title: Design of the health monitoring system for the artificial pancreas: low glucose prediction module.
abstract: BACKGROUND
  The purpose of this study was to design and evaluate a safety system for the artificial pancreas device system (APDS). Safe operation of the APDS is a critical task, where the safety system is engaged only as needed to ensure reliable operation without positive feedback to the controller.
  
  
  METHODS
  The Health Monitoring System (HMS) was designed as a modular system to ensure the safety of the APDS and the user. It was designed using a large set of ambulatory data and evaluated in silico by inducing hypoglycemia with a missed meal [bolus for a 65 g carbohydrate (CHO) meal] and administering rescue CHOs per HMS alerting. The HMS was validated in-clinic with a real-life challenge of a subject who overdosed insulin prior to admission.
  
  
  RESULTS
  The HMS was evaluated for clinical use with a 15 min prediction horizon. Retrospectively, 93.5% of episodes were detected with 2.9 false alarms per day. During in silico evaluation, the HMS reduced the time spent <70 mg/dl from 15% to 3%. When the HMS was first tested in-clinic, the subject overdosed ~3 U of insulin prior to her arrival to a closed-loop session (against protocol). The controller reduced insulin delivery, and the HMS gave four alerts that were successfully received via clinical software and text and multimedia messages. Even with insulin reduction and CHO supplements, hypoglycemia was unavoidable but manageable due to the HMS, confirming that a safety system to detect adverse events is an essential part of the APDS.
  
  
  CONCLUSIONS
  The ability of the HMS to be an effective alert system that provides a safety layer to the APDS controller has been demonstrated in a clinical setting.
authors.affiliation: Department of Chemical Engineering, University of California, Santa Barbara, Santa Barbara, CA 93106, USA.
authors.forename: Rebecca A
authors.initials: RA
authors.lastname: Harvey
authors.forename: Eyal
authors.initials: E
authors.lastname: Dassau
authors.forename: Howard
authors.initials: H
authors.lastname: Zisser
authors.forename: Dale E
authors.initials: DE
authors.lastname: Seborg
authors.forename: Lois
authors.initials: L
authors.lastname: Jovanovič
authors.forename: Francis J
authors.initials: FJ
authors.lastname: Doyle
mesh_terms: D000465:Algorithms; D015190:Blood Glucose Self-Monitoring / Q000295:instrumentation* / Q000379:methods; D003922:Diabetes Mellitus, Type 1 / Q000628:therapy*; D005260:Female; D006801:Humans; D006943:Hyperglycemia / Q000517:prevention & control*; D007003:Hypoglycemia / Q000517:prevention & control*; D007328:Insulin / Q000627:therapeutic use; D007332:Insulin Infusion Systems; D019397:Pancreas, Artificial
chemical_list: D007328:Insulin