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Functional measurement post-stroke via mobile application and body-worn sensor technology.

Nancy Fell1, Hanna H True1, Brandon Allen2

  • 1Department of Physical Therapy, University of Tennessee at Chattanooga, Chattanooga, TN, USA.

Mhealth
|November 16, 2019
PubMed
Summary

The mStroke mobile health system shows promise for remote stroke recovery monitoring, correlating well with clinical assessments. Further development is recommended for this innovative patient support technology.

Keywords:
Mobile applicationsstrokestroke rehabilitationtelemedicine

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Area of Science:

  • Neurology
  • Rehabilitation Medicine
  • Digital Health

Background:

  • Long-term stroke management is crucial for chronic disability and recurrent stroke prevention.
  • Mobile health (mHealth) offers a promising, cost-effective solution for remote patient monitoring and support.
  • Effective mHealth systems require collaboration between healthcare providers and developers to define meaningful remote data collection measures.

Purpose of the Study:

  • To evaluate the mStroke mobile health system for remote data collection in stroke survivors.
  • To assess the correlation between mStroke system measurements and standardized clinical assessments.
  • To explore the utility of the International Classification of Functioning, Disability and Health (ICF) model in guiding mHealth development.

Main Methods:

  • The mStroke system, comprising sensors and a mobile app, was developed based on the ICF model.
  • Four common clinical measures (NIHSS items 5 & 6, FRT, 10MWT) were integrated into the app for remote data collection.
  • 35 stroke survivors underwent simultaneous assessment using the mStroke system and standard clinical evaluations.

Main Results:

  • All four clinical measures demonstrated significant correlation with mStroke system scoring.
  • High correlations were observed for NIHSS Motor Leg (0.736) and 10 Meter Walk Test (0.994).
  • NIHSS Motor Arm (0.839) and Functional Reach Test (0.630) also showed significant correlations, though with noted data skew and limitations for broad translation.

Conclusions:

  • The mStroke system shows potential for clinically meaningful remote measurement in stroke recovery.
  • Further investment in refining and testing mHealth systems for remote data collection is warranted.
  • The ICF model effectively guided collaborative development between clinicians and application developers.