Sleep Quality Monitoring with the Smart Bed

Waltisberg, Daniel; Arnrich, Bert; Tröster, Gerhard

doi:10.1007/978-1-4471-6413-5_9

Cited by 11 publications

(12 citation statements)

References 44 publications

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“…In addition to detecting different sleep stages, this system can estimate the depth of sleep, number of apneic episodes and periodicity, and detect early symptoms of sleep disorders. A detailed review on smart beds based on piezoelectric and pressure sensors can be found in [ 127 ]. Although these systems are useful to estimate the quality of sleep and some of them used the pressure sensor data to estimate the RR [ 126 ], they are not capable of providing detailed information about the vital signs.…”

Section: Smart Monitoring Systems For Elderly and People With Disamentioning

confidence: 99%

Smart Homes for Elderly Healthcare—Recent Advances and Research Challenges

Majumder

Aghayi

Noferesti

et al. 2017

Sensors

466

267

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Advancements in medical science and technology, medicine and public health coupled with increased consciousness about nutrition and environmental and personal hygiene have paved the way for the dramatic increase in life expectancy globally in the past several decades. However, increased life expectancy has given rise to an increasing aging population, thus jeopardizing the socio-economic structure of many countries in terms of costs associated with elderly healthcare and wellbeing. In order to cope with the growing need for elderly healthcare services, it is essential to develop affordable, unobtrusive and easy-to-use healthcare solutions. Smart homes, which incorporate environmental and wearable medical sensors, actuators, and modern communication and information technologies, can enable continuous and remote monitoring of elderly health and wellbeing at a low cost. Smart homes may allow the elderly to stay in their comfortable home environments instead of expensive and limited healthcare facilities. Healthcare personnel can also keep track of the overall health condition of the elderly in real-time and provide feedback and support from distant facilities. In this paper, we have presented a comprehensive review on the state-of-the-art research and development in smart home based remote healthcare technologies.

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Section: Smart Monitoring Systems For Elderly and People With Disamentioning

confidence: 99%

Smart Homes for Elderly Healthcare—Recent Advances and Research Challenges

Majumder

Aghayi

Noferesti

et al. 2017

Sensors

466

267

View full text Add to dashboard Cite

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“…Sleep is a relaxed state that still contains self-induced movements, mainly to prevent pressure ulcers [7]. These self-induced movements are defined as movement states that create behavior over time.…”

Section: A Movement Behaviormentioning

confidence: 99%

“…the functioning of the applied devices during the night [7]. Research on PSG is currently focusing on how to reduce the number of sensors while automatically recognizing the main sleep behavior measurements.…”

Section: ) Polysomnographymentioning

confidence: 99%

“…The device is widely accepted for objective sleep quality measurements. An actigraph is a wearable device attached to the nondominant wrist, providing information about sleep-wake patterns during the night [7]. The device can be used at home, which has the advantage of interfering less with natural sleeping behavior.…”

Section: ) Actigraph Unitmentioning

confidence: 99%

“…Nonwearable sensors are widely applied, such as load cells, force sensors, air cushions, pressure pads, water-filled vinyl tubes [7], smartphones [31], [63], Shimmer sensors [10], Doppler radar signals [64], [65] also with sound signals [65], [66], pressure sensors [16], [17], [17], [20]- [22], [67], and radio signals [68]. Air cushions under the bed collect data such as respiration rate, heart rate, and body movement to estimate sleep stages.…”

Section: ) Nonwearable Technologymentioning

confidence: 99%

See 2 more Smart Citations

Computational Sleep Behavior Analysis: A Survey

Fallmann

Chen

2019

IEEE Access

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Sleep is a key marker of health, as it can either be a cause or a consequence. It is traditionally studied in clinical environments using dedicated medical devices. Recent technological developments, e.g., in sensing and data analysis, have led to new approaches for sleep monitoring and assessment, which are attracting increasing attention in the emerging domain of personalized smart healthcare. Nevertheless, a highlevel overview of technology-enabled research on sleep that can inform related communities of the latest developments is lacking. In this paper, we present a comprehensive review to examine the current status of various aspects of technology-based sleep research. We first characterize sleep behavior and key areas of sleep assessment, and we introduce a general review of the methodologies used in this domain. We review the major technological methods and trends associated with sleep monitoring, data collection and sleep behavior analysis, from which strengths and weaknesses are highlighted. Finally, we also discuss challenges and promising directions for future research.

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