions
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Alzheimer 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

Participation Criteria
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Eligibility Criteria
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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

Ages Eligible for Study
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Minimum Age: 18 Years
Maximum Age: 85 Years

Sexes Eligible for Study
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All

Accepts Healthy Volunteers
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Accepts Healthy Volunteers

Study Plan
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How is the study designed?
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Arms and Interventions

| Participant Group/Arm | Intervention/Treatment |
| --- | --- |
| Group 1: Cognitive Disorders<br>Alzheimer's Disease (AD) Meet National Institute of Aging - Alzheimer's Association (NIA-AA) core clinical criteria (2011) for MCI due to Alzheimer's or Mild Alzheimer's Dementia Dementia with Lewy bodies (DLB) Diagnosis of possible or probable DLB based on the criteria defined by The Dementia with Lewy Bodies Consortium (2015) Non-AD non-DLB MCI Diagnosis of 'probable' and 'possible' behavioral variant frontotemporal dementia (bvFTD) according to the International Behavioral Variant FTD Criteria Consortium OR semantic variant or nonfluent-agrammatic variant primary progressive aphasia (PPA) FTD according to Mesulam's criteria OR Vascular Dementia according to NINDS-AIREN International Workshop AND Date of diagnosis not more than five years prior to consent Subjects must have MMSE scores of 23-30 (inclusive); or TICS40 score of 20-40 (inclusive) based on a test not older than 1 month at the time of consent. Age of 50-85 years (inclusive) | |
| Group 2: Motor disorders<br>Parkinson's Disease (PD) Diagnosis of idiopathic Parkinson's Disease based on the UK Parkinson's Disease Society Brain Bank Clinical Diagnostic Criteria Date of diagnosis not more than five years prior to consent Hoehn and Yahr stage 2 or less Age of 30-85 years (inclusive) Motor neuron Disease (MND) Diagnosis of Amyotrophic Lateral Sclerosis based on gold-standard clinical criteria Stage 3 or less on the King's ALS Staging system Age of 18-85 years (inclusive) | |
| Group 3: Affective disorders<br>Major Depressive Disorder (MDD) Meet Diagnostic and Statistical Manual of Mental Disorders (DSM-5) criteria for a current major depressive episode (MDE) as assessed by the MINI Current episode of at least moderate severity as assessed by the Clinical Global Impression (CGI) scale. Date of diagnosis (using MINI assessment) and severity (CGI) maximum of two months prior to consent. Age of 18-85 years (inclusive). Bipolar Disorder (BD) Meet DSM-5 criteria for BD as assessed by the MINI (type 1 or type 2) Current depressive episode as assessed by the MINI Current episode of at least moderate severity as assessed by the Clinical Global Impression (CGI) scale. Date of diagnosis (using MINI assessment) and severity (CGI) maximum of two months prior to consent. Age of 18-85 years (inclusive). | |
| Group 4: Unaffected Controls<br>Group 4 specific recruitment criteria matched for the 'Group 1: Cognitive Disorders' cohort: Age of 50-85 years (inclusive) Approximately age, gender and education matched to AD subjects on a group level. In otherwise good health condition. Group 4 specific recruitment criteria matched for the 'Group 2: Motor Disorders' cohort: Age of 30-85 years (inclusive) Approximately age, gender and education matched to PD subjects on a group level. In otherwise good health condition. Group 4 specific recruitment criteria matched for the 'Group 3: Affective Disorders' cohort: Age of 30-85 years (inclusive). Approximately age, gender and education matched to MDD/BD subjects on a group level. In otherwise good health condition. | |

What is the study measuring?
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Primary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| The average length of speech elicitation for each speech task (in seconds) during the first week of self-assessments. |  | One week | 

Secondary Outcome Measures

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

 Terms related to the study
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Keywords Provided by Centre Hospitalier Valida
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Speech, Acoustic, Language, Linguistic, Machine Learning, Artificial Intelligence