Emfit Bed Sensor Activity Shows Strong Agreement with Wrist Actigraphy for the Assessment of Sleep in the Home Setting
Juan Piantino,1 Madison Luther,1 Christina Reynolds,2 Miranda M Lim2– 4 1Department of Pediatrics, Division of Child Neurology, Doernbecher Children’s Hospital, Oregon Health and Science University, Portland, OR, USA; 2Department of Neurology, Department of Medicine, Division of Pulmonary and Critic...
Guardado en:
Autores principales: | , , , |
---|---|
Formato: | article |
Lenguaje: | EN |
Publicado: |
Dove Medical Press
2021
|
Materias: | |
Acceso en línea: | https://doaj.org/article/360bd66b25f343e1a0e0cbb9299903a7 |
Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Sumario: | Juan Piantino,1 Madison Luther,1 Christina Reynolds,2 Miranda M Lim2– 4 1Department of Pediatrics, Division of Child Neurology, Doernbecher Children’s Hospital, Oregon Health and Science University, Portland, OR, USA; 2Department of Neurology, Department of Medicine, Division of Pulmonary and Critical Care Medicine, Department of Behavioral Neuroscience, Oregon Health & Science University, Portland, OR, USA; 3Oregon Institute of Occupational Health Sciences, Oregon Health & Science University, Portland, OR, USA; 4Neurology Research Service and National Center for Rehabilitative Auditory Research, VA Portland Health Care System, Portland, OR, USACorrespondence: Juan Piantino Email piantino@ohsu.eduPurpose: Wrist-worn actigraphy via research-grade devices, a well-established approach to the assessment of rest-activity, is limited by poor compliance, battery life, and lack of direct evidence for time spent physically in the bed. A non-invasive bed sensor (Emfit) may provide advantages over actigraphy for long-term sleep assessment in the home. This study compared sleep-wake measurements between this sensor and a validated actigraph.Patients and Methods: Thirty healthy subjects (6 to 54 years) underwent simultaneous monitoring with both devices for 14 days and filled out a daily sleep diary. Parameters included bed entry time, sleep start, sleep end, bed exit time, rest interval duration, and wake after sleep onset (WASO). The agreement between the two devices was measured using Bland–Altman plots and inter-class correlation coefficients (ICC). In addition, sensitivity, specificity, and accuracy were obtained from epoch-by-epoch comparisons of Emfit and actigraphy.Results: Fifteen percent of the subjects reported that wearing the actigraph was a burden. None reported that using the bed sensor was a burden. The minimal detectable change between Emfit and actigraphy was 11 minutes for bed entry time, 14 minutes for sleep start, 14 minutes for sleep end, 10 minutes for bed exit time, 20 minutes for rest interval duration, and 110 minutes for WASO. Inter-class correlation coefficients revealed an excellent agreement for all sleep parameters (ICC=0.99, 95% CI 98– 99) except for WASO (ICC=0.46, 95% CI 0.33– 0.56). Sensitivity, specificity, and accuracy were 0.62, 0.93, and 0.88, respectively. Kappa correlation analysis revealed a moderate correlation between the two devices (κ=0.55, p< 0.0001).Conclusion: Emfit is an acceptable alternative to actigraphy for the estimation of bed entry time, sleep start, sleep end, bed exit time, and rest interval duration. However, WASO estimates are poorly correlated between the two devices. Emfit may offer methodological advantages in situations where actigraphy is challenging to implement.Keywords: Actiwatch 2, Emfit, ambulatory, sleep-wake monitoring |
---|