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Protocol for Rhapsody: a longitudinal observational study examining the feasibility of speech phenotyping for remote assessment of neurodegenerative and psychiatric disorders

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Elliot Hampsey, Marton Meszaros, Caroline Skirrow, Rebecca Strawbridge, Rosie H. Taylor, Lazarus Chok, Dag Aarsland, Ammar Al-Chalabi, Ray Chaudhuri, Jack Weston, Emil Fristed, Aleksandra Podlewska, Olabisi Awogbemila, Allan H. Young

Original languageEnglish
Article numbere061193
JournalBMJ Open
Volume12
Issue number6
DOIs
Published6 Jun 2022

Bibliographical note

Funding Information: Contributors ERH (ORCID ID: 0000-0001-6985-5646): contributed to the writing of the study protocol, in addition to the writing and editing of the manuscript for journal submission. MM (ORCID ID: 0000-0003-4937-3062): main contributor on designing the study and protocol. Contributed to writing the full study protocol and editing the manuscript for journal submission. CS (ORCID ID: 0000-0001-8692-7787): contributed to the study design, writing and editing of the manuscript for journal submission. RS (ORCID ID: 0000-0002-2984-1124): contributed to the editing of the study protocol and manuscript for journal submission, in addition to study set up activities. RHT (ORCID ID: 0000-0001-6742-4842): contributed to editing of the manuscript for journal submission. LC (ORCID ID: 0000-0002-9514-364X): contributed to the writing of the study protocol, in addition to the editing of the manuscript for journal submission. DA (ORCID ID: 0000-0001-6314-216X): contributed to study and protocol design. Principal investigator for neurodegenerative disease cohort. AA-C (ORCID ID: 0000-0002-4924-7712): contributed to study and protocol design. Principal investigator for motor disorders cohort. RC (ORCID ID: 0000-0003-2815-0505): contributed to study and protocol design. Principal investigator for motor disorders cohort. JW (ORCID ID: 0000-0001-5344-7840): contributed to the writing of the study protocol, in addition to editing of the manuscript for journal submission. EF (ORCID ID: 0000-0002-9590-7275): main contributor on designing the study and protocol. Contributed to writing the full study protocol and editing the manuscript for journal submission. AP (ORCID ID: 0000-0002-0805-3356): contributed to editing of the manuscript for journal submission. OA (ORCID ID: 0000-0002-6814-3097): contributed to editing of the manuscript for journal submission. AY (ORCID ID: 0000-0003-2291-6952): chief investigator. Contributed to study and protocol design and edited the manuscript for journal submission. Funding This report is independent research funded by the National Institute for Health Research (Artificial Intelligence, Project RHAPSODY: investigating the clinical feasibility of using AI-based deep audio and language processing techniques to diagnose neurological and psychiatric diseases, AI_AWARD01984) and NHSX. Disclaimer The views expressed in this publication are those of the author(s) and not necessarily those of the National Institute for Health Research, NHSX or the Department of Health and Social Care. Competing interests RS has received an honorarium for speaking from Lundbeck. In the past 3 years, AY has received honoraria for speaking from AstraZeneca, Lundbeck, Eli Lilly and Sunovion; honoraria for consulting from Allergan, Livanova and Lundbeck, Sunovion and Janssen and research grant support from Janssen. ERH declares no conflicts of interest. EF is CEO of Novoic. MM, JW and CS are employees of Novoic, and EF, MM and JW are shareholders in the company. Publisher Copyright: © Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY. Published by BMJ.

King's Authors

Abstract

Introduction Neurodegenerative and psychiatric disorders (NPDs) confer a huge health burden, which is set to increase as populations age. New, remotely delivered diagnostic assessments that can detect early stage NPDs by profiling speech could enable earlier intervention and fewer missed diagnoses. The feasibility of collecting speech data remotely in those with NPDs should be established. Methods and analysis The present study will assess the feasibility of obtaining speech data, collected remotely using a smartphone app, from individuals across three NPD cohorts: neurodegenerative cognitive diseases (n=50), other neurodegenerative diseases (n=50) and affective disorders (n=50), in addition to matched controls (n=75). Participants will complete audio-recorded speech tasks and both general and cohort-specific symptom scales. The battery of speech tasks will serve several purposes, such as measuring various elements of executive control (eg, attention and short-term memory), as well as measures of voice quality. Participants will then remotely self-administer speech tasks and follow-up symptom scales over a 4-week period. The primary objective is to assess the feasibility of remote collection of continuous narrative speech across a wide range of NPDs using self-administered speech tasks. Additionally, the study evaluates if acoustic and linguistic patterns can predict diagnostic group, as measured by the sensitivity, specificity, Cohen's kappa and area under the receiver operating characteristic curve of the binary classifiers distinguishing each diagnostic group from each other. Acoustic features analysed include mel-frequency cepstrum coefficients, formant frequencies, intensity and loudness, whereas text-based features such as number of words, noun and pronoun rate and idea density will also be used. Ethics and dissemination The study received ethical approval from the Health Research Authority and Health and Care Research Wales (REC reference: 21/PR/0070). Results will be disseminated through open access publication in academic journals, relevant conferences and other publicly accessible channels. Results will be made available to participants on request. Trial registration number NCT04939818.

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