NLP Headache Speech (NLPH-SPEECH): a Cross-sectional Study on Natural Language Processing Analysing Spoken Monologues by Headache Patients
Trial Snapshot
- Phase
- Not Applicable
- Status
- Completed
- Sponsor
- University Hospital, Ghent
- Enrollment
- 2
- Locations
- 1
- Primary Endpoint
- Linguistic analysis of texts
Study Overview
Brief Summary
The research collects spoken descriptions of headache disorders by participants with headache disorders. The speech recordings are analyzed by natural language processing (NLP) tools to analyse linguistic properties of the texts and to obtain insight into the potential of NLP machine learning models for the recognition of headache syndromes of the participants.
Study Design
- Study Type
- Interventional
- Allocation
- Na
- Intervention Model
- Single Group
- Primary Purpose
- Other
- Masking
- None
Eligibility Criteria
- Ages
- 18 Years to — (Adult, Older Adult)
- Sex
- All
- Accepts Healthy Volunteers
- No
Inclusion Criteria
- •is a patient of the tertiary headache clinic at Ghent University Hospital
- •is 18 years or older
- •has Dutch as native speaking language
Exclusion Criteria
- •has difficulties in producing spoken language
- •has limited or no knowledge of Dutch
Arms & Interventions
Participants
Participants will provide spoken narratives on their headache disorder
Intervention: Digital Analysis of Speech (Other)
Outcomes
Primary Outcomes
Linguistic analysis of texts
Time Frame: through study completion, an average of 1 year
Descriptive linguistic analysis of lexical choices, sentence formation and thematic content within the texts
Secondary Outcomes
- Machine learning modelling for classification of headache disorders(through study completion, an average of 1 year)
- Machine learning modelling for estimation of headache impact scores(through study completion, an average of 1 year)
