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DISPEL: A Python Framework for Developing Measures From Digital Health Technologies.

A Scotland1, G Cosne1, A Juraver1

  • 1Biogen, Cambridge, Massachusetts Cambridge MA 02142 USA.

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|July 25, 2024
PubMed
Summary
This summary is machine-generated.

DISPEL is a new Python framework for creating sensor-derived measures (SDMs) from digital health technology data in neurodegenerative disease therapeutic development. It standardizes SDM generation and processing, supporting clinical trials.

Keywords:
Signal processingbalancecognitiondigital biomarkersdigital health technologydrawinggaitinertial sensorpythonsmartphonewearable sensing

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Area of Science:

  • Digital Health
  • Neurodegenerative Diseases
  • Biomedical Engineering

Background:

  • Digital health technologies generate vast amounts of data relevant to neurodegenerative disease progression.
  • Developing reliable sensor-derived measures (SDMs) from this data is crucial for therapeutic development.
  • Existing frameworks often lack modularity, standardization, and robust handling of real-world data issues.

Purpose of the Study:

  • Introduce DISPEL, a novel Python framework designed to streamline the development of sensor-derived measures (SDMs).
  • Facilitate the use of digital health technology data in therapeutic development for neurodegenerative diseases.
  • Provide a standardized, flexible, and integrable solution for SDM extraction and processing.

Main Methods:

  • Employed an object-oriented architecture for modular data modeling and SDM extraction.
  • Implemented systematic flagging for missing data and unexpected user behaviors common in unsupervised monitoring.
  • Ensured standardization of SDM generation, naming, storage, and documentation.

Main Results:

  • DISPEL is an open-source (MIT license) Python framework supporting various data formats.
  • It enables traceable end-to-end processing from raw wearable and smartphone data to structured SDM datasets.
  • Currently extracts SDMs from 16 structured tests (including questionnaires) assessing disability, quality of life, cognition, dexterity, and mobility.

Conclusions:

  • DISPEL provides a production-grade framework to support SDM development for clinical trials.
  • The framework includes a comprehensive set of pre-implemented SDMs, refined using clinical trial data.
  • Users are advised to perform context-specific validation of the provided algorithms for their intended use.