Advanced voice analysis in HD

  • Research type

    Research Study

  • Full title

    Advanced voice analysis using machine learning algorithms in patients with Huntington’s disease

  • IRAS ID

    354779

  • Contact name

    Roger Barker

  • Contact email

    rab46@cam.ac.uk

  • Sponsor organisation

    Cambridge University Hospitals NHS Fundation Trust and The University of Cambridge (Joint Sponsors)

  • Clinicaltrials.gov Identifier

    N/A, N/A

  • Duration of Study in the UK

    3 years, 0 months, 1 days

  • Research summary

    Huntington’s disease (HD) is a rare genetic disorder that causes progressive movement, cognitive and mental health problem. One of the symptoms of HD can be changes in voice and speech patterns.

    This study aims to explore whether computer-based analysis through artificial intelligence can identify voice patterns linked to Huntington’s disease. By detecting subtle voice changes, we aim to create a tool that could help doctors monitor the condition more accurately and potentially improve care for individuals with HD.

    The study will be conducted at the John Van Geest Centre for Brain Repair in Cambridge, UK. It will recruit 50 individuals with Huntington’s disease and 50 healthy controls over the age of 18. HD participants must have a confirmed genetic diagnosis, and all participants must be willing and able to complete the assessments. Each participant will attend a single session lasting about 1 hour. During this session, they will complete simple voice tasks such as pronouncing sustained vowel sounds, reading sentences, and repeating syllables. Clinical assessment will also be conducted during the session. All voice recordings will be securely stored and analyzed to identify unique speech features linked to Huntington’s disease. Furthermore, correlations between voice features and standardized clinical scales will be investigated.

    This research has the potential to establish voice analysis as a non-invasive and accessible tool for monitoring Huntington’s disease, benefiting both patients and clinicians by providing an objective and easy-to-use method for clinical assessment.

  • REC name

    North West - Greater Manchester Central Research Ethics Committee

  • REC reference

    25/NW/0115

  • Date of REC Opinion

    15 Apr 2025

  • REC opinion

    Favourable Opinion