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Identification of respiratory abnormalities using speech parameters

AI algorithm aided assessment of respiratory parameters using speech recordings in a community setting from coastal Karnataka

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
CTRI
Registry ID
CTRI/2022/06/043577
Enrollment
880
Registered
2022-06-29
Start date
Unknown
Completion date
Unknown
Last updated
2024-01-22

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

None listed

Interventions

Intervention1: Nil: Nil

Sponsors

Philips India
Lead Sponsor

Eligibility

Inclusion criteria

Inclusion criteria: available & consenting for interview

Exclusion criteria

Exclusion criteria: •Pregnant women •Patients who are discharged from hospitals in less than 4 weeks. •Patients who used inhalers 12-14 hours prior to the assessment. •Subjects in acute exacerbation/recent myocardial infarction or pulmonary embolism (within 4-6 weeks)/ recent eye or abdominal or brain surgery.

Design outcomes

Primary

MeasureTime frame
Comparison of Virtual output of the algorithm with respiratory belt signal Identification of respiratory pathologyTimepoint: 6 months—

Secondary

MeasureTime frame
nilTimepoint: nil—

Countries

India

Contacts

Public ContactDr Chythra R Rao

Kasturba Medical College, Manipal, MAHE

chythra.raj@manipal.edu9448857793

Outcome results

None listed

Source: CTRI (via WHO ICTRP) · Data processed: Feb 4, 2026