Anticipating Depressive and Manic Episodes in Bipolar Disorders Using Vocal Biomarkers

NCT07298278 | Not Yet Recruiting

• 1 other identifier: D24-P020
• Study Type: interventional
• Target: 170
• Locations: 0 countries
• Sites: N/A

Brief Summary

Bipolar disorder (BD) is a chronic, cyclical mental illness affecting over 1% of the global population. It is characterized by alternating episodes of elevated mood and energy (mania or hypomania) and episodes of decreased mood and energy (depression). Manic episodes involve hyperactivity, decreased need for sleep, grandiosity, accelerated speech, and sometimes psychotic symptoms such as hallucinations or delusions. Depressive episodes, in contrast, are characterized by sadness, low energy, social withdrawal, sleep and appetite disturbances, and low self-esteem. Bipolar patients are at very high risk of suicide, with rates up to 20 times higher than in the general population; nearly half will attempt suicide during their lifetime, and 15-20% of these attempts are fatal. BD is associated with a substantial decrease in quality of life, often greater than that seen in other mood or anxiety disorders. This reduction is primarily driven by depressive symptoms, including residual ones that may persist during remission periods. The frequent comorbidity with anxiety disorders further exacerbates the burden of the illness. Recently, research has turned toward the concept of the digital phenotype to identify early markers of relapse using passive and continuous monitoring. Among potential digital biomarkers, voice has shown particular promise. Automated speech analysis, combined with machine learning algorithms, has demonstrated effectiveness in detecting psychiatric symptoms and differentiating mood states. In BD, vocal and linguistic patterns vary with mood fluctuations, suggesting that voice could serve as a sensitive indicator of relapse risk. The main hypothesis of the present study is that automated analysis of speech and lifestyle data can help develop a predictive model capable of identifying early signs of relapse, whether manic, depressive, or mixed, or transitions to high-risk states in individuals with bipolar disorder.

Conditions

Bipolar Disorder (BD)

Keywords

Bipolar Disorders; Digital Biomarkers; Speech Analysis; Relapse prediction

Outcome Measures

Primary Outcomes (5)

• Voice interviews recorded on Callyope application

  The analysis of the interviews (acoustic and linguistic features) will be implemented in a voice model predicting a score.

  Once a week, from Month 0 to Month 6 (end of the study visit)

• Occurrence of relapses during the study period

  Occurrence of relapse episodes during the 6-month follow-up period

  From enrollment to the end of study at 6 months

• Changes from Baseline in the depression score measured by the Montgomery-Asberg Depression Rating Scale

  Depression severity will be assessed by the investigator with the MADRS (Montgomery-Asberg Depression Rating Scale) scale. Score range (min - max): 0-60 higher score relates to worse depression severity

  Month 0, Month 6

• Changes from Baseline in the bipolar disorder severity assessed by the Clinical Global Impression scale

  Bipolar Disorder severity will be assessed by the investigator with CGI (Clinical Global Impression) scale. Score range (min - max): 0 - 7 for the severity subscale symptomatic remission correspond to a score ≤3 (CGI).

  Month 0, Month 6

• Changes from Baseline in the maniac symptoms severity at the Young Mania Rating Scale

  Maniac symptoms severity will be assessed by the investigator with the YMRS (Young Mania Rating Scale). Score range (min - max): 0-60 higher score relates to worse maniac symptoms severity.

  Month 0, Month 6

Secondary Outcomes (18)

• Age

  Month 0

• Sex

  Month 0

• Weight

  Month 0

• Plasma lithium concentration

  Up to 6 months (end of the study)

• Plasma drug concentration

  Up to 6 months (end of study)

Study Arms (1)

Patients with Bipolar Disorder (6-month observational follow-up)

EXPERIMENTAL

Performing voice and language tests on the Callyope application: testing the voice and language analysis algorithm. Daily recording (6 months) of all passive data via the connected watch and the under-mattress sensor and the number of steps via the Callyope application (remotely)

Other: Voice interviews and questionnaires carried out via the CALLYOPE application; Device: Sleep measurements using an under-mattress sensor; Device: Smartwatch for measuring activity, sleep, and skin temperature

Interventions

Voice interviews and questionnaires carried out via the CALLYOPE application OTHER

Voice interviews carried out via the Callyope application: they consist of a series of tests, divided into two parts: Structured tasks (same content for each participant) and Semi-structured tasks (content varies for each participant). The simultaneous analysis of several speech tasks allows us to break down the different stages of speech production and the important factors that influence its achievement. In addition, patients will complete self-questionnaires via the application. Finally, lifestyle habits (number of steps) will be recorded via the application. These different tests will be carried out on the application at the inclusion visit (M0), then every week (+/- 3 days) until the end of study visit at 6 months (M6).

Patients with Bipolar Disorder (6-month observational follow-up)

Sleep measurements using an under-mattress sensor DEVICE

The under-mattress sensor will allow continuous sleep recording (sleep duration, sleep onset and wake times, sleep apnea, sleep cycles, etc.) for patients over a 6-month period, from M0 to M6.

Patients with Bipolar Disorder (6-month observational follow-up)

Smartwatch for measuring activity, sleep, and skin temperature DEVICE

The smartwatch will allow continuous recording of the patient's activity patterns, sleep, and skin temperature. It will be worn continuously from inclusion (M0) until the end of the study at 6 months (M6).

Patients with Bipolar Disorder (6-month observational follow-up)

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)

You may qualify if:

• Adult patient
• Patient capable of providing informed consent
• Patient suffering from bipolar disorder according to DSM-5-TR (2022) criteria
• Patient recently discharged from hospitalization or in remission after a mood episode within the last 12 months, with a MADRS score ≤10 and a YMRS score ≤8, or based on the psychiatrist's subjective evaluation
• Patient treated with lithium/antipsychotics/benzodiazepines (monotherapy or combination therapy)
• Patient capable of performing speech assessments and responding to questionnaires on a smartphone
• Patient able to speak, read, and understand French
• Patient enrolled in a social security system

You may not qualify if:

• Patient with a cognitive disorder
• Patient suffering from a known demential disorder
• Patient receiving treatment for a known addictive disorder
• Patient with a condition affecting speech production
• Patient with a neurological disorder (stroke or neurodegenerative diseases)
• Patient under legal protection, guardianship, or curatorship
• Subjects deprived of liberty by judicial or administrative decision
• Pregnant or breastfeeding women

Sponsors & Collaborators

• Centre Hospitalier St Anne: lead

MeSH Terms

Conditions

Bipolar Disorder

Condition Hierarchy (Ancestors)

Bipolar and Related Disorders; Mood Disorders; Mental Disorders

Study Officials

• Pierre-Alexis Geoffroy, Pr

  Paris Cité University; Centre ChronoS

  PRINCIPAL INVESTIGATOR

Central Study Contacts

Pierre-Alexis Geoffroy, Pr

CONTACT

+33140258263; pa.geoffroy@ghu-paris.fr

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: NA
• Masking: NONE
• Purpose: BASIC SCIENCE
• Intervention Model: SINGLE GROUP
• Sponsor Type: OTHER
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: December 1, 2025
• First Posted: December 23, 2025
• Study Start: December 20, 2025
• Primary Completion (Estimated): May 1, 2027
• Study Completion (Estimated): May 1, 2027
• Last Updated: December 23, 2025

Record last verified: 2025-12