Quantification of Movement in Stroke Patients under Free Living Conditions Using Wearable Sensors: A Systematic Review

Research output: Contribution to journalReview articlepeer-review

9 Citations (Scopus)
124 Downloads (Pure)

Abstract

Stroke is a main cause of long-term disability worldwide, placing a large burden on individuals and health care systems. Wearable technology can potentially objectively assess and monitor patients outside clinical environments, enabling a more detailed evaluation of their impairment and allowing individualization of rehabilitation therapies. The aim of this review is to provide an overview of setups used in literature to measure movement of stroke patients under free living conditions using wearable sensors, and to evaluate the relation between such sensor-based outcomes and the level of functioning as assessed by existing clinical evaluation methods. After a systematic search we included 32 articles, totaling 1076 stroke patients from acute to chronic phases and 236 healthy controls. We summarized the results by type and location of sensors, and by sensor-based outcome measures and their relation with existing clinical evaluation tools. We conclude that sensor-based measures of movement provide additional information in relation to clinical evaluation tools assessing motor functioning and both are needed to gain better insight in patient behavior and recovery. However, there is a strong need for standardization and consensus, regarding clinical assessments, but also regarding the use of specific algorithms and metrics for unsupervised measurements during daily life.

Original languageEnglish
Article number1050
Number of pages45
JournalSensors
Volume22
Issue number3
DOIs
Publication statusPublished - 1-Feb-2022

Keywords

  • stroke
  • activities of daily living
  • continuous monitoring
  • wearables
  • movement quantification
  • UPPER-LIMB ACTIVITY
  • WORLD ARM ACTIVITY
  • SUBACUTE STROKE
  • PHYSICAL-ACTIVITY
  • RECOVERY
  • ACCELEROMETRY
  • REHABILITATION
  • GAIT
  • PREDICTION
  • VALIDITY

Fingerprint

Dive into the research topics of 'Quantification of Movement in Stroke Patients under Free Living Conditions Using Wearable Sensors: A Systematic Review'. Together they form a unique fingerprint.

Cite this