Comparison of physical activity sensors and heart rate monitoring for real-Time activity detection in type 1 diabetes and control subjects

Chinmay Manohar, Derek T. O'Keeffe, Ling Hinshaw, Ravi Lingineni, Shelly K. McCrady-Spitzer, James A. Levine, Rickey E. Carter, Ananda Basu, Yogish C Kudva

Research output: Contribution to journalArticle

2 Scopus citations

Abstract

Background: Currently, patients with type 1 diabetes decide on the amount of insulin to administer based on several factors, including current plasma glucose value, expected meal input, and physical activity (PA). One future therapeutic modality for patients with type 1 diabetes is the artificial endocrine pancreas (AEP). Incorporation of PA could enhance the efficacy of AEP significantly. We compared the main technologies used for PA quantitation. Subjects and Methods: Data were collected during inpatient studies involving healthy control subjects and type 1 diabetes. We report PA quantified from accelerometers (acceleration units [AU]) and heart rate (HR) monitors during a standardized activity protocol performed after a dinner meal at 7 p.m. from nine control subjects (four were males, 37.4±12.7 years old, body mass index of 24.8±3.8 kg/m2, and fasting plasma glucose of 4.71±0.63 mmol/L) and eight with type 1 diabetes (six were males, 45.2±13.4 years old, body mass index of 25.1±2.9 kg/m2, and fasting plasma glucose of 8.44±2.31 mmol/L). Results: The patient-To-patient variability was considerably less when examining AU compared with HR monitors. Furthermore, the exercise bouts and rest periods were more evident from the data streams when AUs were used to quantify activity. Unlike the AU, the HR measurements provided little insight for active and rest stages, and HR data required patient-specific standardizations to discern any meaningful pattern in the data. Conclusions: Our results indicated that AU provides a reliable signal in response to PA, including low-intensity activity. Correlation of this signal with continuous glucose monitoring data would be the next step before exploring inclusion as input for AEP control.

Original languageEnglish (US)
Pages (from-to)751-757
Number of pages7
JournalDiabetes Technology and Therapeutics
Volume15
Issue number9
DOIs
StatePublished - Sep 1 2013

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ASJC Scopus subject areas

  • Endocrinology
  • Medical Laboratory Technology
  • Endocrinology, Diabetes and Metabolism
  • Medicine(all)

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