title: Feasibility of three wearable sensors for 24 hour monitoring in middle-aged women.
abstract: BACKGROUND
  The purpose of this study is to determine the feasibility of three widely used wearable sensors in research settings for 24 h monitoring of sleep, sedentary, and active behaviors in middle-aged women.
  
  
  METHODS
  Participants were 21 inactive, overweight (M Body Mass Index (BMI) = 29.27 ± 7.43) women, 30 to 64 years (M = 45.31 ± 9.67). Women were instructed to wear each sensor on the non-dominant hip (ActiGraph GT3X+), wrist (GENEActiv), or upper arm (BodyMedia SenseWear Mini) for 24 h/day and record daily wake and bed times for one week over the course of three consecutive weeks. Women received feedback about their daily physical activity and sleep behaviors. Feasibility (i.e., acceptability and demand) was measured using surveys, interviews, and wear time.
  
  
  RESULTS
  Women felt the GENEActiv (94.7%) and SenseWear Mini (90.0%) were easier to wear and preferred the placement (68.4, 80% respectively) as compared to the ActiGraph (42.9, 47.6% respectively). Mean wear time on valid days was similar across sensors (ActiGraph: M = 918.8 ± 115.0 min; GENEActiv: M = 949.3 ± 86.6; SenseWear: M = 928.0 ± 101.8) and well above other studies using wake time only protocols. Informational feedback was the biggest motivator, while appearance, comfort, and inconvenience were the biggest barriers to wearing sensors. Wear time was valid on 93.9% (ActiGraph), 100 % (GENEActiv), and 95.2% (SenseWear) of eligible days. 61.9, 95.2, and 71.4% of participants had seven valid days of data for the ActiGraph, GENEActiv, and SenseWear, respectively.
  
  
  CONCLUSIONS
  Twenty-four hour monitoring over seven consecutive days is a feasible approach in middle-aged women. Researchers should consider participant acceptability and demand, in addition to validity and reliability, when choosing a wearable sensor. More research is needed across populations and study designs.
authors.affiliation: School of Nutrition and Health Promotion, Arizona State University, Phoenix, AZ, USA. Jhuberty@asu.edu.
authors.forename: Jennifer
authors.initials: J
authors.lastname: Huberty
authors.affiliation: School of Nutrition and Health Promotion, Arizona State University, Phoenix, AZ, USA. dkehlers@asu.edu.
authors.forename: Diane K
authors.initials: DK
authors.lastname: Ehlers
authors.affiliation: School of Nutrition and Health Promotion, Arizona State University, Phoenix, AZ, USA. jkurka@asu.edu.
authors.forename: Jonathan
authors.initials: J
authors.lastname: Kurka
authors.affiliation: School of Nutrition and Health Promotion, Arizona State University, Phoenix, AZ, USA. barbara.ainsworth@asu.edu.
authors.forename: Barbara
authors.initials: B
authors.lastname: Ainsworth
authors.affiliation: School of Nutrition and Health Promotion, Arizona State University, Phoenix, AZ, USA. matthew.buman@asu.edu.
authors.forename: Matthew
authors.initials: M
authors.lastname: Buman
mesh_terms: D056044:Actigraphy / Q000379:methods*; D000328:Adult; D005240:Feasibility Studies; D005260:Female; D015438:Health Behavior; D006801:Humans; D008019:Life Style; D008875:Middle Aged; D018670:Monitoring, Ambulatory / Q000379:methods; D009043:Motor Activity; D009765:Obesity / Q000453:epidemiology; D057185:Sedentary Behavior; D016387:Women's Health