A lightweight sensing platform for monitoring sleep quality and posture: a simulated validation study

BackgroundThe prevalence of self-reported shoulder pain in the UK has been estimated at 16%. This has been linked with significant sleep disturbance. It is possible that this relationship is bidirectional, with both symptoms capable of causing the other. Within the field of sleep monitoring, there is a requirement for a mobile and unobtrusive device capable of monitoring sleep posture and quality. This study investigates the feasibility of a wearable sleep system (WSS) in accurately detecting sleeping posture and physical activity.MethodsSixteen healthy subjects were recruited and fitted with three wearable inertial sensors on the trunk and forearms. Ten participants were entered into a ‘Posture’ protocol; assuming a series of common sleeping postures in a simulated bedroom. Five participants completed an ‘Activity’ protocol, in which a triphasic simulated sleep was performed including awake, sleep and REM phases. A combined sleep posture and activity protocol was then conducted as a ‘Proof of Concept’ model. Data were used to train a posture detection algorithm, and added to activity to predict sleep phase. Classification accuracy of the WSS was measured during the simulations.ResultsThe WSS was found to have an overall accuracy of 99.5% in detection of four major postures, and 92.5% in the detection of eight minor postures. Prediction of sleep phase using activity measurements was accurate in 97.3% of the simulations. The ability of the system to accurately detect both posture and activity enabled the design of a conceptual layout for a user-friendly tablet application.ConclusionsThe study presents a pervasive wearable sensor platform, which can accurately detect both sleeping posture and activity in non-specialised environments. The extent and accuracy of sleep metrics available advances the current state-of-the-art technology. This has potential diagnostic implications in musculoskeletal pathology and with the addition of alerts may provide therapeutic value in a range of areas including the prevention of pressure sores.

[1]  Michelle Urwin,et al.  Estimating the burden of musculoskeletal disorders in the community: the comparative prevalence of symptoms at different anatomical sites, and the relation to social deprivation , 1998, Annals of the rheumatic diseases.

[2]  F A Matsen,et al.  A prospective, multipractice study of shoulder function and health status in patients with documented rotator cuff tears. , 2000, Journal of shoulder and elbow surgery.

[3]  F. J. Nieto,et al.  The association of sleep-disordered breathing and sleep symptoms with quality of life in the Sleep Heart Health Study. , 2001, Sleep.

[4]  C W Whitney,et al.  Sleep-disordered breathing and cardiovascular disease: cross-sectional results of the Sleep Heart Health Study. , 2001, American journal of respiratory and critical care medicine.

[5]  H. Nagaraja,et al.  How accurately does wrist actigraphy identify the states of sleep and wakefulness? , 2001, Sleep.

[6]  Thomas Penzel,et al.  Effect of Nasal Continuous Positive Airway Pressure Treatment on Blood Pressure in Patients With Obstructive Sleep Apnea , 2003, Circulation.

[7]  H Harry Asada,et al.  Wearable Conductive Fiber Sensors for Multi-Axis Human Joint Angle Measurements , 2005, Journal of NeuroEngineering and Rehabilitation.

[8]  E. Sazonov,et al.  Sleep-wake identification in infants: heart rate variability compared to actigraphy , 2004, The 26th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[9]  S. Redline,et al.  Sleep-disordered breathing, glucose intolerance, and insulin resistance: the Sleep Heart Health Study. , 2004, American journal of epidemiology.

[10]  Kamiar Aminian,et al.  A new approach to accurate measurement of uniaxial joint angles based on a combination of accelerometers and gyroscopes , 2005, IEEE Transactions on Biomedical Engineering.

[11]  A. Carr,et al.  Prevalence and incidence of adults consulting for shoulder conditions in UK primary care; patterns of diagnosis and referral. , 2006, Rheumatology.

[12]  I. Parsons,et al.  Deficits in shoulder function and general health associated with sixteen common shoulder diagnoses: a study of 2674 patients. , 2006, Journal of shoulder and elbow surgery.

[13]  J. Carrier,et al.  Wake detection capacity of actigraphy during sleep. , 2007, Sleep.

[14]  Akram Khan,et al.  Effects of obstructive sleep apnea treatment on left atrial volume and left atrial volume index , 2008, Sleep and Breathing.

[15]  Reliability of arthrometric measurement of shoulder lateral rotation movement in healthy subjects , 2007, Physiotherapy theory and practice.

[16]  Pagamas Piriyaprasarth,et al.  The reliability of knee joint position testing using electrogoniometry , 2008, BMC musculoskeletal disorders.

[17]  K. Aminian,et al.  Ambulatory measurement of 3D knee joint angle. , 2008, Journal of biomechanics.

[18]  Chi-Chun Hsia,et al.  Bayesian classification for bed posture detection based on kurtosis and skewness estimation , 2008, HealthCom 2008 - 10th International Conference on e-health Networking, Applications and Services.

[19]  J. Biswas,et al.  Analysis and comparison of sleeping posture classification methods using pressure sensitive bed system , 2009, 2009 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[20]  Diana Hodgins,et al.  Inertial sensor-based knee flexion/extension angle estimation. , 2009, Journal of biomechanics.

[21]  Weimin Huang,et al.  Multimodal Sleeping Posture Classification , 2010, 2010 20th International Conference on Pattern Recognition.

[22]  C. Gerber,et al.  Subacromial pressures vary with simulated sleep positions. , 2010, Journal of shoulder and elbow surgery.

[23]  Enamul Hoque,et al.  Monitoring body positions and movements during sleep using WISPs , 2010, Wireless Health.

[24]  J. Zenian,et al.  Sleep position and shoulder pain. , 2010, Medical hypotheses.

[25]  Andreas Schrempf,et al.  Measuring nightly activity, body weight and body weight change rate with a sensor equipped bed , 2010, 2010 Annual International Conference of the IEEE Engineering in Medicine and Biology.

[26]  Nadezhda Sazonova,et al.  AASM standards of practice compliant validation of actigraphic sleep analysis from SOMNOwatch™ versus polysomnographic sleep diagnostics shows high conformity also among subjects with sleep disordered breathing , 2010, Physiological measurement.

[27]  Miad Faezipour,et al.  Bed posture classification for pressure ulcer prevention , 2011, 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[28]  Kang-Ming Chang,et al.  Wireless portable electrocardiogram and a tri-axis accelerometer implementation and application on sleep activity monitoring. , 2011, Telemedicine journal and e-health : the official journal of the American Telemedicine Association.

[29]  Guang-Zhong Yang,et al.  Human Back Movement Analysis Using BSN , 2011, 2011 International Conference on Body Sensor Networks.

[30]  Guang-Zhong Yang,et al.  2011 International Conference on Body Sensor Networks BSN 2011 Table of Contents , 2011 .

[31]  Mark Donnelly,et al.  Impact Analysis of Solutions for Chronic Disease Prevention and Management , 2012, Lecture Notes in Computer Science.

[32]  Xingshe Zhou,et al.  Multi-modal Non-intrusive Sleep Pattern Recognition in Elder Assistive Environment , 2012, ICOST.

[33]  L. Meltzer,et al.  Direct comparison of two new actigraphs and polysomnography in children and adolescents. , 2012, Sleep.

[34]  A. Kongsted,et al.  Association between the side of unilateral shoulder pain and preferred sleeping position: a cross-sectional study of 83 Danish patients. , 2012, Journal of manipulative and physiological therapeutics.

[35]  Homer Nazeran,et al.  Automatic sleep staging using empirical mode decomposition, discrete wavelet transform, time-domain, and nonlinear dynamics features of heart rate variability signals , 2013, Comput. Methods Programs Biomed..

[36]  J. Jenny,et al.  Measurement of the knee flexion angle with a Smartphone-application is precise and accurate. , 2013, The Journal of arthroplasty.

[37]  K. Song,et al.  Is shoulder pain for three months or longer correlated with depression, anxiety, and sleep disturbance? , 2013, Journal of shoulder and elbow surgery.

[38]  C. Gay,et al.  Pain characteristics and self-rated health after elective orthopaedic surgery - a cross-sectional survey. , 2013, Journal of clinical nursing.

[39]  Validating actigraphy as a measure of sleep for preschool children. , 2013, Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine.

[40]  Jenny Jean-Yves Measurement of the Knee Flexion Angle With a Smartphone: Application Is Precise and Accurate , 2018 .