PMID- 29848376
OWN - NLM
STAT- MEDLINE
DCOM- 20181001
LR  - 20191210
IS  - 2047-783X (Electronic)
IS  - 0949-2321 (Print)
IS  - 0949-2321 (Linking)
VI  - 23
IP  - 1
DP  - 2018 May 30
TI  - A lightweight sensing platform for monitoring sleep quality and posture: a 
      simulated validation study.
PG  - 28
LID - 10.1186/s40001-018-0326-9 [doi]
LID - 28
AB  - BACKGROUND: The 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. METHODS: Sixteen 
      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. RESULTS: The 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. CONCLUSIONS: The 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.
FAU - Kwasnicki, Richard M
AU  - Kwasnicki RM
AD  - Department of Surgery and Cancer, Imperial College London, 10th Floor QEQM 
      Building, St. Mary's Hospital, Praed Street, London, W2 1NY, UK. 
      richard.kwasnicki07@imperial.ac.uk.
AD  - The Hamlyn Centre, Institute of Global Health Innovation, Imperial College 
      London, London, UK. richard.kwasnicki07@imperial.ac.uk.
FAU - Cross, George W V
AU  - Cross GWV
AD  - Department of Surgery and Cancer, Imperial College London, 10th Floor QEQM 
      Building, St. Mary's Hospital, Praed Street, London, W2 1NY, UK.
FAU - Geoghegan, Luke
AU  - Geoghegan L
AD  - Department of Surgery and Cancer, Imperial College London, 10th Floor QEQM 
      Building, St. Mary's Hospital, Praed Street, London, W2 1NY, UK.
FAU - Zhang, Zhiqiang
AU  - Zhang Z
AD  - The Hamlyn Centre, Institute of Global Health Innovation, Imperial College 
      London, London, UK.
FAU - Reilly, Peter
AU  - Reilly P
AD  - Imperial College Healthcare NHS Trust, London, UK.
FAU - Darzi, Ara
AU  - Darzi A
AD  - The Hamlyn Centre, Institute of Global Health Innovation, Imperial College 
      London, London, UK.
FAU - Yang, Guang Zhong
AU  - Yang GZ
AD  - The Hamlyn Centre, Institute of Global Health Innovation, Imperial College 
      London, London, UK.
FAU - Emery, Roger
AU  - Emery R
AD  - Imperial College Healthcare NHS Trust, London, UK.
LA  - eng
PT  - Journal Article
PT  - Validation Study
DEP - 20180530
PL  - England
TA  - Eur J Med Res
JT  - European journal of medical research
JID - 9517857
SB  - IM
MH  - Actigraphy/*instrumentation
MH  - Adult
MH  - Algorithms
MH  - Female
MH  - Humans
MH  - Male
MH  - *Posture
MH  - *Sleep
MH  - *Wearable Electronic Devices
MH  - Young Adult
PMC - PMC5975552
OTO - NOTNLM
OT  - Activity
OT  - Monitoring
OT  - Pervasive
OT  - Posture
OT  - Sensors
OT  - Shoulder
OT  - Sleep
OT  - Wearables
EDAT- 2018/06/01 06:00
MHDA- 2018/10/03 06:00
PMCR- 2018/05/30
CRDT- 2018/06/01 06:00
PHST- 2018/03/17 00:00 [received]
PHST- 2018/05/18 00:00 [accepted]
PHST- 2018/06/01 06:00 [entrez]
PHST- 2018/06/01 06:00 [pubmed]
PHST- 2018/10/03 06:00 [medline]
PHST- 2018/05/30 00:00 [pmc-release]
AID - 10.1186/s40001-018-0326-9 [pii]
AID - 326 [pii]
AID - 10.1186/s40001-018-0326-9 [doi]
PST - epublish
SO  - Eur J Med Res. 2018 May 30;23(1):28. doi: 10.1186/s40001-018-0326-9.