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Not yet recruitingNCT07298278SPEECHBIPOUpdated Dec 23, 2025

Anticipating Depressive and Manic Episodes in Bipolar Disorders Using Vocal Biomarkers

An interventional study of Voice interviews and questionnaires carried out via the CALLYOPE application and Sleep measurements using an under-mattress sensor in Bipolar Disorder (BD), sponsored by Centre Hospitalier St Anne. Not yet recruiting. Open to participants aged 18 Years and older. Per ClinicalTrials.gov, last updated 2025-12-23.

Sponsored by Centre Hospitalier St Anne · Not applicable, Interventional, and Basic science

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Phase
Not applicable
Study type
Interventional
Enrollment
170
Allocation
Not applicable
Ages
18 Years and older
Sex
All
01

Study 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.

Read the detailed description

Bipolar disorder (BD) is a chronic and cyclical illness that affects a significant portion of the population, representing more than 1% worldwide. It is characterized by alternating episodes of elevated mood and energy (mania or hypomania) and episodes of decreased mood and energy (depression). These mood episodes manifest as substantial variations in energy levels and behavior, which recur over time and have a major social and occupational impact. According to the World Health Organization, BD rank as the fourth leading cause of morbidity and mortality.

Manic episodes are marked by hyperactivity, exalted mood, insomnia, inflated self-esteem, expansive speech and behavior, and sometimes psychotic symptoms (such as delusions of persecution or hallucinations). In contrast, depressive episodes are characterized by low energy, sadness, social withdrawal, hypersomnia or insomnia, and low self-esteem, often accompanied by weight loss or gain and decreased or increased appetite. The risks associated with manic, depressive, or mixed episodes are numerous; notably, individuals with BD have a suicide rate up to 20 times higher than that of the general population. Nearly half of patients with BD will attempt suicide at least once in their lifetime, and 15-20% of these attempts are fatal.

BD are associated with a marked reduction in quality of life, often greater than that observed in other mood or anxiety disorders. This decrease in quality of life is more strongly correlated with depressive symptoms than with manic or hypomanic symptoms. Furthermore, poor quality of life is related to residual depressive symptoms that may persist during remission periods, as well as to the high comorbidity of bipolar disorder with anxiety disorders.

The annual relapse rate ranges between 40% and 61% during the first two years following the initiation of treatment. This high incidence of relapse makes stabilization particularly difficult for patients with BD, with a period of significant vulnerability following each episode. The average duration of hospitalization is 58 days, at an approximate cost of €850 per day, resulting in direct hospitalization costs related to mood disorder relapses of about €3 billion per year. According to the French Court of Auditors, for every euro of direct cost, there are two euros of indirect costs related to social benefits and the negative impact on employment. Extrapolating these figures, the cost of hospitalizations due to relapses in BD is estimated at €45 billion across Europe.

Moreover, each relapse or rehospitalization irreversibly affects the individual's cognitive functioning and contributes to social and occupational disintegration. Staging models of the illness based on neuroprogression have been developed, taking into account the number of relapses and the degree of functional impairment. However, these models are not yet implemented in clinical practice.

Preventing (hypo)manic and depressive episodes through early intervention is therefore a key priority both at the individual level and as a major public health issue.

A new line of research has emerged in mood disorders, focusing on the digital phenotype. Among new digital biomarkers of relapse, voice appears to be a promising parameter. Several studies have demonstrated the efficacy of automated speech analysis, using machine learning models, to aid in the diagnosis of psychiatric disorders. In bipolar disorder, the illness has been shown to influence patients' vocal and linguistic features.

Thus, the main hypothesis of the study is that automated speech analysis and lifestyle data can be used to develop a model capable of predicting either relapse (manic, depressive, or mixed episode) or the transition to a high-risk state in patients with bipolar disorder.

02

Conditions studied

  • Bipolar Disorder (BD)

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Keywords

  • Bipolar Disorders
  • Digital Biomarkers
  • Speech Analysis
  • Relapse prediction
03

In context

Bipolar Disorder

1,684 studies on the registry are indexed under Bipolar Disorder; 267 are open to participants now.

This study's planned enrollment of 170 is above the median of 64 across 1,279 interventional studies indexed under Bipolar Disorder.

Browse Bipolar Disorder studies →

Lead sponsor

Centre Hospitalier St Anne is the lead sponsor of 101 studies on the registry; 55 are open to participants now.

Counted across the registry records on this site, refreshed daily.

04

Who can participate

Ages eligible
18 Years and older
Sexes eligible
All
Accepts healthy volunteers
No

Go through the criteria one by one — yes, no or not sure — and take the list to your doctor or the study team. Kept in this browser only.

Inclusion criteria

  • Adult patient
  • Patient capable of providing
  • Patient suffering from bipolar disorder according to (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

Exclusion criteria

Exclusion Criteria:

  • 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
Terms in these criteria, in plain language(2)

Underlined terms in the criteria open these too. Explained by clinicaltrials.gg, not part of the registry record. The study team decides who can take part.

Informed consent

Before you join, the study team explains what taking part involves — its purpose, what happens, the risks and possible benefits — and answers your questions, so you can decide freely. Consent is usually recorded on a form (the informed consent form, ICF) signed by you or, where the law allows, by someone legally authorised to decide for you.

You can keep asking questions during the study, you are told of new information that matters, and you can choose to leave at any time.

DSM diagnostic criteria

The American Psychiatric Association’s manual of mental health diagnoses. DSM-5 (2013, revised as DSM-5-TR in 2022) replaced DSM-IV, and some studies still name the older edition. “Meets DSM criteria for …” means diagnosed by that edition’s diagnostic criteria, usually by a clinician in an interview.

05

Study design

Phase
Not applicable
Primary purpose
Basic science
Allocation
Not applicable
Intervention model
Single group
Masking
None (open label)
Enrollment
170 participants (estimated)

Study arms

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

    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

  • OtherVoice interviews and questionnaires carried out via the CALLYOPE application

    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).

  • DeviceSleep measurements using an under-mattress sensor

    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.

  • DeviceSmartwatch for measuring activity, sleep, and skin temperature

    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).

06

What researchers measure

Primary outcomes

  1. 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.

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

  2. Occurrence of relapses during the study period

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

    Time frame: From enrollment to the end of study at 6 months

  3. 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

    Time frame: Month 0, Month 6

  4. 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).

    Time frame: Month 0, Month 6

  5. 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.

    Time frame: Month 0, Month 6

Secondary outcomes

  1. Age

    Age in years

    Time frame: Month 0

  2. Sex

    Sex (Male/Female)

    Time frame: Month 0

  3. Weight

    Weight in kilograms

    Time frame: Month 0

  4. Plasma lithium concentration

    Plasma lithium levels measured in mEq/L when available during the 6-month study period.

    Time frame: Up to 6 months (end of the study)

  5. Plasma drug concentration

    Plasma concentrations of ongoing psychotropic treatments measured when available during the 6-month study period

    Time frame: Up to 6 months (end of study)

  6. Changes from Baseline in symptoms (depression, anxiety, functional autonomy, fatigue)

    Symtpoms will be assessed by the score of the PHQ-9 (Patient Health Questionnaire - 9). Score range (min - max): 0 - 27 Higher score relates to a worse outcome

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

  7. Changes from Baseline in anxiety symptoms

    Anxiety symptoms will be assessed by the score of the GAD-7 (Generalized Anxiety Disorder) questionnaire. Score range (min - max): 0 - 21 Higher score relates to a worse outcome

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

  8. Sleep disturbances severity (Athens Insomnia Scale total score)

    Total score on the Athens Insomnia Scale (AIS) (range 0-24) ; Higher scores indicate more severe sleep disturbances

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

  9. Medication adherence measured by Medication Adherence Report Scale total score

    Adherence to medications will be assessed with the Medication Adherence Report Scale (MARS). A higher score indicates better therapeutic adherence.

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

  10. Fatigue measured by the Multidimensional Fatigue Inventory

    Total fatigue score on the Multidimensional Fatigue Inventory (MFI). Score range (min - max): 20 - 100; Higher total scores correspond with more acute levels of fatigue.

    Time frame: Month 0, Month 6

  11. Quality of social relationships measured by the Social Network Index

    Social Network Index (SNI). This questionnaire comprises a social diversity score (minimum = 0, maximum = 12), the total number of people in the social network, and the number of embedded social networks.

    Time frame: Month 0, Month 6

  12. Assessment of Loneliness Using the UCLA 3-Item Loneliness Scale

    Assessment of loneliness using the UCLA 3-Item Loneliness Scale. Scores range from 3 to 9, with higher scores indicating greater feelings of loneliness.

    Time frame: Month 0, Month 6

  13. Mean number of steps

    Collection of passive number of steps with the Callyope application and de wearable watch throughout the study

    Time frame: Continuous monitoring, from Month 0 to the end of study (Month 6)

  14. Sleep duration

    Measure of the total sleep time (hours) per night and the duration of sleep stages (hours) throughout the study thanks to the Withings Sleep Analyzer and wearable watch.

    Time frame: Continuous monitoring, from Month 0 to the end of study (Month 6)

  15. Heart rate variability

    Measure of the mean and continus heart rate variability (ms) thanks to the Withing watch.

    Time frame: Continuous monitoring, from Month 0 to the end of study (Month 6)

  16. Blood oxygen saturation

    Measure of the blood oxygen saturation (%) throughout the study thanks to th Withing watch

    Time frame: Continuous monitoring, from Month 0 to the end of study (Month 6)

  17. Body temperature

    Measure of the body temperature (°C) throughout the study thanks to the Withing watch.

    Time frame: Continuous monitoring, from Month 0 to the end of study (Month 6)

  18. Sleep apnea

    Measure of the apnea-hypopnea index during sleep throughout the study thanks to the Withings sleep analyzer.

    Time frame: Continuous monitoring, from Month 0 to the end of study (Month 6)

07

Study locations

No study locations are listed for this record.

08

Timeline

Tracking since Sep 25, 2026
ElapsedEstimatedEstimated, not yet reachedSimilar studies: half by the dot; the band is the middle halfHalf of similar studies reached it by the dot; the band is the middle half, from a quarter to three quarters

Start is estimated for Dec 2025; primary completion for May 2027, 17 months later.

Of 354 non-industry interventional studies with no phase under Bipolar Disorder, half reached primary completion within 37 months of starting (the median), counting those still running; a quarter within 23 and three quarters within 58. This study's planned 17 months is below that.

Counting every sponsor, half of 356 studies reached it within 37 months; a quarter within 23 and three quarters within 58.

How these figures are worked out, and which studies are left out of them.

Registered
Dec 1, 2025
First posted
Dec 23, 2025
StartEst.
Dec 20, 2025
Primary completionEst.
May 2027
CompletionEst.
May 2027
Last update
Dec 23, 2025
What these dates mean
Start.
When the first participant enrolled; while estimated, when the study expects to open to recruitment.
Primary completion.
When the last participant was examined or treated to collect data for the study's main question, its primary outcome. A study that stopped early gives the date its data collection stopped.
Completion.
When the last participant's last visit took place, for every outcome, secondary ones and side effects included: the end of the study. Often later than primary completion, sometimes the same day.
Actual and Est.
Actual means the registry says the date has happened. Est. (estimated) is a date the sponsor plans or expects. It can still move, and the sponsor is expected to change it to actual once it has passed.
No changes since tracking began. The registry record was last updated on Dec 23, 2025, before this site started recording changes on Sep 25, 2026. Its history is on ClinicalTrials.gov ↗
09

Registry details

Key details

Study ID
NCT07298278
Responsible party
Sponsor
First posted
Dec 23, 2025
Start date
Dec 20, 2025 (estimated)
Primary completion
May 2027 (estimated)
Completion
May 2027 (estimated)
Last update
Dec 23, 2025

Study contacts

Pierre-Alexis Geoffroy, Pr
Contact
pa.geoffroy@ghu-paris.fr
+33140258263
Pierre-Alexis Geoffroy, Pr
principal investigator · Paris Cité University; Centre ChronoS

Oversight

Data monitoring committee
No
FDA-regulated drug
No
FDA-regulated device
No
View the source record on ClinicalTrials.gov ↗

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