Session Time: 1:45pm-3:15pm
Location: Exhibit Hall C
Objective: To implement and validate quantification of motor dysfunction in a Huntington disease (HD) clinical trial using machine learning algorithmic analysis derived from biometric monitoring through a smartphone and wearable sensor combination.
Background: Motor symptoms in HD are typically evaluated by clinicians using rating scales, such as the Unified Huntington’s Disease Rating Scale total motor score (UHDRS-TMS). Assessments are infrequent, inherently subjective, may lead to intra- and inter-rater variability, and are prone to placebo response. The use of biometric health solutions could enable objective, real-time monitoring of motor dysfunction in both clinical research and patient care.
Methods: Up to 60 HD patients with a pre-defined spectrum of motor dysfunction will be included in a sub-study of Open Pride-HD (NCT02494778; Phase II, open-label, extension study) after meeting a set of pre-specified inclusion and exclusion criteria. Participants will be asked to use the biometric monitoring platform for 6 months. High-frequency movement-tracking data will be collected using an iPhone and wearable Pebble smartwatch combination and streamed continuously to a secure cloud-based analytics platform. 3D accelerometer and gyroscope data that reflect the intensity and direction of movements will be collected at the patients’ homes and during in-clinic visits.
Results: The digital health sub-study of Open Pride-HD started enrolling patients in December 2016 with anticipated duration for up to 2 years. The collected information, comprising accelerometer data, app-enabled patient-reported severity assessments of motor dysfunction, and in-clinic sessions, will be used to assess the validity of biometric monitoring as a means of providing reliable information on motor dysfunction in HD patients between and during clinic visits.
Conclusions: The design of this innovative study in HD is poised to set the foundation for the development of biometric monitoring solutions as a key component of HD management in clinical trials and everyday care.
Presented at: AAN annual meeting; April 22-28, 2017; Boston, MA, USA
To cite this abstract in AMA style:S. Papapetropoulos, S. Fine, E. Cohen, C. Admati, Y. Dolan, I. Grachev, I. Grossman, M. Hayden. Implementation and Validation of a Biometric Solution for Remote Monitoring of Motor Symptoms in Patients with Huntington Disease in a Phase II Clinical Trial [abstract]. Mov Disord. 2017; 32 (suppl 2). https://www.mdsabstracts.org/abstract/implementation-and-validation-of-a-biometric-solution-for-remote-monitoring-of-motor-symptoms-in-patients-with-huntington-disease-in-a-phase-ii-clinical-trial/. Accessed December 5, 2023.
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